research on football betting

Boost Your Game with Accurate Football Statistics and Predictions

Experience the best football statistics and analysis tools, and save countless hours of daily research.

• Customize your match list to fit your needs
• Get predictions based on team performance
• Check the highest percentages for each market

• Stats by matches
• +0,5 goals 1H
• +1,5 goals 1H
• +2,5 goals 1H
• +0,5 goals 2H
• +1,5 goals 2H
• +2,5 goals 2H
• +2,5 goals & BTTS
• Conceded +1
• Conceded +2
• Conceded +3
• Scored both halves
• Most goals in 1H
• Most goals in 2H
• Most goals = X
• 1st goal scored
• +6,5 corners
• +7,5 corners
• +8,5 corners
• +9,5 corners
• +10,5 corners
• +11,5 corners
• +12,5 corners
• Corners AVG

BettingStats.org - Football predictions and Free Soccer Stats

Looking for a comprehensive website for all your football betting statistics and tips? Look no further than BettingStats.org! Our website is designed to provide gamblers with everything they need to make informed betting decisions, all in one convenient location.

At BettingStats, we know that time is money, which is why we created our website to save you hours of research every day. With our user-friendly design and detailed football stats, you can easily access high-quality and valuable information, without having to spend hours scouring the internet for the data you need.

Our football stats are carefully analyzed to increase your chances of winning in betting, and we present them in a beautiful and easy-to-use interface. With BettingStats, you can get a quick overview of today’s football matches and access all the stats you need in one place.

By using our statistics, you can quickly gain knowledge about a team’s performance in each market, allowing you to choose the right bets and markets for your wagers. So, whether you’re a seasoned gambler or just starting out, BettingStats is the ultimate destination for football predictions and free soccer stats.

Which football stats do you offer?

We have football stats from +200 leagues and tournaments worldwide.  

Also we support a lot of different football stats such as:

• Goals stats
• Corners stats
• Cards stats
• 1st half stats
• 2nd half stats
• 1×2 stats
• Player stats
• Referee stats
• League stats
• Over/under stats
• And much more

Football predictions

Looking for a way to save time on your football betting research? BettingStats.org has got you covered with our expert football predictions! Our system calculates the percentage of all teams and lists them in order, with the highest number appearing first.

How do we do it? By analyzing the last 5 or 10 matches for each team and comparing their stats in each market, we can give you an average for that market. This means that our stats aren’t just based on winning percentages, but on the average performance of both teams in their last 5 to 10 matches. You can easily select the markets you want to see and find the matches with the highest average percentage.

But that’s not all BettingStats offers. We also provide you with the ability to check scores, fixtures, sports results, player stats, goal stats, corner stats, card stats, BTTS stats, over/under stats, and more for over 200 leagues and tournaments worldwide. With all this information in one place, you can make informed betting decisions quickly and easily.

So why waste time researching football matches on your own when you can rely on BettingStats for accurate predictions and comprehensive statistics? Join us today and start winning big on football!

Find the best and most attractive football stats on our website

Our website offers a wide range of leagues, from the biggest and most prestigious competitions like the Champions League and Europa League, to smaller leagues like the Ukrainian and Danish leagues.

At BettingStats, we’re committed to providing every user with daily analyzed football stats to help them make informed betting decisions. Our website features color-coded statistics and filtering options, making it quick and easy for you to get an overview of the day’s football matches. Plus, we’ve made it simple for users to customize their favorite stats board to their exact needs, so you can easily find the scores and information you’re looking for every time you visit BettingStats.

So why waste time scouring the internet for the latest football stats when you can find everything you need in one convenient location? Join us today and explore our huge archive of the most popular football matches!

What can I use the football stats for?

At BettingStats.org, we offer a wealth of football statistics and analysis to help you make informed betting decisions. But you may be wondering: what can you actually use these stats for?

First and foremost, our football stats can help you gain a better understanding of each team’s strengths and weaknesses. By analyzing factors like goals scored and conceded, as well as shots on target and possession, you can identify trends and patterns that may influence the outcome of a match.

Our stats can also help you make smarter betting decisions by providing you with valuable insights into each team’s performance in various markets. For example, by analyzing a team’s over/under stats, you can get a better sense of whether they tend to play high-scoring or low-scoring matches.

Beyond betting, our football stats can be used for a variety of purposes, such as fantasy football and general sports analysis. By staying up-to-date on the latest statistics and trends, you can gain a competitive edge and improve your overall knowledge of the sport.

So whether you’re a seasoned bettor or simply a football fan looking to stay informed, our comprehensive football stats have something to offer. Visit BettingStats.org today to explore our full range of football statistics and analysis!

Benefits of using Betting Stats - Increase your betting profit.

• Save hours daily on analyzing football stats
• Get quick overview of todays football matches
• Customize the stats table exactly for your needs
• Check todays football predictions
• Get better knowledge of the matches
• Predictions

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The 10 Best Football Websites for Stats & Analysis (2024)

Here at ThePuntersPage.com (TPP) we’re dedicated to building a trustworthy brand and strive to provide the very best content and offers for our readers. Please note that some of the links included on TPP may be affiliate links, which means we may earn a commission (at no additional cost to you) if you click on a link and subsequently open an account. We only recommend products and companies we use and trust. To learn more, visit our About Us Page .

If you want to make the most out of your bets, you must refrain from betting with your gut. How? By using the best football websites for stats and analysis! With numerous web sources and multiple ways of using them, let's explore our top picks.

• 1 Football Betting Stats & Analysis Sites: Top 10
• 2 The Importance of Stats Analysis in Football Betting
• 3 Top 10 Football Stats Sites for Odds, Rankings, Tips, & Predictions
• 4 Top Football Analysis Sites Compared
• 5 Why These Football Analysis Sites Are Useful
• 6 How To Choose the Best Football Analysis Site
• 7 The Importance of Livestreaming
• 8 ThePuntersPage Final Say
• 9 Football Analysis Sites FAQs
• You can click on the icon and hold this button to grab/move/drop it to any location wherever you want.
• Clicking on the text will open the table of content.

Football Betting Stats & Analysis Sites: Top 10

ThePuntersPage Stats Hub

KickForm.com

Sofascore.com

SoccerSTATS

WhoScored.com

Flashscore.com

Soccerbase.com

Opta Analyst

The Importance of Stats Analysis in Football Betting

Football, even with the magic of upsets and giant killings, can be somewhat predictable. By analysing statistics and data, you can uncover hidden patterns that can be perfect for betting. Before getting into the nitty-gritty, let's take a look at why stats and analysis are so important.

Following the mythical hunch will likely lead to failure. Sure, lucky wagers do happen and are common enough; however, in the long run, you won’t get far without hard facts. The best football tipsters always prioritise research and gain an in-depth knowledge of sports events.

All the information is at your fingertips. You have everything you could need, so it’s not a hard addition to your betting arsenal. Finding valuable stats is a breeze thanks to our curated list on this very page!

As football has evolved, so has the way the game has been presented to us, as fans and bettors . Match stats have become an integral part of the match-day experience, with technology making them available on our phone screens. They're also readily discussed in pre-match shows and during matches too.

Good news! Our Football Stats Centre is your go-to source for the latest stats and valuable tips on popular football betting markets .

Top 10 Football Stats Sites for Odds, Rankings, Tips, & Predictions

Below, we take a closer look at the top football sites online for stats, betting odds , and other valuable information.

1. ThePuntersPage Stats Hub

You guessed it! Our very own football stats hub is fully focused on giving you the stats that matter the most to betting. Firstly, we offer in-depth statistics in 36 leagues , cups and tournaments, so you won’t miss any of the action.

You can view player stats , team stats, betting stats or tournament stats, all of which can give you the edge when betting. With over 22 metrics and dozens of sub metrics on offer for every competition, you’re guaranteed to come across some valuable information whichever table you choose.

If you prefer betting on a specific market, you can do so. For example, you can view our corner stats to see which teams from across the world had the most corners awarded or conceded, and how they faired both home and away. The percentages shown represent how likely a specific metric is to occur.

Our statistics are incredibly versatile and could turn your bets from duds into studs. All you need to do is find the hidden value. Don’t have time to scour through thousands of stats? Who does? That’s why we’ve created a state-of-the-art algorithm to find the best bets possible for every match. You can access it too on our TPP hot tips page .

Let’s use a couple of examples to really bring home our point as to why we think we do it best:

Say you want to bet on corners: without our stats, you could just bet on the Premier League, purely based on your knowledge and week-to-week monitoring. But with our set of statistics, you might find out that the Newcastle Jets and Perth Glory, in the Australian League, have the best corner stats, with 96% of their matches having over 7.5 corners. That’s excellent value, and it is easy to find on our stats page.

You’re looking for the deadliest striker in Europe to place a ‘golden boot’ bet, or a ‘player to score’ bet. From our set of statistics, you can observe total shots and find out which players had the most shots on target, goals, and their conversion rate. It’s the full picture and can give you an edge.

There are hundreds of ways to use these metrics, and with so many leagues and competitions, you’ll never run out of bet-worthy data.

• 36 Leagues and competitions available
• Up-to-date stats
• Dozens of metrics
• Detailed fixtures list and results page
• Hot Tips showing you the best betting options
• Stats on referees from major leagues.
• No live updates or live scores
• No data on transfers

Author Opinion

This is genuinely one of my favourite products to use when I’m looking up stats. It’s easy to navigate and has all the current information I could ever need. While there are no live updates, the real value of this tool lies in how easy it is to use the statistics for betting purposes.

2. KickForm.com

Our KickForm page is a free-to-use platform providing exclusive, scientifically-backed predictions, odds, and statistics on the biggest football competitions. The data is updated daily and fuels predictions on future match outcomes, probable scores, and much more.

Stats like these can prove vital for popular betting options, such as   over/under or  both teams to score (BTTS) markets. Just try viewing any league’s match week and observe all the predicted scores and possible outcomes to understand the usefulness of the site.

In addition to this, you can check important match stats like head-to-head information, current form, most recent line-ups, and much more.

KickForm provides stats from the following leagues:

England: Premier League

Germany: 1. Bundesliga tips , 2. Bundesliga, 3. Liga

Italy: Serie A

Spain: La Liga prediction

France: Ligue 1

KickForm's highly accurate predictions are powered by the renowned KickForm Football Formula™ , ensuring reliable match forecasts.

• Excellent prediction on 10 different leagues
• Perfect for specific betting markets
• In-depth stats also offered
• Don’t have predictions for lesser leagues.

Kickform is my go-to source for predictions, and I mostly use it to create accumulators on teams to win, or on bets like both teams to score. It’s best suited for markets related to goals but can also be used to gather stats and data.

3. SofaScore

SofaScore is the leading site when it comes to live score features. With a mind-blowing 11,000+ tournaments and 600+ leagues across 20 sports , it's clear to see why. It's also available in 30 languages !

Their live score feature offers in-depth data and real-time match statistics, including player and team stats, play-by-play heatmaps, and customisable live notifications.

Looking for historical data? SofaScore has you covered, providing comprehensive insights into all leagues and players. One of the key highlights of the platform, the ‘Player Statistics Table’ offers a wealth of information, allowing you to compare players across elite tournaments with 83 different metrics side by side.

Moreover, SofaScore has partnered with bet365 , featuring odds for most tournaments and events, ranging from the English Premier League to the Nigerian Professional League .

Recently, SofaScore has added a community aspect to their site, where users can share their predictions, and are even ranked based on how often they are correct. While it’s not perfect, this too can be used for betting by assessing opinions from other punters.

• Great live-score feature
• Excellent database of leagues and players
• Large amount of historical data
• Comparisons for matches and players
• Live transfer updates
• Live commentary based on stats
• No predictions available

Author’s Opinion

I enjoy SofaScore as much as the next guy. For live updates, it’s unmatched, and it’s useful when looking up some historical data. When it comes to in-match information, it’s my number one choice.

Don’t be fooled by its slightly simplistic appearance — FBref is one of the best football statistics sites around. They specialise in amazingly in-depth historical data, often reaching back to a competition's origins, like England's 1888/89 season. This trend carries on with their player stats, covering current and historical football data spanning entire careers.

Jumping back into the present, FBref features scores, fixture, and league stats for football betting on the current season, on a wide variety of leagues and competitions. They offer over 100 data points powered by Opta for the top leagues, including advanced metrics such as xG (expected goals) or xGA (expected goals against).

Finally, if you want even more stats and the ability to compare and create tables, you can subscribe to Stathead — FBref’s paid subscription service.

• Amazing for historical data
• Stathead allows you to compare and create stats tables
• Over 100 data points across many leagues
• Stathead is a paid subscription
• No live updates

As a certified stats geek, I love looking back to historical data, so FBref is definitely on my radar. Historical stats can be useful, especially for competitions like the World Cup. Their modern stats, such as xG or xGA, can also rival some of the best sites out there.

5. SoccerSTATS

SoccerSTATS  easily ranks among the finest football stat websites, with an exceptionally user-friendly football database. It boasts a plethora of information on every aspect of a match, from home-and-away form to stadium attendance.

The depth of statistics SoccerSTATS covers is quite remarkable, including even the most niche of markets . However, its standout feature lies in the extensive array of leagues and league statistics it offers, all presented in a user-friendly format, ideal for planning accumulator bets .

For instance, you can easily select the “Goals Per Match” option, where each team will be listed alphabetically, displaying their average goals per match. You can then use this information to decide which teams you should add to your accas and which teams you should avoid.

Another feature worth mentioning is the ability to view the average minute a team scores their first goal, as well as viewing a total goals breakdown for each 15-minute period within a 90-minute game. This can be particularly useful for those that like to bet   in-play .

• Brilliant range of stats
• Live stats and commentary on select matches
• Easy to navigate

With large databases across several leagues, SoccerSTATS is another great site for statistics. I like their season-wide stats and sleek use of bars and percentages, which provides some good detail in an easy-to-understand manner. Their live commentary is also worth a look.

6. WhoScored

WhoScored is one of the most complete databases online, making it an incredible resource when it comes to football betting. It covers daily fixtures, live scores, news, stats, plus detailed previews of games from all the major leagues and cup competitions across Europe.

The home page displays an extremely digestible breakdown of the most important player and team stats across the Premier League , La Liga , Bundesliga , Serie A, Ligue 1, and provides player ratings based on the WhoScored system . This system is a ratings service based on their own unique statistical algorithm, considering 200 raw statistics, which are calculated live in play and in real time. Every important moment is factored in and can influence the ratings positively or negatively.

The preview section of the website is a fantastic tool when looking into team selection before a game. A quick search will bring up statistical previews of games from the top five leagues, from where you can view probable starting elevens and team news.

There is nothing more frustrating than placing a goalscorer bet, only to find out your chosen player is out injured. WhoScored.com eliminates this problem, making it a great stop before you begin to draw up your bets.

• Up-to-date news articles
• Excellent player stats
• In-depth pre-match team news
• Great injury updates
• Some stats are only offered on the top five leagues

WhoScored is a great source, and there’s a lot of unique value here. I use it for its excellent database of player statistics, its handy pre-match data, including tips on who might be playing, and to read through any news that might be worth punting on.

7. Flashscore.com

Part of a global live scoring network, Flashscore , offers precise live scores for 26 sports and over 5,000 competitions worldwide. This ultra-user-friendly platform provides live commentary, as well as a list of available livestreaming options.

On top of all this, you'll find live scores and results for over 1,000 football tournaments, including the Premier League, La Liga, Serie A , Bundesliga , and UEFA Champions League . But Flashscore doesn’t just provide live scores; it also offers detailed match statistics such as bookings, fouls, and corners.

Moreover, you can stay updated with goal alerts and access a team's complete history, past and future matches, current betting odds, and rankings. What's more, the site's My Games feature allows you to customise your experience with push notifications.

This real-time live scoring service caters not only to football fans and bettors, but also to enthusiasts of 30 other sports, attracting nearly 50 million monthly visitors .

• Huge database of leagues and teams
• Live odds on most matches
• Customisable favourites page
• News and live updates
• Flashscore news on top events
• All stats are opened on new tabs

Flashscore is another all-rounder, with tons of stats, leagues, and sports to view. Their metrics are in-depth and can be found for virtually every match. I personally like their live odds, which show you what’s gaining or falling in value.

8. Soccerbase.com

Soccerbase is a treasure trove of valuable football statistics and information for bettors. Right from the off, the homepage displays all the main matches coming up that day, with all the recent form of each team clearly visible. Should you need it, there are proposed bets and football betting tips.

What sets this site apart is the depth of information available to tipsters. For comprehensive analysis of major games, the matches page provides up-to-the-minute league tables and a complete fixture list.

Delving deeper into the platform, you can explore player careers, manager career stats, referee history, and even data on individuals that have left the game behind. The historical data section includes head-to-head records between two clubs, with a dedicated page for historical and hypothetical comparisons between any two footballing sides worldwide.

Soccerbase allows users to tailor their information search, making it an excellent choice for those who appreciate that extra personal touch.

• Great historical data
• Excellent head-to-head section for teams
• Lots of betting tips for big matches
• No transfer information

Soccerbase has a uniquely, betting-focused approach to sports stats, which makes it quite useful for me. I also love the head-to-head section, offering a lot of valuable insight.

9. Footystats

Footystats is an excellent bet statistics football site, boasting an advanced football analysis algorithm that emphasises team form and excels in pre-match markets. Stats here are meticulously detailed and regularly updated across various leagues.

The dozens of markets available will directly aid in your betting research, and are in turn enhanced by the predictions page, featuring over 100 tips.

Live football statistics more your thing? Well, Footystats has got that in their locker too, with a product rivalling the rest on this list. The only slight drawback is that their historical data only starts from 2007/08.

Unfortunately, Footystats have placed several stats, predictions, and metrics behind a paywall, so unless you pay up, you won't be able to access everything. Having said that, the subscription is well worth the price!

Discover the freshest and most valuable odds from the leading UK football betting sites , listed right here at ThePuntersPage!

• Amazing betting stats markets
• Great stats, tips and predictions
• Solid historical data after 2007/08
• Many aspects of the site are behind a paywall

Footystats is one of the best sites for betting statistics, having a massive range of live data. My only problem with it is that it’s behind a pay wall. Some of the metrics can, nonetheless, be found for free elsewhere.

10.Opta Analyst

Offering a whole host of in-depth stats on the top leagues, teams, and players, it's no wonder why Opta Analyst is among the leading sources for stats and predictions. Their metrics mostly focus on the top European five leagues, UEFA Champions League, the EFL Championship, and the Women’s Super League.

They provide some thrilling pre-game statistics for each match, a hub for live updates, and even a predictor for match outcomes. When it comes to league stats, they’ve got you covered too. Opta Analyst features several tables and graphs to provide valuable insights, although comparing these all together might be tricky, as you’ll have to do it manually. Most of their statistical analysis come in the form of interesting articles.

For every match, they offer predictions in the form of percentages, which makes it clear to evaluate and very useful to compile relatively achievable accumulators. The same is true of their tournament predictions — percentages are superbly useful for betting.

Their player stats are a sight to behold, with options to view not only a player’s goals and assists , but also their xG value (expected goals) and xA value (expected assists). This is perfect for betting on player markets.

Opta Analyst are also well known for their League simulations, which access the probability of every team’s possible league outcome, making them great for outright betting . Moreover, they are credited with the Opta Power Ranking that rates over 13,000 teams and ranks them based on their performance.

• Amazing predictions and stats on league, teams and players
• Famous Opta Power Ranking
• Brilliant league simulations
• Only offer data on 11 leagues

Opta Analyst is a solid choice if your focus is the top leagues. I especially enjoy their use of percentages to display probability and their league simulations, offering some valuable insights.

Top Football Analysis Sites Compared

The best football statistics sites provide comprehensive data, offering a complete picture for punters. While each platform has unique characteristics, they all provide up-to-date tables, team details, scores, and essential statistics.

Here's a quick comparison:

Why These Football Analysis Sites Are Useful

While different, each of the football analysis sites listed above will offer you what you need when conducting research of your own. Making use of them could be your ticket to spotting something that your gut wouldn’t have.

Whether you're interested in tracking when teams typically lose their lead or when others initiate a comeback, utilising time-based betting, goals scored betting, and player-specific data will not only enhance your betting experience but also increase your chances of success.

Designing the Best Betting Strategies

Having the tools is the first step, but how can you get the most out of them for your betting gain? There are plenty of ways, and it really comes down to your creativity and personal objectives. Here are a few betting strategies while using several stats pages.

Find the Best Markets

It’s the easiest way to start. Sites like ThePuntersPage, Flashscore, Footystats, and Opta Analyst offer odds and probabilities on actual betting markets. You can compare these to see which markets are most often suggested. For example, if every site agrees that Liverpool vs Arsenal will end with over 2.5 goals, it may be worth a punt.

General stats

If you prefer coming up with your own conclusions, statistical pages with huge depth and history are your best choice. You can find metrics that are only offered on particular sites and compare them to create a clearer image, and possibly a better bet. This could include, shot stats, XGA, or home- and-away records.

Betting on Form

Several sites offer great form data, and it can be especially useful when betting on specific tournaments or players. Sources like SofaScore, Soccerbase and SoccerSTATS have great options for this.

Comparing Predictions

While there can never be a 100% guarantee of the future, if multiple sources are predicting the same or a similar outcome, it’s likely to be more accurate. Sites such as KickForm and Opta Analyst are perfect for this betting strategy.

Finding your Niche

Finding a particular metric or data point, which may not be as well-known, could give you a better chance against the bookies. Each site has its own niche and can be exploited by you. Using them together could yield even greater results.

Forecasting Upcoming Scores & Events

Betting strategies can go a long way, but these are only as good as the statistics supporting them. Forecasting is all about finding and interpreting specific metrics that could hold a hidden pattern which has betting value.

If you nail interpreting stats, you could be looking at some serious boosts in betting. Firstly, comparison sites like ThePuntersPage stats centre already have some pre-made groupings, while FBref allows you to create your own. These will guide the way, and you can also compare all these web sources to see how accurate each one is.

Here are a few examples of using statistics to come up with conclusions.

Let’s say you’re looking for a goalscorer in the Manchester United vs Tottenham match — you can look up goals, xG, and shots on target to predict whether a player could score. But you can also check out which players are providing assists, creating chances, and putting in crosses. If these individuals aren’t playing, there might be fewer goals.

Trying to bet on fouls? Foul stats could be complemented with yellow cards, tackles, possessions won and lost, or heat maps for defensive players.

Match predictions are also great for this: if KickForm predicts that Chelsea vs Man City will end 2-2, you can use that information to place bets like over 2.5 goals, both teams to score, or no clean sheets. Even a goalscorer bet could be a good idea.

With so many stats pages, you might be thinking that picking your favourite one is enough, but there’s no such thing as that. Using several of these sources together is the best way to go, and here’s why.

Comparisons — Some bookies offer statistics that might be slightly different, such as fouls vs tackles, which could be used together to make smarter bets.

Better predictions — Prediction stats are tricky, but if you find one which is expressed by several sites, it’s probably more likely than others.

Hidden Gems — When looking up statistics, you always stand a chance of finding that amazing anomaly which is perfect for bets. Using several sources means that you’re more likely to find these hidden gems.

Other Perspectives — With such a variety of metrics available, you might gain new perspectives on stats, uncovering insights you might have previously missed.

Find patterns – Patterns rule the football betting world. With all these gems and perspectives, you get a clearer picture of any patterns forming, hopefully leading to more winning bets.

How To Choose the Best Football Analysis Site

It’s a tough choice, given that every source has something to offer, so it’s really up to your personal preference.

Knowing your objective is crucial. If you’re looking for predictions, some sites aren't for you; if you're looking for historical data, only a handful are worth using. The same goes for the type of metrics — if player stats are more important, some sources stand out more compared to if you want form or up-to-date intel. Often, using several platforms together can give you the best results.

Just in case you aren’t sure of how to go about choosing the right site, here’s a handy little guide:

Site seeing. Understanding each site is the first step. Getting to know the tools and interesting features offered can help with your choice.

Set your objective. Decide what you’re looking for. Are predictions more your style, or do you prefer coming up with your own conclusions? Figuring out what you need is crucial in choosing the right source for you.

Decide what you need. According to your objective, choose which attributes are best from each site. Worth keeping in mind: stats depth, accuracy, recency, and ease of use.

Choose your site/s. After compiling your list of important features and metrics, pick the platform(s) that most closely offer what you need.

The Importance of Livestreaming

As vital as stats and analysis are for crafting smarter bets, there's no substitute for actually watching the matches you'd like to bet on. The nuances of each team's playing ability cannot be fully understood through numbers or text alone; so it's best to witness this for yourself!

Livestreaming should be seen as an important tool which can be used alongside the statistical sites to bridge the game between historical facts and ongoing information, such as match momentum or fitness levels.

ThePuntersPage Final Say

Using the proper stats sites and tools will give yourself the best chance of generating a long-term  profit  and  beat the bookies  at the same time. That is, after all, the bettor’s dream!

Scroll up to our list above for our top recommendations that can help you not just win individual bets, but also increase your chances of success in the long run.

Football Analysis Sites FAQs

There's one site that stands head and shoulders above the rest, and that's none other than KickForm.com !

The best website for live football score stats is SofaScore , as it offers a wide range of leagues and competitions. It also features a handy app, which offers personalised notifications.

The best app for football results is LiveScore. Dive into our detailed reviews of the top live score apps to find out why!

It’s simple — stats get results. While nothing in sports is ever guaranteed, properly using data will give you an added edge and help you place more valuable bets. Don't just take our word for it; explore our football stats centre and witness the difference for yourself!

If there’s one thing Jeremy loves, it’s sports. A football fanatic at heart, Jeremy can always been found watching, playing or talking about sports. It’s in his blood, and with a keen interest in sports betting, sports writing is a match made in heaven.

Further reading

• Best Live Betting Sites in the UK – In-Play Betting Guide 2024 Sometimes referred to as in-play betting, live betting involves real-time wagering on an ongoing sporting event, greatly heightening the overall experience. In this article, we provide a list of what...
• Best Football Betting Sites in UK — 2024 Guide The beloved game of football is watched worldwide and is by far the biggest sport amongst British punters. With this in mind, we've curated a list of the best football...
• Best MLB Betting Sites in the USA 2024 Baseball isn't just a game; it's a cultural phenomenon transcending borders, and the best MLB betting sites can amplify the thrill of every match through unbeatable promotions and competitive odds....

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• How To Research For a Football Bet: 5 Things To Look For

Building a successful strategy for football betting can be a real challenge. Even if you do manage to achieve it, this doesn’t mean you will just place bets and collect your winnings. Constant effort is required and there are certain steps in the preparation for each bet that just can’t be ignored.

How to Study Football Betting

The research before each football match is the key to success, as it’s the only way to get a good evaluation of what’s to be expected.

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Depending on the markets you choose, there might be plenty of details, but the basis remains the same most of the time.

Let’s cover the aspects of how to analyse football matches for betting. They won’t instantly make you a winner, but it’s a huge step in the right direction.

1. Check the Performance of Both Teams Over a Long Period

This is an obvious step and yet, somehow plenty of people underestimate its importance. The long-term performance of both teams involved is the best way to get a good idea of their average performance. There is a reason the legendary Bill Shankly once said: “form is temporary, class is permanent”. Certain bookies like bet365 will under-price a well known team, just because punters assume they’ll win. Sometimes a side like Man Utd may always struggle away to Sunderland, but the bookies don’t reflect this in their odds – they want to suck people in that just jump on the big named teams.

The exact time frame depends on what you are looking for, but the minimum should be around a couple of months or even a year. This will give you a good start and a platform to build on when you go into more details later.

The important questions here are how does the team perform in terms of goals scored, goals conceded, playing home or away (depending on the game), results against teams similar to the next opponent and many more valid points that should be considered.

2. Check the Short-Term Trends

After you have a good understanding of the bigger picture, it’s time to dig deeper and see what is the current shape of both teams. As we know, confidence is key in football and certain players can look like world beaters one day and like Sunday league amateurs the next. That makes short-term trends extremely important.

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Take a look at the last 5-10 games of each team, this should be enough to show you what to expect. Once again, stats such as goals scored, goals conceded, average possession and form of the best players are the things you should be looking for. It’s a good idea to actually read a short match report for each of the games in case you haven’t watched them. You never know if a team was just unlucky with some near misses, wonder goals conceded or referee mistakes.

3. Team News Is Essential

Almost every punter out there knows that you should check the list of suspended, injured and doubtful players. The problem of most people is that they don’t fully evaluate the influence of the absentees. A certain player can be badly missed against certain opposition and easily compensated against another. For example, a team missing its best centre back could struggle against an attacking-minded opponent and do well against a side that prefers to sit back.

WhoScored.com has a great section in their match previews that highlights current injuries and suspensions

Of course, you should also take a look who’s going to replace the missing players. How did their subs perform the last time they played? Are they just bench-warmers or squad players that get enough minutes to be in good shape? Those questions and many more need to be answered.

There is another aspect that is often ignored. The schedule of both teams is essential, as nowadays the number of games played per season demands rotation. This is especially true for the English Premier League due to the lack of a winter break. Check the last couple of games of each team and what’s coming next. It should give you a good idea if the manager will start his strongest line-up or try to rotate a bit.

4. Previous Meetings Between the Two Teams

The next step would be to check how both teams performed against each other in the past. The last couple of games are the most telling, but the historical data shouldn’t be underestimated. Certain fierce rivalries such as the North London Derby between Tottenham and Arsenal, for example, has its own rules and the game often does not depend on form as much.

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There is another important thing you might notice – certain teams or even certain players sometimes have a good streak against a specific opposition. Plenty of examples can be seen in the English Premier League where Sunderland is on a great streak against the local rival Newcastle in the past couple of years. The Magpies are also the favorite opponent for Arsenal’s striker Olivier Giroud who is scoring against them on a regular basis.

5. Listen to the Experts

Nowadays, you can find so many opinions on the Internet that could be pretty overwhelming. Most of them would just confuse you and can’t contribute much to your analysis. Still, there are certain experts that could be useful. Whether is successful punters or well-known journalists, there are people who are good at analyzing and predicting football matches.

We don’t recommend you to directly copy someone else’s opinion, but taking your time to read a preview is not a bad idea. Seeing a different perspective could confirm your own expectations or show you an angle you might have missed.

List of Soccer Analysis Websites

After we went through the most important steps you have to take in your preparation, it’s time to list some useful websites that can help you in this regard. Most of them will provide you the necessary data:

SoccerStats.Com

Oddsportal.com.

One of the best free odds comparison services in the business. You will find the best prices for almost any football match out there. It has all the important markets and then some more. On top of that, there are plenty of stats, betting tools, a reliable live score service and even tipsters who provide picks. It’s pretty much the full package.

The OLBG community is probably the biggest when it comes to betting. The platform has many useful features including free tournaments with real prizes, hundreds of successful tipsters and much more. One of the best things is that it’s not limited to football only, so you could check it for other sports as well.

Make your list of things to look for when betting on football

Consider this article as your starter pack for how to bet on football . It’s not enough, but it’s a pretty solid beginning. We strongly encourage you to build on it by finding your own ways for an even better evaluation of the matches you are willing to bet on. Also, there are so many reliable websites and services out there, that you should spend some time checking what can be useful to you.

Mike has over 14 years of experience with online sports betting, having used countless online betting sites. Mike previously provided football betting tips on goals and corners in Facebook groups before starting his own betting website. A huge football fan, Mike has been writing betting guides and football betting advice for years.

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The Best Football Statistics and Historical Odds Data for Betting Analysis

Now you can see and manipulate the latest football statistics in the most easily accessible interactive charts and graphs on Betaminic.com’s new statistics page .

This fantastic free tool is an interactive chart that shows data from 54 leagues around the world since 2012, updated daily. You can filter the data by season, country, league and even by team.

The charts show:

1X2 Match Odds Statistics

• Full time and half time results as percentages in pie charts.
• Top 10 scores at full time and half time as percentages in a bar chart.
• Change in match odds prices from opening odds to closing odds as an average percentage in a graph.
• HT/FT results as percentages in a bar chart.

Goals Statistics

• Over 2.5 goals at full time data as percentages in a pie chart.
• Over 1.5 goals at half time data as percentages in a pie chart.
• Top 5 total goals figures at full time and half time as percentages in bar charts.
• Change in total goals odds prices from opening odds to closing odds as an average percentage in a graph.
• Average goals at half time and full time per game per season shown as a bar chart.

The visual layout makes it easier than ever before to see the whole picture on one screen and instantly get a good overview of trends. You can then use the filters to refine and research the data to analyse specific areas of interest. Once you notice a trend and get an idea for a betting strategy, you can even test it with actual historical bookmaker odds in the Betamin Builder tool to see if that betting strategy would have led to profit.

Interactive and Highly Customizable: See Trends Easily

By clicking on various parts of the chart, data can be quickly filtered to reveal new trends.

For example, if we click on the blue “1” slice of the 1X2 full time match result pie chart, it will filter down to only the matches that ended with a home win. Here we can see that the majority of home wins ended 1-0 and 2-1, so it can give us the idea to research if it is more profitable to split a stake on a home win bet into 2 correct score bets of 1-0 and 2-1 respectively. (The red arrow points to the area that was clicked on.)

Half Time Statistics: Useful For In-Play Betting

Another example, if we click on the blue half time home win “1” slice of the HT match result pie chart, we see that 33.48% of games were home wins at HT and of those, 78.59% of those teams went on to win their game (fair odds 1.27). This means you would need to have a very strong reason to bet against those teams winnings from that position.

We can go deeper than that if we reset the chart and then click on the HT score 1-0, we can see that 72.75% of teams winning 1-0 at home at half time went on to win that game (fair odds 1.37). More interestingly, only 27% of those 1-0 at HT games finished 1-0 (fair odds 3.70), so there could be profit to be made backing another goal if the odds look good.

Team Statistics: Bet With More Confidence

We can be even more specific, if you are following a game live, then we can filter down to those specific leagues and then teams.  If we are watching West Ham 1-0 up at home to Southampton, what kind of trends can we see?

In the Premier league 80.88% of home teams winning at half time go on to win that game. But in West Ham’s case they only go on to win 77.08% of games they are winning at half time (fair odds 1.3).

In the premier league 73.94% of teams 1-0 up at HT go on to win that game, and West Ham win 73.33% of games they are 1-0 up at HT in (fair odds 1.36).

Head to Head Statistics: Use Data to Make the Right Bets

When playing Southampton at home, they have played 8 times and West Ham won 75% of those (6 of 8 games). In 4 of those 8 games they were winning at half time and West Ham went on to win all of those. West Ham have only been up 1-0 at half time once, and they went on to win that game. So now when we look at the odds of a game at HT, we can have a fair idea if the odds are value or not. If West Ham are winning at half time against Southampton, or a team of similar level, they may be worth a bet.

Half Time Draws: Lay the Draw or Bet on Another Goal

Another example is if we select the HT draw piece in Premier League games, we see that 36% of games went on to draw, but only 27% of those games that were 0-0 at HT finished as 0-0 (fair odds 3.7). So laying the draw or backing one more goal at HT may be profitable if the odds look good.

Dropping Odds: Know When to Bet Early or Late

One of the unique points of Betaminic’s statistic page is the ability to see trends of how the odds changed over time in a clear, visual format. We can look at general trends, country, league and team specific odds changes. We can also look at specific seasons, too. When using data driven betting strategies. We are trying to beat the bookmaker’s models. In general, bookmaker’s often start with lower odds than what is fair and then raise them as the market becomes more mature, with the best odds available closer to kick off.

In the above graph we see that in general for all football leagues, the odds price tends to rise between 1.39%-1.60% from the time that they are first published until kick off. These odds are taken from Pinnacle which is known to have one of the lowest bookmaker margins and have odds that are some of the best value available. This trend seems to continue from 2013 to the present. But it is better to look at leagues individually since bookmaker’s often change their models for each league.

If we look at the Argentinian Primera Nacional, the 2 nd tier league in that country. We can see that draw odds actually tend to decrease since they were published. This would suggest that their opening odds were too high, and often got lowered later on as people bet heavily on them or as Pinnacle adjusted to match the overall market price. Although we can see that this increase has been reducing over time since 2012. Note that the decreasing bars show that the average change is decreasing when the new data is added, it does not indicate the change for that year. In fact, we can filter and see just the most recent season’s data.

By selecting the 2019/20 season we can see there are 332 games in the data set and the dropping odds change has reversed. It seems the model makers have fixed their mistakes on the draw odds and now the odds tend to increase after they are published. However, it seems by fixing their draw odds, they have begun to misprice their home win odds, as the home win odds now show a trend of dropping odds after they are first published. This would suggest not only that it is better to bet early if you want to back a home team in the Argentinian Premier Nacional, but also that this league is a hard one for the bookmakers to make a good model for. So with further investigation in the Betamin Builder Tool , there may be chances for profit here. This shows the importance of not only checking each league, but also looking at the most recent trends in the data to see possible opportunities for a profitable strategy.

Most importantly, though, is that we can use these charts to know when to bet, early or late, opening odds or closing odds, depending on the type of bet and the league. For example, For the German Bundesliga 2, we can see that we should bet early on away wins (average odds decreasing trend) and late for home and draws (average odds increasing trend).

Total Goals Scored Statistics

On the main screen, by clicking on the yellow “Switch to Goal Stats View” yet more soccer data becomes accessible. We can see data about the total goals scored at full time and half time. We can see the most common total goals statistics. We can see the average odds change from opening to closing odds of the over 2.5 goals market. We can see the average goals scored at HT and FT

League Specific Goals Data: Find Trends for Smart Betting

Again we can use the interactive charts to filter down to specific leagues and look for patterns. For example, in the German Bundesliga 2 we see that its over 2.5 goals at FT percentage for this season (53.92%) is higher than the overall football trend for all leagues (48.83%). And then we can also see that the German Bundesliga 2’s under 1.5 goals at HT percentage for this season is 63.40%. This trend suggests that waiting until half time to enter the over 2.5 goals bet in this league might be a profitable strategy. It seems that there are likely to be less than 2 goals having been scored in the first half, but still a higher chance than other leagues of the game finishing with 3 goals or more.

Quick Tips: Go Full-Screen or Download the Data Easily

You can make the chart go full screen by clicking on the box in the bottom right of the tool. This can make it easier to view. You can also save the data currently displayed by clicking on the box with a down arrow that is next to the full screen button. Data can be saved an image, a PDF or even in PowerPoint format.

Power to Your Bets with Betaminic

Betaminic  is a website that has a vast amount of football data from over 50 major leagues around the world since 2012. Betaminic has a range of useful tools at the bettor’s disposal to analyse historical football data and real bookmaker odds.

Betaminic’s Statistics Pages have interactive charts and tables with daily updated football statistics including 1X2 markets, goal markets, odds change data, total goals HT/FT, HT/FT result and so on that can be manipulated in a wide variety of ways to see countries, leagues, teams and seasons in an easily accessible way.

Using this data Betaminic has also produced two other unique big data analysis tools, the  Betamin Builder  and  Betlamp .

The Betamin Builder tool  combines the football data with real bookmaker historical odds data so that it is possible to backtest strategies and find out what betting systems work or not. It allows us to find patterns and trends in the data, to find consistent mistakes in the bookmakers odds calculation models, and to take advantage of those for profit.  It uses the most common betting markets (1X2, OU 2.5 goals, Double Chance and DNB).  You can have future picks from that strategy emailed to you.

The Betlamp tool  has many kinds of football statistics available in it, with a wide variety of markets to choose from: 1X2 (HT & FT), Over/Under 0.5, 1.5, 2.5, 3.5 goals at HT or FT, Asian Handicap, Total Goals HT or FT, Over/Under from 8.5 to 13.5 Corners, Both Teams to Score (HT &F T), Yellow Cards and more. It is an excellent tool to detect trends. You can view statistics of all the matches in the season or the last 2, 4 and 8 games played. You can display the results of the games played at home/away or overall.  You can have future fixtures that match your selection criteria emailed to you for free.

Analysing football statistics is made easier and more accessible with Betaminic. Use our tools to find trends and create profitable strategies for football betting.

Sign Up for free to access the Betamin Builder here.

Read more about Betaminic’s soccer statistics pages here.

Access Betlamp, the amazing free statistics tool here.

See the best betting systems ranked by profit, ROI and risk here.

Read more Betaminic posts here.

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Understanding Football Odds: A Beginner’s Guide to Successful Betting

Football betting is a popular pastime that adds excitement to the sport. However, for beginners, understanding betting odds can be a daunting task. This guide aims to demystify football betting odds, covering the different types—fractional, decimal, and moneyline—and providing examples to help you read and use them effectively.

What Are Betting Odds?

Betting odds represent the probability of an event happening and determine how much you can win if your bet is successful. They are a crucial part of betting, helping you understand the potential return on your investment.

Types of Betting Odds

There are three main types of betting odds: fractional, decimal, and moneyline. Each format is used in different regions and has its own way of representing the probability and potential payouts.

Fractional Odds

Fractional odds, commonly used in the UK and Ireland, are expressed as a fraction (e.g., 5/1 or 7/2). The number on the left (numerator) represents the potential profit, while the number on the right (denominator) represents the stake.

Odds of 5/1 mean you can win $5 for every $1 you bet.

If you bet $10 at 5/1 odds and win, your total payout would be $60 ($50 profit + $10 stake).

Decimal Odds

Decimal odds are popular in Europe, Australia, and Canada. They are expressed as a decimal number (e.g., 2.50 or 3.00), which represents the total payout, including the original stake.

Odds of 2.50 mean you will receive $2.50 for every $1 you bet.

If you bet $10 at 2.50 odds and win, your total payout would be $25 ($15 profit + $10 stake).

Moneyline Odds

Moneyline odds, also known as American odds, are used primarily in the United States. They can be positive (+) or negative (-).

Positive moneyline odds indicate how much profit you will make on a $100 bet.

Negative moneyline odds indicate how much you need to bet to make a $100 profit.

Odds of +300 mean you will win $300 for every $100 you bet.

Odds of -150 mean you need to bet $150 to win $100.

How to Read Betting Odds

Converting Odds to Implied Probability

Understanding the implied probability behind betting odds can help you gauge the likelihood of an event happening. Here’s how to convert each type of odds into implied probability:

Fractional Odds: Implied Probability=DenominatorNumerator+Denominator×100Implied Probability=Numerator+DenominatorDenominator ​ ×100

For odds of 5/1, the implied probability is 15+1×100=16.67%5+11 ​ ×100=16.67%.

Decimal Odds: Implied Probability=1Decimal Odds×100Implied Probability=Decimal Odds1 ​ ×100

For odds of 2.50, the implied probability is 12.50×100=40%2.501 ​ ×100=40%.

Moneyline Odds:

For positive odds: Implied Probability=100Positive Odds+100×100Implied Probability=Positive Odds+100100 ​ ×100

For negative odds: Implied Probability=Negative OddsNegative Odds+100×100Implied Probability=Negative Odds+100Negative Odds ​ ×100

For odds of +300, the implied probability is 100300+100×100=25%300+100100 ​ ×100=25%.

For odds of -150, the implied probability is 150150+100×100=60%150+100150 ​ ×100=60%.

Practical Examples of Betting on Football

To bet on football successfully, it’s important to understand how to apply these odds in real-world scenarios. Let’s look at a few examples.

Example 1: Premier League Match

Imagine a Premier League match between Liverpool and Manchester United . The odds might be presented as follows:

Liverpool to win: 2/1 (fractional), 3.00 (decimal), +200 (moneyline)

Manchester United to win: 3/2 (fractional), 2.50 (decimal), +150 (moneyline)

Draw: 5/2 (fractional), 3.50 (decimal), +250 (moneyline)

If you bet $20 on Liverpool to win at 2/1 odds and they win, your payout would be $60 ($40 profit + $20 stake). Similarly, betting $20 on a draw at 3.50 decimal odds would yield a payout of $70 ($50 profit + $20 stake).

Example 2: Champions League Match

Consider a Champions League match between Barcelona and Bayern Munich with the following odds:

Barcelona to win: 2.20 (decimal), 6/5 (fractional), +120 (moneyline)

Bayern Munich to win: 1.75 (decimal), 3/4 (fractional), -133 (moneyline)

Draw: 3.30 (decimal), 23/10 (fractional), +230 (moneyline)

If you bet $50 on Bayern Munich at 1.75 odds and they win, your total payout would be $87.50 ($37.50 profit + $50 stake). Betting $50 on a draw at +230 moneyline odds would result in a payout of $165 ($115 profit + $50 stake).

In both examples, the potential return varies based on the type of odds and the amount wagered. Understanding these differences helps you make more informed decisions when you bet on football.

Tips for Beginners

Start Small and Learn

As a beginner, start with small bets to get a feel for how betting works. This approach minimizes your risk while you learn.

Research Teams and Players

Knowledge is power. Researching teams, players, and their current form can provide valuable insights and improve your betting decisions.

Compare Odds

Different bookmakers offer varying odds for the same event. Compare odds across multiple platforms to find the best value for your bets.

Use Betting Tools

Many online betting sites offer tools and calculators to help you understand potential payouts and implied probabilities. Utilize these resources to make informed bets.

Manage Your Bankroll

Set a budget for your betting activities and stick to it. Avoid chasing losses and bet only what you can afford to lose.

Understanding football betting odds is fundamental to becoming a successful bettor. By grasping the different types of odds—fractional, decimal, and moneyline—and knowing how to read and apply them, you can make more informed decisions and improve your chances of winning. Remember to start small, do your research, and always bet responsibly. With these tips, you’ll be well on your way to navigating the exciting world of football betting.

Story originally appeared on Mountain West Wire

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Football Betting Stats

Stats and insight for your predictions.

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Identify teams based on their performance in key performance metrics like goals over 0.5, 1.5, 2.5, both teams scoring, and more. This approach is highly effective in discerning valuable opportunities. All information is derived from currently active leagues, with a minimum of six matches played by a team for inclusion in our data.

Many individuals are experiencing setbacks due to poor strategic decisions and a lack of data. Essentially, people are making decisions blind. The information we offer on this page is designed to enhance your strategic approach. We handle the in-depth analysis, providing you with straightforward information that boosts your confidence in decision-making. The data showcased here is just an introduction to what FootyStats offers. Our platform features over 1,500 leagues, rich with detailed statistics on goals, corners, cards, players, and much more.

• Top BTTS Leagues
• Esoccer Battle 78%
• Season Progress 97%
• AVG Goals Per Game 3.77
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• FFA Cup 78%
• Season Progress 69%
• AVG Goals Per Game 4.22
• 2.5+ Goals Percentage 83%
• Reserve League 77%
• Season Progress 99%
• AVG Goals Per Game 3.58
• 2.5+ Goals Percentage 75%
• Queensland Premier League 2 77%
• Season Progress 95%
• AVG Goals Per Game 4.72
• 2.5+ Goals Percentage 88%
• U19 League C 76%
• Season Progress 70%
• AVG Goals Per Game 5.45
• 2.5+ Goals Percentage 89%
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• Tampines Rovers 83%
• At Home 80%
• Away from Home 86%
• AVG 2H Goals 2.58
• Rosengard Women 80%
• At Home 100%
• Away from Home 63%
• AVG 2H Goals 2.00
• Darwin Olympic 78%
• At Home 78%
• Away from Home 78%
• AVG 2H Goals 2.17
• Holland Park Hawks 76%
• At Home 82%
• Away from Home 70%
• AVG 2H Goals 2.19
• Rigas FS II 75%
• Away from Home 71%
• AVG 2H Goals 1.75
• Most Offsides by Team
• Deportes Santa Cruz 6.07 /Match
• Matches Played 22
• AVG Match Offsides 6.07
• AVG Team Offsides 2.07
• Tristan Suarez 5.86 /Match
• Matches Played 28
• AVG Match Offsides 5.86
• AVG Team Offsides 3.00
• Magallanes 5.75 /Match
• AVG Match Offsides 5.75
• AVG Team Offsides 1.92
• Fylkir 5.74 /Match
• Matches Played 19
• AVG Match Offsides 5.74
• AVG Team Offsides 1.53
• Defensores Unidos 5.60 /Match
• AVG Match Offsides 5.60
• AVG Team Offsides 2.10
• Highest Corners on AVG
• KR 13.66 /Match
• Matches Played 18
• Highest in Single Match 11
• Over 9.5 Corners 100%
• Over 10.5 Corners 83%
• Over 11.5 Corners 78%
• Hacken 13.11 /Match
• Highest in Single Match 14
• Over 9.5 Corners 83%
• Over 10.5 Corners 67%
• Over 11.5 Corners 61%
• HK 12.72 /Match
• Highest in Single Match 8
• Over 10.5 Corners 72%
• Malmo FF 12.32 /Match
• Highest in Single Match 18
• Over 9.5 Corners 63%
• Over 10.5 Corners 63%
• Over 11.5 Corners 53%
• Orlando City II 12.14 /Match
• Matches Played 21
• Highest in Single Match 13
• Over 9.5 Corners 62%
• Over 10.5 Corners 43%
• Over 11.5 Corners 43%
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• Matches Played 17
• Total AVG Goals 5.65
• Under 2.5 Goals Percentage 0%
• Launceston United 100%
• Total AVG Goals 6
• Redcliffe PCYC 95%
• Matches Played 20
• Total AVG Goals 4.7
• Under 2.5 Goals Percentage 5%
• Kingborough Lions 94%
• Total AVG Goals 5.06
• Under 2.5 Goals Percentage 6%
• Atletico Mineiro W 93%
• Matches Played 14
• Total AVG Goals 4
• Under 2.5 Goals Percentage 7%
• Most Clean Sheets
• Hekari United 100%
• Matches Played 7
• Goals Conceded 0
• Away from Home 100%
• Deportivo Colonia 88%
• Matches Played 8
• Goals Conceded 1
• At Home 67%
• CSKA Moskva W 88%
• Matches Played 16
• Goals Conceded 3
• At Home 88%
• Away from Home 88%
• Sturm Hauzenberg 86%
• Olimpia W 83%
• Goals Conceded 4
• Away from Home 89%
• Most Cards by League
• Segunda División 7.55 /Match
• Season Progress 73%
• Over 2.5 Cards 94%
• Over 3.5 Cards 88%
• Over 4.5 Cards 84%
• Primera División Amateur 7.43 /Match
• Over 2.5 Cards 97%
• Over 3.5 Cards 92%
• Over 4.5 Cards 86%
• LFPB 6.63 /Match
• Season Progress 93%
• Over 2.5 Cards 95%
• Over 3.5 Cards 89%
• Over 4.5 Cards 79%
• Primera División 6.38 /Match
• Season Progress 66%
• Over 2.5 Cards 92%
• Over 3.5 Cards 84%
• Over 4.5 Cards 71%
• Copa Paulista 6.22 /Match
• Season Progress 87%
• Over 3.5 Cards 83%
• Over 4.5 Cards 67%
• Teams with First Half Goals
• Glebe North 100%
• Matches Played 1
• Away from Home 0%
• Malahide United 100%
• Lucan United 100%
• Maynooth University Town FC 100%
• Bluebell United 100%

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The Art and Science of Football Betting: A Comprehensive Guide

Understanding Football Betting

Strategies for successful football betting, responsible betting practices.

Football, the beautiful game, is not only a source of entertainment and passion but also a realm of opportunity for those who wish to engage in football betting. Betting on football matches has grown into a global industry, offering excitement, camaraderie, and, for some, a chance to turn their knowledge into profits. This article will take you on a journey through the intricate world of football betting, exploring its different aspects, strategies, and responsible practices.

Football betting, often referred to as sports betting, involves wagering on the outcome of football matches. While the concept may seem straightforward, there is a lot more to it than meets the eye. Here are some essential elements to understand. If you're looking for a reliable platform to kickstart your football betting journey, consider exploring onlinekladionice.com , where you'll find a wide range of betting markets and valuable insights to enhance your betting experience. This platform offers a seamless interface, competitive odds, and a community of passionate bettors who share tips and strategies, making it an excellent choice for both novice and experienced punters.

Betting Markets : Football betting offers a diverse range of markets, including match result (1X2), over/under goals, Asian handicaps, and countless others. Each market provides a different way to bet on the game.

Odds : Odds represent the bookmakers' assessment of a team's likelihood of winning or a particular event occurring. Understanding how odds work is crucial for making informed bets.

Bookmakers : Bookmakers are companies that provide platforms for individuals to place bets. Popular bookmakers include Bet365, William Hill, and Betfair.

Successful football betting requires a combination of knowledge, research, and discipline. Here are some strategies to help you make more informed decisions:

Research : In-depth research is the backbone of successful football betting. Analyze team statistics, form, injury reports, and historical performance to make informed predictions.

Bankroll Management : Set a budget for your betting activities and stick to it. Responsible bankroll management ensures you don't overspend and helps you avoid chasing losses.

Value Betting : Look for bets where the odds offered by bookmakers are higher than your assessment of the team's real probability of winning. This approach is known as value betting.

Specialize : Focus on specific leagues, teams, or betting markets. Becoming an expert in a niche area can give you an edge over the bookmakers.

Avoid Emotional Betting : Emotional betting can lead to impulsive decisions. Bet with your head, not your heart.

Stay Informed : Keep up with the latest news and developments in the world of football. Injuries, suspensions, and managerial changes can have a significant impact on match outcomes.

Football betting can be a fun and potentially profitable hobby when done responsibly. Here are some practices to keep in mind:

Set Limits : Establish daily, weekly, or monthly betting limits to prevent excessive gambling.

Avoid Chasing Losses : If you experience a losing streak, resist the urge to bet more to recover losses. Accept that losses are a part of betting.

Use Reputable Bookmakers : Choose well-established bookmakers with a strong reputation for fair play and transparent practices.

Self-Exclusion : Most bookmakers offer self-exclusion options for individuals who feel they are losing control. Utilize these features if necessary.

Seek Help : If you believe your gambling is becoming a problem, seek assistance from support organizations or professionals who specialize in gambling addiction.

Football betting can be a thrilling and potentially profitable pastime for those who approach it with knowledge, discipline, and responsibility. Understanding the various betting markets, employing strategies, and adhering to responsible betting practices are crucial for an enjoyable and sustainable experience. For those seeking exciting adventures in the world of football betting, it's important to remember that while it can add an extra layer of excitement to the game, it should be viewed as entertainment, not as a guaranteed way to make money. Always bet responsibly and within your means to ensure your betting adventures remain enjoyable and sustainable.

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Football Betting Systems: Win Big with Expert Strategies

Football Betting Systems

Exploring football betting systems? Learn how strategic betting not only enhances your understanding of the game but can also significantly increase your chances of winning. Discover the art of matched betting, value bets, and smart bankroll management to bet smarter and turn the odds in your favor.

Introduction

Football betting systems are more than just a set of rules for placing bets; they are comprehensive strategies designed to maximize winnings and minimize losses over time. In the unpredictable realm of football, where a single goal can turn the tide, the importance of having a structured approach cannot be overstated. By understanding and employing these systems, bettors can navigate the complexities of odds, probabilities, and betting markets with greater confidence and strategic insight.

Understanding Football Betting Systems

Definition and purpose of betting systems.

A football betting system is a structured approach to gambling on football matches. It involves predefined criteria and methods for selecting bets, managing stakes, and making decisions based on statistical analysis, historical data, and other relevant factors. The primary purpose of these systems is to overcome the inherent advantage held by bookmakers and to make informed betting decisions that have a higher probability of resulting in profit over the long term.

Types of Football Betting Systems

Football betting systems can be categorized into various types, each with its own set of principles and objectives. Some systems focus on minimizing risk, while others aim for high rewards by embracing greater levels of uncertainty. Common types include:

• Statistical-based systems : These rely on extensive data analysis and statistical models to predict match outcomes.
• Progressive betting systems : Involves adjusting the size of bets based on previous results to manage and potentially capitalize on winning or losing streaks.
• Value betting systems : Focus on finding bets that are undervalued by the market, offering higher potential returns relative to the risk.
• Arbitrage betting systems : Aim to exploit differences in odds offered by various bookmakers for guaranteed profits, regardless of the match outcome.

Popular Football Betting Systems

Matched betting, explanation and how it works.

Matched betting stands out as a low-risk betting strategy , particularly favored for its ability to generate profit from free bets and incentives offered by bookmakers. At its core, matched betting involves placing two bets: one at a bookmaker using a free bet offer and the other at a betting exchange to ‘lay’ against the initial bet. This combination ensures that all possible outcomes are covered, guaranteeing a profit regardless of the match result.

Benefits and Drawbacks

• Low Risk : By covering all outcomes, the risk of losing is minimized.
• Profitable : Utilizes free bets, turning them into real cash.
• Accessible : Suitable for beginners with guidance and the right tools.
• Limited Earnings : Profitability is contingent on the availability of free bets.
• Time-Consuming : Requires time to find and qualify for suitable offers.
• Complexity : Initially, the process can be complex for novices.

Football betting systems, from the mathematical rigor of matched betting to the predictive prowess of statistical models, offer a fascinating blend of discipline, knowledge, and intuition. By carefully selecting and applying these systems, bettors can not only enhance their understanding and enjoyment of the game but also increase their chances of making profitable bets. Whether you’re a seasoned bettor or new to the scene, the strategic insights provided by these systems can be invaluable tools in your betting arsenal.

Value Betting

Understanding value bets.

Value betting is a cornerstone concept in sports betting, encapsulating the strategy of placing bets on outcomes that have been underestimated by bookmakers. A value bet exists when you believe the chances of a particular outcome are higher than what the odds offered by bookmakers suggest. It’s about finding the diamond in the rough – those opportunities where the probability of a win is greater than the odds imply, thus offering you an edge over the bookmaker.

Identifying Value Bets in Football

To identify value bets in football, a bettor must have a keen understanding of the game, including team form, historical performance, and current events such as injuries and player conditions. Combining this knowledge with statistical analysis allows bettors to spot discrepancies in the odds. Tools like betting calculators, odds comparison sites, and statistical databases can aid in this process, enabling bettors to quantify value and make informed decisions. Identifying a value bet requires patience, research, and a solid grasp of football analytics.

The Martingale System

System overview.

The Martingale System is a popular betting strategy that involves doubling your bet after every loss, with the theory being that when you eventually win, you recover all previous losses plus win a profit equal to your original stake. Originating in France in the 18th century, this system is straightforward and can be easily applied to betting on football, particularly in markets with close to even odds, such as betting on the outcome of a match (win or draw).

Risks and Rewards

• Financial Risk : The need to double bets after each loss can quickly escalate the required stake, potentially leading to significant financial strain.
• Betting Limits : Bookmakers and casinos often have betting limits, which can prevent the continuation of the system after several losses.
• Short-Term Solution : The Martingale System is more of a short-term strategy and doesn’t necessarily increase your chances of winning over the long term.
• Simple Recovery : For those with the capital to support it, the system can recover losses with just one win.
• Ease of Use : The strategy is straightforward and doesn’t require intricate knowledge of the sport or betting markets.

Developing Your Own Football Betting System

Analyzing historical data, importance of statistics in betting.

In the realm of football betting, statistics are the bedrock upon which successful betting systems are built. Analyzing historical data allows bettors to discern patterns, understand team performance trends, and make predictions with greater accuracy . Statistical analysis provides a quantitative foundation for betting decisions, transforming what might otherwise be guesswork into an informed strategy.

Tools and Resources for Data Analysis

To effectively analyze historical data, bettors can utilize a variety of tools and resources designed for statistical analysis. These include:

• Sports Databases : Comprehensive databases like Opta Sports or Football-Data offer extensive historical data on teams, players, and match outcomes.
• Betting Calculators : Tools that allow for the calculation of odds, potential profits, and betting risks.
• Software : Advanced software like Microsoft Excel for data organization and statistical programs like SPSS or Python for data analysis and predictive modeling.

Developing your own football betting system requires a commitment to understanding the intricacies of the game, a solid grasp of statistical analysis, and the patience to refine your approach over time. By analyzing historical data, identifying value bets, and understanding the principles behind systems like the Martingale, bettors can create personalized strategies tailored to their betting style and goals.

Managing Your Bankroll

Strategies for effective bankroll management.

Effective bankroll management is critical to sustaining a successful betting career. It involves setting aside a specific amount of money for betting purposes and managing that money wisely. One popular strategy is the “unit” system, where you divide your bankroll into 100 units and bet a single unit per wager. This method helps mitigate the risk of large losses and encourages more disciplined betting practices.

Setting Betting Limits

Setting betting limits is another fundamental aspect of bankroll management. Determine in advance how much of your bankroll you are willing to risk on a daily, weekly, or monthly basis. It’s crucial to adhere to these limits rigorously to avoid the temptation of placing larger, potentially reckless bets in an attempt to recoup losses.

Tips for Successful Football Betting

Research and knowledge.

The foundation of successful football betting lies in thorough research and a deep understanding of the game. This encompasses everything from player stats and team form to weather conditions and head-to-head records. The more information you have at your disposal, the better equipped you are to make informed betting decisions.

Discipline and Patience

Discipline and patience are virtues in the betting world. It’s important to maintain a level head, stick to your strategy, and avoid impulsive decisions. Recognize that not every bet will win and that success in betting comes from long-term profitability rather than short-term gains.

Understanding the Odds

A profound understanding of how odds work is essential for any bettor. Odds not only reflect the probability of a particular outcome but also indicate the potential return on a bet. Learning to read and interpret odds across different bookmakers can reveal value bets and opportunities to maximize returns.

Avoiding Common Pitfalls in Football Betting

Emotional betting.

Emotional betting refers to making betting decisions based on personal biases or emotions rather than logical analysis. To avoid this pitfall, bettors should strive to remain objective and base their bets on solid research and statistical evidence.

Chasing Losses

Chasing losses is a dangerous practice where bettors increase their stakes in an attempt to recoup previous losses. This often leads to even greater losses, creating a vicious cycle that can be hard to break. Adhering to a disciplined betting strategy and accepting losses as part of the game are crucial to avoiding this trap.

Overestimating the Importance of Trends

While trends can provide valuable insights, overreliance on them can be misleading. Not all trends are indicative of future outcomes, and it’s important to consider the broader context and other influencing factors before placing a bet.

Throughout this exploration of football betting systems, we’ve uncovered the importance of structured strategies, effective bankroll management, and the value of research and discipline. Approaching football betting with a systematic and informed perspective can significantly enhance your chances of success. If you’re eager to delve deeper into the world of football betting and refine your strategies, I invite you to join my betting course . Here, we’ll explore advanced techniques, insider tips, and comprehensive strategies to help you elevate your betting game.

What is the best football betting system for beginners? Matched betting is highly recommended for beginners due to its low-risk nature and the use of free bets.

How much capital do I need to start using football betting systems? It varies, but starting with a modest bankroll of 100 to 200 units of your minimum bet size is a prudent approach.

Can football betting systems guarantee a win? No system can guarantee a win every time, but the right strategies can improve your chances of long-term profitability.

How do I adjust my betting system based on ongoing results? Regularly review your bets, assess performance, and adjust your strategies based on outcomes and new insights.

Are there any legal considerations I should be aware of when using football betting systems? Always ensure that you are betting legally, within your jurisdiction, and through licensed and reputable bookmakers.

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How to Analyse Football Matches & Improve Your Betting Skills

Learn how to analyse football matches, seek value betting opportunities, and devise the best football betting strategy.

I can give you the tools you need to learn how to improve your football betting skills. Sounds good?

Lucky for you, that’s exactly what this guide will cover!

Betting Institute’s football betting tutorial intends to teach you how to devise a football betting strategy, seek value betting opportunities and shop around for the best odds. It is essentially a beginners guide, a ‘how to bet on football 101′, although it does include excellent betting advice that can prove to be useful regardless of your experience as a football bettor.

Being skilled in football betting relies mostly on a punter’s money management and value spotting ability. To spot value in football matches, you must have access to information and the ability to evaluate the data you have on hand correctly.

Assessing two opponents’ performance potential can be tricky, so if you want to find out how to improve your football betting skills, make sure you integrate some of these critical aspects in your football betting match analysis before drawing any conclusions.

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Analysing Football Matches

Money management basics, shop around for the best odds, spot value bets.

Here we’ll talk a bit about the core elements that need to be part of any football betting strategy. Betting on football looking for a yield will require a lot of work, from collecting data and information to digesting it in order to discover football value betting tips.

Objective And Motivation

I can’t stress enough how important this is: get this right and the rest will be like baby puzzle bits falling into place. If you can find out what the clubs’ short and long term goals are, you’ve already got a decent platform to build on. We’re talking about fixture commitments.

Busy clubs will sacrifice some matches in favour of others every season, so if you find out this before the bookies do, you’re basically laughing. Leaving that aside, knowing each team’s actual level of motivation to win, draw or lose a match can be crucial. Yes, you’ve heard well: some managers might ask their players not to lose by no more than two goals if they have a first-leg advantage of let’s say 4 goals; they will be happy to surrender to give some players a rest and to make sure nobody becomes exhausted or gets hurt.

Just think about it for a second; it happens all the time in FA Cup games involving English Premier League teams and of course, in other competitions involving famous football clubs, such as the Italian Serie A or even the mighty Champions League .

Remember always to check the upcoming fixtures of each club, not just their recent run of results.

Home & Away Behaviour

The ‘Home Advantage’ should not be taken for granted. Some teams play better away from home, and that can even vary from one competition to another. Also, teams might have completely different approaches depending on where they play. Spotting a solid away team before the bookies become aware of it can fill your pocket with cold hard cash.

Head To Heads

Past meetings can be deceitful when analysing football matches, and that’s because final scores can be deceiving, as much as stats can be. Of course, some teams have historically had problems playing others (or at specific grounds), but things change rapidly in football these days; a simple example would be PSG’s rise : in 2010 they finished 13th in Ligue 1, next season 4th and then they ended up league champions in 2012. And well all know what happened afterwards…  Do you think their head to heads mattered at all?

Form And Morale

The form is definitely an essential factor in football betting analysis, but remember that form is subject to sudden changes when you expect the least. Most punters haven’t got a proper way of determining true form: they just look at a few numbers and conclude in just seconds. And this could be the reason why those who place highly popular football bets often end up losing.

Form stats can be misleading: team who scored the first goal, goals scored, possession, corners awarded, shots on target etc. so you ideally want to watch football matches or at least highlights of those matches. On top of that, investigate advanced stats and information to figure out form, like the number of shots sent by the team and the on-target/off-target ratio, fouls, goals from action/set-pieces, mistakes made by referees – like lucky/unlucky scored/cancelled goals – and so on.

A team can play very badly and still win 2-0, as much as it can play really well and lose 0-2. Another facet that needs looking into would be morale, which is not necessarily connected to the most recent four or five results. A squad with a poor form can have good morale as a result of :

• receiving overdue wage payments
• attending a wedding of one of the players or staff members
• being promised a huge bonus if they win the next match
• the manager being sacked
• an upset of their closest rivals etc.

That is why team news can have a pivotal role in deciding the football tips to wager on. You head to read football day in and day out. Whenever a team with a very poor streak suddenly wins the game investigate why that happened. Same goes for the teams in great form that lose unexpectedly. Ideally, you’ll learn from these experiences and become better at anticipating such scenarios in the future.

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Unavailable Players

Most bettors misjudge injuries and suspensions. In fact, there are many football tips out there based solely on such information: ‘Falcao is missing, AS Monaco will surely lose’.

The truth is that some teams might even benefit from such scenarios, as their substitutes might be a lot more motivated to prove their worth to the team than those that are used to feature in the starting line-up. For example, Borussia Dortmund performed flawlessly in the 17/18 Bundesliga during the first 7 matchdays, winning 6 out of 7 fixtures, despite undergoing a nasty injury crisis – several key players were sidelined from a total of +11 injuries.

When you hear about an injury, don’t just think about the loss, but try to figure out how the replacement will perform. Generally, a squad with a good squad depth can overcome such trouble, so keep that in mind as the odds might be moving wrongly (because of what people bet) and you could benefit from that if you are above the crowd.

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Match Conditions

This is probably one of the most overlooked topics in football betting or sports betting in general. Before backing a favourite, ask yourself this question: “ Could they do it on a cold rainy night in Stoke? ” Leaving the jokes aside, take these elements into account when weighing options and try to investigate how well both teams could cope under such circumstances:

• Weather  – Pay attention to humidity, altitude, pressure, not just temperature and precipitations.
• Pitch Condition  – Will the match be played on grass or artificial turf? Is the pitch muddy, wet, sandy, frozen?
• Stadium & Fans  – Is it a neutral stadium? Match behind closed gates? Does the home side have many hardcode fans – does this have a positive or negative impact?
• Time  – Besides the eventual time zone difference, which is rarely a factor, observe how teams perform under daylight and night conditions.
• Referee  – Scout for possible animosities by checking out the history of the reff concerning the two clubs. Find out if he is more lenient or rigorous on the pitch and then combine this information with either squad’s aggressiveness to draw relevant conclusions.

Consistency

Avoid betting on teams that usually perform very differently from a week to another. The standard variance when value betting is one thing, but if you choose to wager on unpredictable teams you’d better do it regularly to benefit from the unexpected results, otherwise just skip their matches.

Day-to-Day Issues

Head coach or staff changes? Financial problems? Club takeover? Internal rivalries, fights, discipline issues etc. Keep every single aspect under your radar, even if this means monitoring various social media accounts, bloggers, news portals, and so on. Remember, if it were easy, everybody would do it!

Weaknesses & Strengths

Develop a football betting strategy to follow when you analyse each fixture. Take a sheet of paper and split it in half. On the left side, write each club’s weaknesses and write their strengths on the right. You’ll see that everything is a lot easier to weigh when you have to put your thoughts on paper.

After reaching a fair amount of betting samples feel free to evaluate your performance and tweak the model until you’re on top of the game. Remember that the cornerstone of winning football bets is, of course, weighing everything accurately and staying away from fixtures that are too unpredictable from your point of view.

Don’t expect to win bets every time , instead focus on betting where the value is, as you will benefit from it in the long run. Of course, winning your bet is always nice, but take note that pro punters who wager on even odds generally win just about 50% of their bets.

Did you know we’re publishing safe football betting tips daily?

You already know that money management is critical to success in sports betting – almost every betting guide says so – but still you might not be on the right track just yet. Don’t get lost in all the Martingale’s and Fibonacci’s, but rather stick to the flat staking method. This staking strategy falls into the advanced betting category (most pros use it). Yet, it’s very simple to work with: you select a percentage between 0.5% and 5% of your initial bankroll, and you calculate the amount chosen as your stake.

You’ll always use that same stake (with each straight bet you place, so say goodbye to football accumulators) until you deposit or withdraw funds . Of course, you can feel free to recalculate the flat stake at the end of a season or every 12 months if you consider it would be wise doing so.

The flat staking money management routine works pretty well with Asian handicapping and is one of the two most popular methods employed by professional punters , the other being Kelly Criterion . And the good news is that either can be used for betting on football, horse racing, tennis, basketball, cricket and even on the NFL Super Bowl.

Don’t get excited by betting winnings or losses and try to keep your head clear during good and bad streaks. Remember to bet on singles and try to cut the footy accas and other bet types  as I said. Don’t get complacent and never chase losses. Set long-haul targets. Be patient: Good things come to those who wait!

Explore these 5 essential sports betting money management strategies

Every football tipster knows that winning your bets from time to time isn’t going to be enough to secure a profit at the end of the year. Football betting odds are significant for your betting success.

It doesn’t matter if you’re going for a straight bet, a double chance bet, a correct score bet or a handicap bet, if you want to wager on the English Premier League , Champions League, FA Cup or any other football competition, as long as you shop around to find the best offer. As you already know, betting lines are different with every bookmaker, so you must do your utmost to grab the best odds on the bet market.

It may not seem much at first, but if you do the betting calculations on a large sample of bets, you’ll see how many times bigger your bankroll would have been if you were picking the best betting odds offered by online sportsbooks. I recommend this bookie . If you want to learn more about odds, from decimal odds and fractional odds to the reasons why odds change, please give this resource a good read: betting odds explained .

What’s the best welcome bonus in online betting? Find out now!

Don’t just bet on the favourites, but on the odds that are better than they should be. How can you achieve that? Well, there’s only one way: devise a model to evaluate estimated probabilities for football markets and tweak them regularly. Having programming skills can be useful but not anyhow mandatory.

Browse our betting guide , try to pick up some key indicators, and then focus on one of the most popular football bets, such as the Under/Over 2.5 goals or the 1X2 Moneyline. Commence by creating your own football odds and forget about copying other punter’s betting tips.

Learn how to calculate value bets , combine the stats with team news and start placing football bets only where you find value. You won’t become a successful football bettor overnight, but you will certainly have a platform to build on if you take the value betting path.

Wait no more! You can start wagering with the best bookmaker in the UK in less than 2 minutes!

Read more BettingInstitute How To guides:

Nice article… I feel more confident… although I will do more studies…

Thanks a lot

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Open Access

Peer-reviewed

Research Article

A statistical theory of optimal decision-making in sports betting

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Dept of Biomedical Engineering, City College of New York, New York, NY, United States of America

• Jacek P. Dmochowski

• Published: June 28, 2023
• https://doi.org/10.1371/journal.pone.0287601
• Peer Review
• Reader Comments

The recent legalization of sports wagering in many regions of North America has renewed attention on the practice of sports betting. Although considerable effort has been previously devoted to the analysis of sportsbook odds setting and public betting trends, the principles governing optimal wagering have received less focus. Here the key decisions facing the sports bettor are cast in terms of the probability distribution of the outcome variable and the sportsbook’s proposition. Knowledge of the median outcome is shown to be a sufficient condition for optimal prediction in a given match, but additional quantiles are necessary to optimally select the subset of matches to wager on (i.e., those in which one of the outcomes yields a positive expected profit). Upper and lower bounds on wagering accuracy are derived, and the conditions required for statistical estimators to attain the upper bound are provided. To relate the theory to a real-world betting market, an empirical analysis of over 5000 matches from the National Football League is conducted. It is found that the point spreads and totals proposed by sportsbooks capture 86% and 79% of the variability in the median outcome, respectively. The data suggests that, in most cases, a sportsbook bias of only a single point from the true median is sufficient to permit a positive expected profit. Collectively, these findings provide a statistical framework that may be utilized by the betting public to guide decision-making.

Citation: Dmochowski JP (2023) A statistical theory of optimal decision-making in sports betting. PLoS ONE 18(6): e0287601. https://doi.org/10.1371/journal.pone.0287601

Editor: Baogui Xin, Shandong University of Science and Technology, CHINA

Received: December 19, 2022; Accepted: June 8, 2023; Published: June 28, 2023

Copyright: © 2023 Jacek P. Dmochowski. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data is available at https://github.com/dmochow/optimal_betting_theory .

Funding: The author received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The practice of sports betting dates back to the times of Ancient Greece and Rome [ 1 ]. With the much more recent legalization of online sports wagering in many regions of North America, the global betting market is projected to reach 140 billion USD by 2028 [ 2 ]. Perhaps owing to its ubiquity and market size, sports betting has historically received considerable interest from the scientific community [ 3 ].

A topic of obvious relevance to the betting public, and one that has also been the subject of multiple studies, is the efficiency of sports betting markets [ 4 ]. While multiple studies have reported evidence for market inefficiencies [ 5 – 11 ], others have reached the opposite conclusion [ 12 , 13 ]. The discrepancy may signify that certain, but not all, sports markets exhibit inefficiencies. Research into sports betting has also revealed insights into the utility of the “wisdom of the crowd” [ 14 – 16 ], the predictive power of market prices [ 17 – 20 ], quantitative rating systems [ 21 , 22 ], and the important finding that sportsbooks exploit public biases to maximize their profits [ 13 , 23 ].

Indeed, the decisions made by sportsbooks to set the offered odds and payouts have been previously analyzed [ 13 , 23 , 24 ]. On the other hand, arguably less is known about optimality on the side of the bettor . The classic paper by Kelly [ 25 ] provides the theory for optimizing betsize (as a function of the likelihood of winning the bet) and can readily be applied to sports wagering. The Kelly bet sizing procedure and two heuristic bet sizing strategies are evaluated in the work of Hvattum and Arntzen [ 26 ]. The work of Snowberg and Wolfers [ 27 ] provides evidence that the public’s exaggerated betting on improbable events may be explained by a model of misperceived probabilities. Wunderlich and Memmert [ 28 ] analyze the counterintuitive relationship between the accuracy of a forecasting model and its subsequent profitability, showing that the two are not generally monotonic. Despite these prior works, idealized statistical answers to the critical questions facing the bettor, namely what games to wager on, and on what side to bet, have not been proposed. Similarly, the theoretical limits on wagering accuracy, and under what statistical conditions they may be attained in practice, are unclear.

To that end, the goal of this paper is to provide a statistical framework by which the astute sports bettor may guide their decisions. Wagering is cast in probabilistic terms by modeling the relevant outcome (e.g. margin of victory) as a random variable. Together with the proposed sportsbook odds, the distribution of this random variable is employed to derive a set of propositions that convey the answers to the key questions posed above. This theoretical treatment is complemented with empirical results from the National Football League that instantiate the derived propositions and shed light onto how closely sportsbook prices deviate from their theoretical optima (i.e., those that do not permit positive returns to the bettor).

Importantly, it is not an objective of this paper to propose or analyze the utility of any specific predictors (“features”) or models. Nevertheless, the paper concludes with an attempt to distill the presented theorems into a set of general guidelines to aid the decision making of the bettor.

Problem formulation: “Point spread” betting

For positive s (home team favored), the home team is said to “cover the spread” if m > s , whereas the visiting team has “beat the spread” otherwise. Conversely, for negative s (visiting team favored), the visiting team covers the spread if m < s , and the home team has beat the spread otherwise. The home (visiting) team is said to win “against the spread” if m − s is positive (negative).

Denote the profit (on a unit bet) when correctly wagering on the home and visiting teams by ϕ h and ϕ v , respectively. Assuming a bet size of b placed on the home team, the conventional payout structure is to award the bettor with b (1 + ϕ h ) when m > s . The entire wager is lost otherwise. The total profit π is thus bϕ h when correctly wagering on the home team (− b otherwise). When placing a bet of b on the visiting team, the bettor receives b (1 + ϕ v ) if m < s and 0 otherwise. Typical values of ϕ h and ϕ v are 100/110 ≈ 0.91, corresponding to a commission of 4.5% charged by the sportsbook.

In practice, the event m = s (termed a “push”) may have a non-zero probability and results in all bets being returned. In keeping with the modeling of m by a continuous random variable, here it is assumed that P ( m = s ) = 0. This significantly simplifies the development below. Note also that for fractional spreads (e.g. s = 3.5), the probability of a push is indeed zero.

Wagering to maximize expected profit.

Consider first the question of which team to wager on to maximize the expected profit. As the profit scales linearly with b , a unit bet size is assumed without loss of generality.

Corollary 1 . Assuming equal payouts for home and visiting teams ( ϕ h = ϕ v ), maximization of expected profit is achieved by wagering on the home team if and only if the spread is less than the median margin of victory .

A subtle but important point is that knowledge of which side to bet on for each match is insufficient for maximizing overall profit. The reason is that even if wagering on the side with higher expected profit, it is possible (and in fact quite common, see empirical results below) that the “optimal” wager carries a negative expectation. Thus, an understanding of when wagering should be avoided altogether is required. This is the subject of the theorem below.

It is instructive to consider the conditions above for typical values of ϕ h and ϕ v . When wagering on the home team with ϕ h = 0.91, positive expectation requires the spread to be no larger than the 0.476 quantile of m . When wagering on the visiting team, the spread must exceed the 0.524 quantile. This means that, if the spread is contained within the 0.476-0.524 quantiles of the margin of victory, wagering should be avoided . Practically, it is thus important to obtain estimates of this interval and its proximity to the median score in units of points .

The result of Theorem 2 is reminiscent of the “area of no profitable bet” scenario described in [ 28 ]. Whereas the latter result is presented in terms of outcome probabilities estimated by the bettor and the sportsbook, Theorem 2 here delineates the conditions under which the sportsbook’s point spread assures a negative expectation on the bettor’s side.

Optimal estimation of the margin of victory.

Theorem 3 . Define an “error” as a wager that is placed on the team that loses against the spread. The probability of error is bounded according to : min{ F m ( s ), 1 − F m ( s )} ≤ p (error) ≤ max{ F m ( s ), 1 − F m ( s )}.

The result of Theorem ( 8 ) provides both the best- and worst-case scenario of a given wager. When F m ( s ) is close to 1/2, both the minimum and maximum error rates are near 50%, and wagering is reduced to an event akin to a coin flip. On the other hand, when the true median is far from the spread (i.e., F m ( s ) deviates from 1/2), the minimum and maximum error rates diverge, increasing the highest achievable accuracy of the wager.

Optimality in “moneyline” wagering

Corollary 4 . Define an “error” as a wager that is placed on the team that loses the match outright. The probability of error in moneyline wagering is bounded according to : min{ F m (0), 1 − F m (0)} ≤ p (error) ≤ max{ F m (0), 1 − F m (0)}.

Notice that optimal decision-making in moneyline wagers requires knowledge of quantiles that may be near 0 (if ϕ v ≫ ϕ h ) or near 1 (if ϕ h ≫ ϕ v ). More subtly, the required quantiles will differ for matches that exhibit different payout ratios. For example, a match with two even sides will require knowledge of central quantiles, while a match with a 4:1 favorite will require knowledge of the 80th and 20th percentiles. The implications of this property on quantitative modeling are described in the Discussion .

The moneyline wagering considered in this section is a two-alternative bet that is popular in North American sports. In European betting markets, the most common type of wager is the three-alternative “Home-Draw-Away” bet where there is no point spread and the task of the bettor is to forecast one of the three potential outcomes: m > 0, m = 0, or m < 0, each of which are endowed with a payout (see, for example, [ 26 , 29 , 30 ]). Clearly the the probability p ( m = 0) will be non-zero in this context. As a result, the methodology here, which models m by a continuous random variable, cannot be straightforwardly applied to the case of the Home-Draw-Away bet. The extension of the present findings to the case of multi-way bets with discrete m is a potential topic of future research.

Optimality in “over-under” betting

The following two results may be proven by replacing m with τ , ϕ h with ϕ o , and ϕ v with ϕ u in the Proofs of Theorems 1 and 2, respectively.

In the special case of ϕ o = ϕ u , one should bet on the over only if and only if the sportsbook total τ falls below the median of t .

Define F t ( τ ) as the CDF of the true point total evaluated at the sportsbook’s proposed total. The following corollary may be proven by following the Proof of Theorem 3.

Corollary 8 . Define an “error” in over-under betting as a wager that is placed on the “over” when t < τ or on the “under” when t > τ. The probability of error is bounded according to : min{ F t ( τ ), 1 − F t ( τ )} ≤ p (error) ≤ max{ F t ( τ ), 1 − F t ( τ )}.

Empirical results from the National Football League

In order to connect the theory to a real-world betting market, empirical analyses utilizing historical data from the National Football League (NFL) were conducted. The margins of victory, point totals, sportsbook point spreads, and sportsbook point totals were obtained for all regular season matches occurring between the 2002 and 2022 seasons ( n = 5412). The mean margin of victory was 2.19 ± 14.68, while the mean point spread was 2.21 ± 5.97. The mean point total was 44.43 ± 14.13, while the mean sportsbook total was 43.80 ± 4.80. The standard deviation of the margin of victory is nearly 7x the mean, indicating a high level of dispersion in the margin of victory, perhaps due to the presence of outliers. Note that the standard deviation of a random variable provides an upper bound on the distance between its mean and median [ 31 ], which is relevant to the problem at hand.

To estimate the distribution of the margin of victory for individual matches, the point spread s was employed as a surrogate for θ . The underlying assumption is that matches with an identical point spread exhibit margins of victory drawn from the same distribution. Observations were stratified into 21 groups ranging from s o = −7 to s o = 10. This procedure was repeated for the analysis of point totals, where observations were stratified into 24 groups ranging from t o = 37 to t o = 49.

How accurately do sportsbooks capture the median outcome?

It is important to gain insight into how accurately the point spreads proposed by sportsbooks capture the median margin of victory. For each stratified sample of matches, the median margin of victory was computed and compared to the sample’s point spread. The distribution of margin of victory for matches with a point spread s o = 6 is shown in Fig 1a , where the sample median of 4.34 (95% confidence interval [2.41,6.33]; median computed with kernel density estimation to overcome the discreteness of the margin of victory; confidence interval computed with the bootstrap) is lower than the sportsbook point spread. However, the sportsbook value is contained within the 95% confidence interval.

• PPT PowerPoint slide
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• TIFF original image

( a ) The distribution of margin of victory for National Football League matches with a consensus sportsbook point spread of s = 6. The median outcome of 4.26 (dashed orange line, computed with kernel density estimation) fell below the sportsbook point spread (dashed blue line). However, the 95% confidence interval of the sample median (2.27-6.38) contained the sportsbook proposition of 6. ( b ) Same as (a), but now showing the distribution of point total for all matches with a sportsbook point total of 46. Although the sportsbook total exceeded the median outcome by approximately 1.5 points, the confidence interval of the sample median (42.25-46.81) contained the sportsbook’s proposition. ( c ) Combining all stratified samples, the sportsbook’s point spread explained 86% of the variability in the median margin of victory. The confidence intervals of the regression line’s slope and intercept included their respective null hypothesis values of 1 and 0, respectively. ( d ) The sportsbook point total explained 79% of the variability in the median total. Although the data hints at an overestimation of high totals and underestimation of low totals, the confidence intervals of the slope and intercept contained the null hypothesis values.

https://doi.org/10.1371/journal.pone.0287601.g001

Aggregating across stratified samples, the sportsbook point spread explained 86% of the variability in the true median margin of victory ( r 2 = 0.86, n = 21; Fig 1c ). Both the slope (0.93, 95% confidence interval [0.81,1.04]) and intercept (-0.41, 95% confidence interval [-1.03,0.16]) of the ordinary least squares (OLS) line of best fit (dashed blue line) indicate a slight overestimation of the margin of victory by the point spread. This is most apparent for positive spreads (i.e., a home favorite). Nevertheless, the confidence intervals of both the slope and intercept did include the null hypothesis values of 1 and 0, respectively. The data for all sportsbook point spreads with at least 100 matches is provided in Table 1 .

Regular season matches from the National Football League occurring between 2002-2022 were stratified according to their sportsbook point spread. Each set of 3 grouped rows corresponds to a subsample of matches with a common sportsbook point spread. The “level” column indicates whether the row pertains to the 95% confidence interval (0.025 and 0.975 quantiles) or the mean value across bootstrap resamples. The dependent variables include the 0.476, 0.5, and 0.524 quantiles, as well as the expected profit of wagering on the side with higher likelihood of winning the bet for hypothetical point spreads that deviate from the median outcome by 1, 2, and 3 points, respectively.

https://doi.org/10.1371/journal.pone.0287601.t001

The distribution of observed point totals for matches with a sportsbook total of τ = 46 is shown in Fig 1b , where the computed median of 44.45 (95% confidence interval [42.25,46.81]) is suggestive of a slight overestimation of the true total. Combining data from all samples, the sportsbook point total explained 79% of the variability in the median point total ( r 2 = 0.79, n = 24; Fig 1d ).

Interestingly, the data hints at the sportsbook’s proposed point total underestimating the true total for relatively low totals (i.e., black line is below the blue for sportsbook totals below 43), while overestimating the total for those matches expected to exhibit high scoring (i.e., black line is above the blue line for sportsbook totals above 43). Note, however, that the confidence intervals of the regression line (slope: [0.72,1.02], intercept: [-1.14, 12.05]) did contain the null hypothesis values. The data for all sportsbook point total with at least 100 samples is provided in Table 2 .

Matches were stratified into 24 subsamples defined by the value of the sportsbook total. The dependent variables are the 0.476, 0.5, and 0.524 quantiles of the true point total, as well as the expected profit of wagering conditioned on the amount of bias in the sportsbook’s total.

https://doi.org/10.1371/journal.pone.0287601.t002

Do sportsbook estimates deviate from the 0.476-0.524 interval?

In the common case of ϕ = 0.91, a positive expected profit is only feasible if the point spread (or point total) is either below the 0.476 or above the 0.524 quantiles of the outcome’s distribution. It is thus interesting to consider how often this may occur in a large betting market such as the NFL. To that end, the 0.476 and 0.524 quantiles of the margin of victory were estimated in each stratified sample (horizontal bars in Fig 2 ; the point spread is indicated with an orange marker; all quantiles are listed in Table 1 ).

With a standard payout of ϕ = 0.91, achieving a positive expected profit is only feasible if the sportsbook point spread falls outside of the 0.476-0.524 quantiles of the margin of victory. The 0.476 and 0.524 quantiles were thus estimated for each stratified sample of NFL matches. Light (dark) black bars indicate the 95% confidence intervals of the 0.476 (0.524) quantiles. Orange markers indicate the sportsbook point spread, which fell within the quantile confidence intervals for the large majority of stratifications. An exception was s = 5, where the sportsbook appeared to overestimate the margin of victory. For two other stratifications ( s = 3 and s = 10), the 0.524 quantile tended to underestimate the sportsbook spread, with the 95% confidence intervals extending to just above the spread.

https://doi.org/10.1371/journal.pone.0287601.g002

For the majority of samples, the confidence intervals of the 0.476 and 0.524 quantiles contained the sportsbook spread. One exception was the spread s = 5, where the margin of victory fell below the sportsbook value (95% confidence interval of the 0.524 quantile: [0.87,4.85]). The margin of victory for s = 3 (95% confidence interval of the 0.524 quantile: [0.78,3.08]) and s = 10 (95% confidence interval of the 0.524 quantile: [6.42,10.06]) also tended to underestimate the sportsbook spread, with the confidence intervals just containing the sportsbook value.

The analysis was repeated for point totals ( Fig 3 , all quantiles listed in Table 2 ). All but one stratified sample exhibited 0.476 and 0.524 quantiles whose confidence intervals contained the sportsbook total ( t = 47, [41.59, 45.42]). Examination of the sample quantiles suggests that NFL sportsbooks are very adept at proposing point totals that fall within 2.4 percentiles of the median outcome.

The 0.476 and 0.524 quantiles of the true point total were estimated for each stratified sample of NFL matches. For all but one stratification ( t = 47, 95% confidence interval [41.59-45.42], sportsbook overestimates the total), the confidence intervals of the sample quantiles contained the sportsbook proposition. Visual inspection of the data suggests that, in the NFL betting market at least, sportsbooks are very adept at proposing totals that fall within the critical 0.476-0.524 quantiles.

https://doi.org/10.1371/journal.pone.0287601.g003

How large of a discrepancy from the median is required for profit?

In practice, it is desirable to have an understanding of how large of a sportsbook bias, in units of points, is required to permit a positive expected profit. To address this, the value of the empirically measured CDF of the margin of victory was evaluated at offsets of 1, 2, and 3 points from the true median in each direction. The resulting value was then converted into the expected value of profit (see Materials and Methods ). The computation was performed separately within each stratified sample, and the height of each bar in Fig 4 indicates the hypothetical expected profit of a unit bet when wagering on the team with the higher probability of winning against the spread . For the sake of clarity, only the four largest samples ( s ∈ {−3, 2.5, 3, 7}) are shown in the Figure, with data for all samples listed in Table 1 .

In order to estimate the magnitude of the deviation between sportsbook point spread and median margin of victory that is required to permit a positive profit to the bettor, the hypothetical expected profit was computed for point spreads that differ from the true median by 1, 2, and 3 points in each direction. The analysis was performed separately within each stratified sample, and the figure shows the results of the four largest samples. For 3 of the 4 stratifications, a sportsbook bias of only a single point is required to permit a positive expected return (height of the bar indicates the expected profit of a unit bet assuming that the bettor wagers on the side with the higher probability of winning; error bars indicate the 95% confidence intervals as computed with the bootstrap). For a sportsbook spread of s = 3 (dark black bars), the expected profit on a unit bet is 0.021 [0.008-0.035], 0.094 [0.067-0.119], and 0.166 [0.13-0.2] when the sportsbook’s bias is +1, +2, and +3 points, respectively (mean and confidence interval over 500 bootstrap resamples).

https://doi.org/10.1371/journal.pone.0287601.g004

The expected profit is negative (i.e., ( ϕ − 1)/2 = −0.045) when the spread equals the median (center column). Interestingly however, for 3 of the 4 largest stratified samples, a positive profit is achievable with only a single point deviation from the median in either direction (the confidence intervals indicated by error bars do not extend into negative values). Averaged across all n = 21 stratifications, the expected profit of a unit bet is 0.022 ± 0.011, 0.090 ± 0.021, and 0.15 ± 0.030 when the spread exceeds the median by 1, 2, and 3 points, respectively (mean ± standard deviation over n = 21 stratifications, each of which is an average over 1000 bootstrap ensembles). Similarly, the expected return is 0.023 ± 0.013, 0.089 ± 0.026, and 0.15 ± 0.037 when the spread undershoots the median by 1, 2, and 3 points respectively. This indicates that sportsbooks must estimate the median outcome with high precision in order to prevent the possibility of positive returns.

The analysis was repeated on the data of point totals. A deviation from the true median of only 1 point was sufficient to permit a positive expected profit in all four of the largest stratifications ( Fig 5 ; t ∈ {41, 43, 44, 45}; error bars indicate 95% confidence intervals; data for all samples is provided in Table 2 ). When the sportsbook overestimates the median total by 1, 2, and 3 points, the expected profit on a unit bet is 0.014 ± 0.0071, 0.073 ± 0.014, and 0.13 ± 0.020, respectively (mean ± standard deviation over n = 24 samples, each of which is a average over 1000 bootstrap resamples). When the sportsbook underestimates the median, the expected profit on a unit bet is 0.015±0.0071, 0.076± 0.014, and 0.14± 0.020, for deviations of 1, 2, and 3 points, respectively. Note that despite the dependent variable having a larger magnitude (compared to margin of victory), the required sportsbook error to permit positive profit is the same as shown by the analysis of point spreads.

Vertical axis depicts the expected profit of an over-under wager, conditioned on the sportsbook’s posted total deviating from the true margin by a value of 1, 2, or 3 points (horizontal axis). The analysis was performed separately for each unique sportsbook total, and the figure displays the results for the four largest samples. A deviation from the true median of a single point permits a positive expected profit in all four of the depicted groups. For a sportsbook total of t = 44 (green bars), the expected profit on a unit bet is 0.015 [0.004-0.028], 0.075 [0.053-0.10], and 0.13 [0.10-0.17] when the sportsbook’s bias is +1, +2, and +3 points, respectively (mean and confidence interval over 500 bootstrap resamples).

https://doi.org/10.1371/journal.pone.0287601.g005

The theoretical results presented here, despite seemingly straightforward, have eluded explication in the literature. The central message is that optimal wagering on sports requires accurate estimation of the outcome variable’s quantiles. For the two most common types of bets—point spread and point total—estimation of the 0.476, 0.5 (median), and 0.524 quantiles constitutes the primary task of the bettor (assuming a standard commission of 4.5%). For a given match, the bettor must compare the estimated quantiles to the sportsbook’s proposed value, and first decide whether or not to wager ( Theorem 2 ), and if so, on which side ( Theorem 1 ).

The sportsbook’s proposed spread (or point total) effectively delineates the potential outcomes for the bettor ( Theorem 3 ). For a standard commission of 4.5%, the result is that if the sportsbook produces an estimate within 2.4 percentiles of the true median outcome, wagering always yields a negative expected profit— even if consistently wagering on the side with the higher probability of winning the bet . This finding underscores the importance of not wagering on matches in which the sportsbook has accurately captured the median outcome with their proposition. In such matches, the minimum error rate is lower bounded by 47.6%, the maximum error rate is upper bounded by 52.4%, and the excess error rate ( Theorem 4 ) is upper bounded by 4.8%.

The seminal findings of Kuypers [ 13 ] and Levitt [ 23 ], however, imply that sportsbooks may sometimes deliberately propose values that deviate from their estimated median to entice a preponderance of bets on the side that maximizes excess error. For example, by proposing a point spread that exaggerates the median margin of victory of a home favorite, the minimum error rate may become, for example, 45% (when wagering on the road team), and the excess error rate when wagering on the home team is 10%. In this hypothetical scenario, the sportsbook may predict that, due to the public’s bias for home favorites, a majority of the bets will be placed on the home team. The empirical data presented here hint at this phenomenon, and are in alignment with previous reports of market inefficiencies in the NFL betting market [ 5 , 32 – 35 ]. Namely, the sportsbook point spread was found to slightly overestimate the median margin of victory for some subsets of the data ( Fig 2 ). Indeed, the stratifications showing this trend were home favorites, agreeing with the idea that the sportsbooks are exploiting the public’s bias for wagering on the favorite [ 23 ].

The analysis of sportsbook point spreads performed here indicates that only a single point deviation from the true median is sufficient to allow one of the betting options to yield a positive expectation. On the other hand, realization of this potential profit requires that the bettor correctly, and systematically, identify the side with the higher probability of winning against the spread. Forecasting the outcomes of sports matches against the spread has been elusive for both experts and models [ 6 , 36 ]. Due to the abundance of historical data and user-friendly statistical software packages, the employment of quantitative modeling to aid decision-making in sports wagering [ 37 ] is strongly encouraged. The following suggestions are aimed at guiding model-driven efforts to forecast sports outcomes.

The argument against binary classification for sports wagering

The minimum error and minimum excess error rates defined in Theorems 3 and 4, respectively, are analogous to the Bayes’ minimum risk and Bayes’ excess risk in binary classification [ 38 ]. Indeed, one can cast the estimation of margin of victory in sports wagering as a binary classification problem, aiming to predict the event of “the home team winning against the spread”. Here this approach is not advocated. In conventional binary classification, the target variable (or “class label”) is static and assumed to represent some phenomenon (e.g. presence or absence of an object). In the context of sports wagering, however, the event m > s need not be uniform for different matches. For example, the event of a large home favorite winning against the spread may differ qualitatively from that of a small home “underdog” winning against the spread. Moreover, the sportsbook’s proposed point spread is a dynamic quantity. To illustrate the potential difficulty of utilizing classifiers in sports wagering, consider the case of a match with a posted spread of s = 4, where the goal is to predict the sign of m − 4. But now imagine that the the spread moves to s = 3. The resulting binary classification problem is now to predict the sign of m − 3, and it is not straightforward to adapt the previously constructed classifier to this new problem setting. One may be tempted to modify the bias term of the classifier, but it is unclear by how much it should be adjusted, and also whether a threshold adjustment is in fact the optimal approach in this scenario. On the other hand, by posing the problem as a regression, it is trivial to adapt one’s optimal decision: the output of the regression can simply be compared to the new spread.

The case for quantile regression

Conventional ordinary least-squares (OLS) regression yields estimates of the mean of a random variable, conditioned on the predictors. This is achieved by minimizing the mean squared error between the predicted and target variable.

The findings presented here suggest that conventional regression may be a sub-optimal approach to guiding wagering decisions, whose optimality relies on knowledge of the median and other quantiles. The presence of outliers and multi-modal distributions, as may be expected in sports outcomes, increases the deviation between the mean and median of a random variable. In this case, the dependent variable of conventional regression is distinct from the median and thus less relevant to the decision-making of the sports bettor. The significance of this may be exacerbated by the high noise level on the target random variable, and the low ceiling on model accuracy that this imposes.

Therefore, a more suitable approach to quantitative modeling in sports wagering is to employ quantile regression, which estimates a random variable’s quantiles by minimizing the quantile loss function [ 39 ]. Any features that are expected to forecast sports outcomes could be provided as the predictors in a quantile regression to produce estimates that are aligned with the bettor’s objectives: to avoid wagering on matches with negative expectation for both outcomes, and to wager on the side with zero excess error.

Potential challenges in moneyline wagering

Bias-variance in sports wagering

The view that low variance implies “simple” models has recently been challenged in the context of artificial neural networks [ 41 ]. Nevertheless, the desire for low-variance, high-bias modeling in sports wagering does suggest the preference for simpler models. Thus, it is advocated to employ a limited set of predictors and a limited capacity of the model architecture. This is expected to translate to improved generalization to future data.

Sport-specific considerations

The three types of wagers considered in this work—point spread, moneyline, and over-under—are the most popular bet types in North American sports. The empirical analysis employed data from the National Football League (NFL). One unique aspect of American football is its scoring system, in which the points accumulated by each team increase primarily in increments of 3 or 7 points. The structure of the scoring imposes constraints on the distribution of the margin of victory m . For example, in American Football, the distribution of the margin of victory is expected to exhibit local maxima near values such as: ±3, ±7, ±10. In the case of games in the National Basketball Association (NBA), the most common margins of victory tend to occur in the 5-10 interval, reflecting the overall higher point totals in basketball and its most common point increments (2 and 3). As a result, the shape and quantiles of the distribution of m may vary qualitatively between the NBA and NFL.

As a final illustrative example of the importance of the quantiles of m , consider the hypothetical scenario of two American football teams playing a match whose parameters θ have been exactly matched three times previously. In those past matches, the outcomes were m = 3, m = 7, and m = 35. In this fictitious example, the median is 7 but the mean is 15. Now imagine that the point spread for the next match has been set to s = 10 (home team favored to win the match by 10 points). Assuming that one has committed to wagering on the match, the optimal decision is to bet on the visiting team, despite that fact that the home team has won the previous matches by an average of 15 points.

Materials and methods

All analysis was performed with custom Python code compiled into a Jupyter Notebook (available at https://github.com/dmochow/optimal_betting_theory ). The figures and tables in this manuscript may be reproduced by executing the notebook.

Empirical data

Historical data from the National Football League (NFL) was obtained from bettingdata.com , who has courteously permitted the data to be shared on the repository listed above. All regular season matches from 2002 to 2022 were included in the analysis ( n = 5412). The data set includes point spreads and point totals (with associated payouts) from a variety of sportsbooks, as well as a “consensus” value. The latter was utilized for all analysis.

Data stratification

In order to estimate quantiles of the distributions of margin of victory and point totals from heterogeneous data (i.e., matches with disparate relative strengths of the home and visiting teams), the sportsbook point spread and sportsbook point total were used as a surrogate for the parameter vector defining the identity of each individual match ( θ in the text). This permitted the estimation of the 0.476, 0.5, and 0.524 quantiles over subsets of congruent matches.

Only spreads or totals with at least 100 matches in the dataset were included, such that estimation of the median would be sufficiently reliable. To that end, data was stratified into 21 samples for the analysis of margin of victory: {-7, -6, -3.5, -3, -2.5, -2, -1, 1, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 10) and 24 samples for the analysis of point totals (37, 37.5, 38, 39, 39.5, 40, 40.5, 41, 41.5, 42, 42.5, 43, 43.5, 44, 44.5, 45, 45.5, 46, 46.5, 47, 47.5, 48, 48.5, 49 }. This resulted in the employment of n = 3843 matches in the analysis of point spreads and n = 4300 matches in the analysis of point totals.

Note that the stratification process did not account for varying payouts, for example −110 versus −105 in the American odds system, as this would greatly increase the number of stratified samples while decreasing the number of matches in each sample. It is likely that the resulting error is negligible, however, due to the likelihood of the payout discrepancy being fairly balanced across the home and visiting teams.

Median estimation

In order to overcome the discrete nature of the margins of victory and point totals, kernel density estimation was employed to produce continuous quantile estimates. The KernelDensity function from the scikit-learn software library was employed with a Gaussian kernel and a bandwidth parameter of 2. For the margin of victory, the density was estimated over 4000 points ranging from -40 to 40. For the analysis of point totals, the density was estimated over 4000 points ranging from 10 to 90. The regression analysis relating median outcome to sportsbook estimates ( Fig 1 ) was performed with ordinary least squares (OLS).

Confidence interval estimation

In order to generate variability estimates for the 0.476, 0.5, and 0.524 quantiles of the margin of victory and point total, the bootstrap [ 42 ] technique was employed. 1000 resamples of the same size as the original sample were generated in each case. The confidence intervals were then constructed as the interval between the 2.5 and 97.5 percentiles of the relevant quantity. Bootstrap resampling was also employed to derive confidence intervals on the regression parameters relating the median outcomes to sportsbook spreads or totals ( Fig 1 ), as well as the confidence intervals on the expected profit of wagering conditioned on a fixed sportsbook bias (Figs 4 and 5 ).

Expected profit estimation

To model the idealized case of always placing the wager on the side with the higher probability of winning against the spread, the reported expected profit was taken as the maximum of the two expected values in ( 15 ). The analogous procedure was conducted for the analysis of point totals.

Acknowledgments

The author would like to thank Ed Miller and Mark Broadie for fruitful discussions during the preparation of the manuscript. The author would also like to acknowledge the effort of the reviewers, in particular Fabian Wunderlich, for providing many helpful comments and critiques throughout peer review.

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Effects of expertise on football betting

Yasser khazaal.

1 Geneva University Hospitals, Grand-pré 70 C, 1206 Geneva, Switzerland

Anne Chatton

Joël billieux.

2 Psychological Sciences Research Institute, Catholic University of Louvain, Louvain-La-Neuve, Belgium

Lucio Bizzini

Grégoire monney, emmanuelle fresard, gabriel thorens, guido bondolfi, nady el-guebaly.

3 Addiction Division, University of Calgary, Calgary, AB, Canada

Daniele Zullino

Football (soccer) is one of the most popular sports in the world, including Europe. It is associated with important betting activities. A common belief, widely spread among those who participate in gambling activities, is that knowledge and expertise on football lead to better prediction skills for match outcomes. If unfounded, however, this belief should be considered as a form of “illusion of control.” The aim of this study was to examine whether football experts are better than nonexperts at predicting football match scores.

Two hundred and fifty-eight persons took part in the study: 21.3% as football experts, 54.3% as laypersons (non-initiated to football), and 24.4% as football amateurs. They predicted the scores of the first 10 matches of the 2008 UEFA European Football Championship. Logistic regressions were carried out to assess the link between the accuracy of the forecasted scores and the expertise of the participants (expert, amateur, layperson), controlling for age and gender.

The variables assessed did not predict the accuracy of scoring prognosis (R 2 ranged from 1% to 6%).

Conclusions

Expertise, age, and gender did not appear to have an impact on the accuracy of the football match prognoses. Therefore, the belief that football expertise improves betting skills is no more than a cognitive distortion called the “illusion of control.” Gamblers may benefit from psychological interventions that target the illusion of control related to their believed links between betting skills and football expertise. Public health policies may need to consider the phenomenon in order to prevent problem gambling related to football betting.

Introduction

Football is one of the most popular sports in the world, Europe included. It is associated with important monetary transactions and financial sponsoring [ 1 ].

Sports betting is associated with pathological gambling [ 2 ] and is widely available on the Internet [ 3 ], one of the most important means for seeking general, medical, and gambling information [ 4 , 5 ]. There, one can find messages such as “To win at sports betting, you have to prognosticate correctly. Don’t forget that a sports bet is not the lotto. Sport is not only a question of chance, far from it. To place your bet efficiently, you must learn about football as a sport and follow a minimum of its championships.”

Football competition is, unmistakably, a sport based on a high level of training and specific skills. This assertion may lead to the belief that football knowledge and expertise will allow better prediction of match scores. If unfounded, however, this belief should be considered a form of “illusion of control.” This term was defined by Langer [ 6 ] as “an expectancy of a personal success probability inappropriately higher than the objective probability would warrant.” This type of distorted thinking was considered a major factor in gambling persistence and severity [ 7 , 8 ], and led to the development of cognitive restructuring therapies for pathological gamblers [ 6 ].

As suggested by Cantinotti, Ladouceur, and Jacques [ 9 ], to a certain degree, the utility of sport expertise in sport betting cannot be fully ruled out. For example, it was previously found that factors such as the home field advantage, team rankings, most recent results of teams, and injuries of key players significantly affect game results [ 10 - 14 ]. It was then suggested that skills could be helpful when betting on sports events [ 15 ].

Probably in connection with these considerations in sport and football betting, defeats have been shown to be more often discussed than wins [ 16 ] and were commonly attributed to unlikely or random events [ 5 ] or were considered a “near win” [ 11 ], whereas wins were attributed to skills in selecting the victorious players. This interpretation probably contributes to an overestimation of betting skills [ 5 ].

It would be relevant to determine whether expertise is essential for determining game scores. If this were not the case, the alleged skills in sports betting could be regarded as no more than a manifestation of the illusion of control, as observed in most gambling activities.

With several exceptions, such as horse betting [ 17 ] and hockey [ 7 ], the relation between gamblers’ skills and betting outcomes has been rarely studied. Studies that evaluated gambling skills rather than the role of expertise in sports for betting activities showed that monetary gains from gambling skills were not significantly higher than would have occurred by chance. Because of the wide popularity of football and football betting, it seems important from a public health policy perspective to assess the links between football expertise and prediction of match results.

The present study examined whether football experts were better than non-experts for predicting the scores of the first 10 matches of the 2008 UEFA European Football Championship.

During the 3 weeks prior to the beginning of the first match of the 2008 UEFA European Football Championship, a questionnaire was completed anonymously by 258 study participants recruited through local advertising and direct contact of football professionals (players, handlers, and referees) and sports reporters. The questionnaire assessed professional and amateur activity in relation to football. It also included five questions (Table ​ (Table1) 1 ) related to the degree of football interest (questions 1, 2, and 3), the degree of belief in the link between a good knowledge of football teams and accuracy of match-related prognoses (question 4), and sport betting habits (question 5). In addition, participants predicted outcomes for the first 10 matches of the 2008 UEFA European Football Championship.

Questions related to football and sport betting

Participants were classified as being in one of three categories:

(a) “Experts”: The experts are professional or semiprofessional football players, coaches, or football sport journalists whose work was related to the 2008 UEFA European Football Championship.

(b) “Amateurs”: These participants have an amateur link with football (e.g., amateur referee) and/or play football as amateurs.

(c) “Laypersons”: This group has neither professional nor amateur connections.

The forecasts were analyzed for winning accuracy (accuracy of the prognosis: winning team 1, winning team 2, or draw) and score accuracy (good score prediction).

Statistical analyses were performed with SPSS for Windows (version 15.0). An initial exploratory analysis involved the calculation of proportions, as well as means and standard deviation of the outcome values. Spearman correlations with Bonferroni’s correction ( p  = 0.05/4 since four correlations were analyzed; p  = 0.0125) were carried out to assess the links between each of the first four questions related to football interests and the fifth related to sports betting (Table ​ (Table1). 1 ). Moreover, one-way analyses of variance (ANOVAs) were performed to compare the distribution of the mean numbers of correct outcomes and correct score predictions as dependent variables with regard to the above-cited first four questions as factors, adjusting for multiple pairwise comparisons.

We also used a paired samples t -test to test whether gamblers had a greater number of correct outcomes than chance when forecasting the results of the games. Indeed, by chance, that is to say in the absence of any information, the probability of a gambler predicting 7 correct outcomes out of 10 games (0.016; the exact formula for the binomial distribution is given by p x = ( x n ) p x 1 − p n − x , where x is the number of successes and n the number of trials) is not the same as the probability of predicting 7 outcomes out of 10, given all the information in the bettor’s possession (0.7; given by the assumption: 7 correct outcomes out of 10 games). This last probability, referred to as conditional probability, means that before making a choice, the bettor will take into account all relevant information at their disposal. In addition to each participant’s observed probability of making the right bet, one may compare this to the expected probability based on chance.

Finally, a binary logistic regression for each of the 10 matches was done to predict the accuracy of the scores (correct vs. incorrect score) with the participants’ expertise categories (expert, amateur, or layperson) as predictor, controlling for age and gender (female vs. male). For the categorical factors “gender” and “expertise,” the reference groups were levels 2 and 3, respectively.

After checking for multicollinearity and outliers, we assessed the goodness of fit of these logistic models by considering the following:

The classification table of the intercept-only model (baseline or null model) with that of the full model, where a significant improvement should be expected over the null model.

The Nagelkerke R-square statistic with all the independent variables. This statistic attempts to quantify the proportion of explained variation in the logistic regression.

The statistical tests of the predictors, using the Wald chi-square statistics. P-values less than 0.05, or alternatively, confidence intervals that exclude the “1” value, are suggestive of significant predictions.

Two hundred and fifty-eight persons participated in the study (57% were men; mean age: 36.6 years ± 11.2). Fifty-five (21.3%) were classified as football experts, 140 (54.3%) as laypersons, and 63 (24.4%) as amateurs.

Answers to the five questions in the questionnaire are reported in Table ​ Table2. 2 . After Bonferroni’s correction was performed, the Spearman correlation showed significant associations between the first three questions related to football interest and sports betting (Spearman’s r = 0.49, r = 0.43, r = 0.41; p  < 0.0005, respectively). Sports betting appeared to be associated with football interest. There was no correlation found between question 4 (believed role of football expertise for prognosis skills) and sports betting.

Distribution of participants’ answers to the five questions reported in Table ​ Table1 1

The numbers and percentages of accurate outcomes and scores by category of participants are reported in Table ​ Table3. 3 . The mean number of correct outcome or score prognoses and the relative frequency of the distribution of correct outcomes by category of participants are reported in Table ​ Table4 4 and Figure ​ Figure1, 1 , respectively.

Number and percentage of correct outcomes and scores by categories of participants and by match

Comparison of mean number (standard deviation) of correct outcomes and scores exactly predicted by each group of participants

Distribution of relative frequencies of correct outcomes.

The ANOVAs that were used to compare the distribution of the mean numbers of correct outcomes and correct score predictions with regard to the first four questions showed a statistical significant between-group difference for the mean number of correct outcomes (F (3,253)  = 2.8 and p  = 0.04) in question 4 (“I think that a good knowledge of the teams allows me to predict with accuracy the match score results”). But after adjusting for multiple comparisons, this difference was no longer significant. No significant difference before or after adjustment was observed for the other three questions.

The paired sample t -test that was used to evaluate whether gamblers had a greater number of correct outcomes than chance when forecasting the results of the games showed a statistical significant difference (t = 39.15 and p  < 0.0005). We conclude from the data that the bettors were more accurate in their predictions than chance.

The logistic regressions, which were done to test the research hypothesis, yielded poor results. The classification table of the full models showed no improvement over the baseline models, meaning that the classification rates were exactly the same in both situations (Table ​ (Table5, 5 , column 2). The Nagelkerke R-square measures ranged from 1% to 6%, leading us to conclude that these models were not useful in explaining the outcome variable (Table ​ (Table5, 5 , column 3). Finally, the predictor variable “expertise” (Table ​ (Table5, 5 , column 4) did not prove significant except for the model involving the game Germany-Poland ( p  = 0.03, odds ratio = 2.57 and 95% CI for odds ratio = [1.08; 6.14]). This result means that compared with a layperson, being an amateur increases the likelihood of accurate score prediction by 2.57, assuming that the other factors in the model are held constant. There was no significant difference between experts and laypersons since the confidence interval includes “1” (exact results not shown).

Evaluation of model’s goodness of fit

*Maximum iterations reached and final solution not found because group sample size too small.

It is worthwhile noting that no expert was able to correctly predict more than seven outcomes and no participant more than eight (Figure ​ (Figure1 1 ).

In the present study, the results of the logistic regressions, although poor, were consistent across matches. Experts do not appear to be better than non-experts at predicting football match scores. Similarly, ANOVA results indicated that the average number of correct outcomes with respect to accurate scores were not significantly different across the four conditions (first four questions in Table ​ Table1). 1 ). The belief that expertise is useful for sports gamblers seems to be simply an illusion of control.

By chance alone, the probability of someone predicting 10 correct outcomes (first winning team, second winning team, or draw) out of 10 games is estimated to be 1.7 100 , 000 , i.e., P X = 10 = 10 ! 10 ! 0 ! × 1 3 10 × 2 3 0 . The exact formula for the binomial distribution is given by p x = ( x n ) p x 1 − p n − x , where χ is the number of successes and n the number of trials. This is an interesting probability for the sports betting business, which mostly offers big monetary winnings on a combination of match results. Thus, in consideration of this probability and the lack of impact of expertise on football betting outcomes, sports betting appears to be nothing other than a game of chance, as suggested by other studies [ 7 , 15 ].

As reported elsewhere [ 18 ], sport interest, rather than the athlete’s status [ 19 ], is possibly linked to sport betting. The finding of a lack of association between sports bets and the belief assessed in question 4 (“I think that a good knowledge of the teams allows me to predict with accuracy the match score results”) may result from the present sample being participants from the community and not problem or pathological gamblers. About 6% of the subjects did, however, consider this declaration as extremely correct and more than 30% as fairly correct, showing the wide diffusion of such beliefs.

One possible limitation of the present study is that it was not carried out as a real gambling condition. The results should be then taken with caution. Further studies may include measures of gambling-related cognitions (e.g., fallacy, superstitious beliefs, biased evaluation of outcomes), participants’ betting behaviors and habits, and more detailed measures of expertise and self-confidence related to a sense of expertise, as suggested by wagering models [ 20 ]. Further studies may also include betting related to other sport activities.

Another limitation was the small sample of games surveyed and the non-random selection of these games, which resulted in a non-probability sample. Out of all matches that were played during the 2008 UEFA European Football Championship, only the first 10 were selected for analysis. The possibility that, by pure chance, the games selected happened to be more or less predictable than the standard ones should not be ignored.

Finally, the logistic regression models set up to predict the accuracy of the number of goals scored by each team may have failed to take account of other possible significant predictors, such as the quality of the teams (ability to attack and/or to defend), the team’s league position at the time of playing, and the “home effect” (advantage in playing at home). The absence of these potential predictors may explain the small predictive power of our models.

Expertise, gender, and age did not have an impact on the accuracy of the football match prognoses. Consequently, the belief that football expertise improves betting skills seems to be a cognitive distortion.

Clinicians may inform gamblers about the limited help of football expertise in match-outcome predictions and the relative fallacy of commercial advertisements for sport betting, such as “….a sports bet is not the lotto… to place your bet efficiently, you must learn about football as a sport and follow a minimum of its championships.” Gamblers may benefit from psychological interventions that target the illusion of control related to their believed links between betting skills and football expertise. Furthermore, public health prevention policies may need to consider the present results in order to prevent problem gambling related to football betting.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

YK and DZ participated in the design of the study. YK and NG drafted the manuscript. AC performed the statistical analysis. JB, LB, GM, EF, GT, RK, and GB participated in recruitment and data collection. All authors read and approved the final manuscript.

Acknowledgements

We thank the study participants, the football experts who agreed to participate in the study, GREA and Mr. Pascal Savary, the “Rien ne va plus,” the Geneva Health Department, Dr. Christine Davidson, Mrs. Alessandra Horn, and Mr. Christian Osiek.

Funding source

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College football betting guide: Trends to consider before making picks, predictions for the 2024 season

A primer to explain everything you need to know about wagering on college football this upcoming season.

College football has changed a lot in recent years, but not every change has involved paying players or conference realignment. For fans, one of the biggest shifts has been the prevalence of sports betting.

Once an activity banished to the back corner of a dingy bar, only to be whispered about, betting on sports is now legal in many states nationwide. When you tune into a college football game on a Saturday afternoon, you're assailed non-stop with ads for legal online sportsbooks during commercial breaks and even sponsored in-game segments. Last year, the Big Ten passed a rule requiring its teams to publish injury reports and the SEC plans to do the same this year. These are changes made with gambling in mind to help ensure there isn't any foul play.

Eventually, we will see the conferences pair with sportsbooks as an additional source of revenue. Hell, given what we've heard about the Big 12 looking to sell its naming rights , we might see a league named after one soon!

All of this has led to more fans dipping their toe into the world of sports betting. It can be intimidating if you don't know what you're doing, but don't worry -- nearly everybody doing it doesn't know what they're doing, either. This is a handy little betting guide to help teach you some of the absolute basics; it is not a guide to winning money betting on sports.

Sorry to hit you with a bucket of cold water, but most people don't win money betting on sports, even though every one of your friends says they do. Unless you plan on doing this professionally, which consumes far more of your time than you realize, the goal should be to win some bets and have fun. This guide should help you achieve those goals.

All stats and trends according to TruMedia

College football betting basics

What can you bet in college football? While sportsbooks will offer prop bets on players and game-time situations during the season, those are more difficult to master, particularly if one does not understand the basics. The bread and butter of college football betting consists of the point spread (or "spread"), the total and the moneyline.

The spread : The most popular bet, the spread is the number of points given to a team to handicap a game with two equally likely outcomes. For example: in Week 0, Florida State and Georgia Tech are squaring off in Ireland. The spreads are listed as Florida State (-12.5) vs. Georgia Tech (+12.5). The easiest way to think about this is the game starts with Georgia Tech given a 12.5-point lead. Suppose you bet Florida State (-12.5), the Seminoles need to win by at least 13 points for you to win your bet. If you bet Georgia Tech, you win your bet if Tech wins outright or loses by 12 points or fewer. While this spread includes a half-point to make sure there's no tie, that's not always the case. If the spread was 13 and the game ended with a 13-point margin, your bet would be graded a "push" and your money would be refunded.

The total : This represents the total points scored in the game. The listed total for the same Florida State-Georgia Tech game is 56.5 points. You can bet on the over or under. If you think more than 56.5 points will be scored in the game, you bet the over 56.5. If you think there will be fewer, you bet the under 56.5. Pretty straightforward, isn't it?

The moneyline : This is the simplest bet because you're picking who will win the game outright. The math isn't straightforward, however. As a 12.5-point favorite, Florida State is clearly expected to win more often, which is why it's listed at (-500) on the moneyline. Georgia Tech is at (+375). That means the payouts will differ depending on which side you choose. 

A simple way to go about it is to think in $100 bets: To win $100 betting Florida State at (-500), you must risk $500. Conversely, a $100 bet on Georgia Tech (+375) would win you $375 if the Yellow Jackets pull off the upset. You are paying the price, given the likelihood of your chosen outcome occurring.

Another way to think about it: If the odds are (-500), divide one by five and you get 0.20, which means you will win 20 cents for every dollar you risk. If you have plus odds, like Georgia Tech at (+375), multiply one by 3.75. You win $3.75 for every dollar you risk.

Odds : Moneylines are not the only bets with odds attached to them. Spread and total bets have odds as well. Using the same game as the example, Florida State -12.5 is listed with (-110) attached. Georgia Tech +12.5 also has (-110), as do both sides of the total. This is called the "juice" or "vigorish" (aka "vig"). Essentially, it's how much the sportsbook charges you for the ability to make a bet. While -110 is standard, the odds can fluctuate for spreads and totals depending on various factors. Like the moneyline, with -110 juice you have to bet $110 to win $100. Another factor you must consider, though, is implied odds.

Implied odds

The simplest way to think of implied odds is how often you have to win a particular bet to make money. The math is simple. If the odds are a negative number, remove the negative and add 100 to that number. Then divide the original odds by the new number. So, for -110, we add 100 to 110 to get 210. We then divide 110 by 210 to get 52.38%. That means you must be correct 52.38% of the time to make money on that wager. If you place 100 bets at (-110) and win 52, you will lose money even though you won more bets than you lost. 

If the juice is a positive number, the process is slightly different. Using Georgia Tech's moneyline of (+375), we again add 100 to the 375 before dividing 100 by the new number. So, it would be 100 divided by 475, which equals 21.05%. Georgia Tech needs to win the game 21.05% of the time for you to break even in the long run. Those are its implied odds. If you want to bet Florida State (-500), you better be sure the Seminoles are winning the game at least 83.33% (500/600) of the time.

I know what you're thinking. "But, Tom, when I add up the implied odds of those moneyline bets, I get 104.38%!"

You sure do! There's a reason there are so many sportsbooks out there and they all make money. They're designed so that no matter what happens, the sportsbook will make money, and you will lose money in the long run if you aren't familiar with the implied odds of a bet.

Now that we've gotten the education out of the way, let's get to some of the fun stuff.

Is there an advantage to betting favorites or underdogs?

There is not. One thing to remember as you enter the sports betting space is nothing is designed to make it easier for you to win. While you can sometimes see casual bettors betting on favorites ("they're the better team, of course they'll cover!") or the more recognizable team ("Georgia is good, right?"), that doesn't have an impact on results. Plus, the books know this and will juice things accordingly.

I have numbers to back it up if you're skeptical. Going back to the 2014 season, the beginning of the College Football Playoff era, excluding pushes, favorites have gone 4,071-4,207 ATS. That's a cover rate of 49.2%. That means underdogs have covered 50.8% of the time.

But remember, the vig exists, and at standard juice of (-110) you need to win 52.38% of your bets to make money. So if you had bet every underdog in every game since 2014, you'd have won more often than you lost but still have lost a lot of money along the way.

Also, no matter the spread, there's no noticeable difference. A 20-point favorite is just as likely to cover as a 3-point favorite. So when you see a team that's a 31-point underdog, don't talk yourself into "this team starts with a 31-0 lead! I can't lose!" You can, and you will half the time.

For entertainment purposes, here's a look at the schools that have been favored the most since 2014, along with the schools that have covered the most often as favorites. Below that will be most frequent underdogs. 

Most frequent favorites (since 2014)

Most successful favorites since 2014 (min. 30 games)

Most frequent underdogs (since 2014)

Most successful underdogs since 2014 (min. 30 games)

Is the over or under a better bet?

Going back to the 2014 season, there's more of an advantage here than the spread but not enough to win money. Since 2014, the under has hit more often, winning at a rate of 51.2%. Again, assuming standard juice, we need to win 52.38% of the time, so we'd have lost less money on the under but have lost it all the same.

All that said, there are some things to consider when deciding to bet on the total. None of it's foolproof, but it's a decent place to start. Typically, teams that move at a quicker tempo on offense and run a lot of plays are more likely to score points. Conversely, the teams that move slowly, run the ball a lot and play the field position game score fewer points.

Another thing to look for is how teams perform in the red zone. An offense that can easily move the ball down the field but struggles to finish drives and settles for field goals can sometimes "trick" you. Some defenses play a bend-but-don't-break style that allows plenty of yards but shuts things down in the red zone and holds teams to field goals.

I always pay attention to how the two teams in a game perform in the red zone on both sides of the ball before placing a bet on the total. There is no magic formula to find winners, but paying attention to this can give you a slight leg up on those who don't. It's not a bad thing to consider when betting the spread, either.

Also, you want to pay attention to rule changes and how they impact games. With new clock rules in place last season, we saw a lot of games early in the season finishing under the posted total before books began lowering totals for games. From 2014 to 2022, the average total for an FBS game was 56.21. The average total for the 2023 season was 52.22. That's an incredible drop! How might the implementation of a two-minute warning impact games this season? My guess is it'll lead to more points because the additional timeout will allow offenses more time to score late in games, but we won't know until the games begin.

As we did with favorites and underdogs, let's look at which teams go over the total the most often and which ones tend to stay under.

Best 'over' teams (min. 100 games)

Best 'under' teams (min. 100 games)

Do trends matter?

Not nearly as much as people will lead you to believe. From a purely mathematical standpoint, trends hold no predictive value. A team covering its last five games as a road underdog does not guarantee they'll cover the sixth.

Trends are nice to support theories about a game, but they should never be followed blindly. I'll use my favorite "trend" as an example. Since the 2005 season, when service academies (Air Force, Army and Navy) play each other, the under has gone an astounding 46-10-1. It seems impossible, but it's easy to understand. Service academies run option offenses and run the ball on nearly 80% of their plays. That means the clock rarely stops running, which limits the overall number of plays and possessions in a game, and the fewer plays and possessions, the fewer opportunities to score points.

It's been a bet I've placed on each of the three meetings between the academies for years, but I never do it blindly. 

As I mentioned earlier, the average total for FBS games dropped from 56.21 between 2014 and 2022 to 52.22 last season, and service academy games were not immune. For years, the totals for these games were posted in the 40s. Last year's Army-Navy Game finished with a total of 28.5. At some point, the trend will come to an end, and my sense is that end is closer than ever before.

So when somebody tells you to make a bet because of a trend, instead of following the trend, try to figure out why that trend exists and if there's anything that explains it. If you realize it's just dumb luck, ignore it, but if you believe you've found something behind it, then you can consider trusting it.

But always remember that just because it's worked in the past doesn't mean it will continue to work in the future.

How am I supposed to make money doing this?

You aren't. I know that much of what I've written here can make it seem like there's no point in betting on sports, but it depends on your ultimate goal. If you want to be a bettor that makes money in the long run, it's possible. Plenty of people do so, but they devote a lot of time and attention to doing so. 

Successful bettors aren't opening their phone five minutes before kickoff and going with their gut. They spend hours monitoring stats and data to form power ratings and looking for spots to exploit. And these pros and semi-pros will tell you that it gets harder to find those edges every single year, particularly now that it's legal to bet on sports in so many parts of the country.

That's why the best advice I can give you is to have fun. Do not start betting on games thinking you're going to get rich. You might get lucky and get a big win, but you're far more likely to lose in the long run. 

Never bet more than you're comfortable losing, and remind yourself that it's all designed to have you lose.

When a commercial tells you how great the parlays are at a sportsbook, ask yourself, "Why do they want me to bet parlays so badly?" Simple! They're harder to win! Think of it as a coin flip. If you flip a coin once, there's a 50% chance it'll be heads, but if you have to get heads twice in a row, the chances drop to 25%. For every leg you add, the less likely you are to win, and while the payouts on parlays increase with each leg, they never increase enough to match your actual odds of winning.

Also, the "odds boosts" offered by books are rarely as beneficial to you as they'll have you believe. That's not to say there aren't boosts worth taking, but use your better judgment before placing a bet simply because the sportsbook is pushing it. 

And, finally, if you read this and manage to crack the code, remember the person who helped set you on the path to wealth beyond your wildest dreams, will you?

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‘I’m So Scared’: NFL Players on How Betting Changes the Sport

Good for the league. Not so good for you.

(From left) NFL players Austin Ekeler, River Cracraft, Terron Armstead, Julius Thomas and Chase Edmonds.

Photo illustration: 731; Photographers: Devin Christopher and Jared Soares for Bloomberg Businessweek; Getty Images; YouTube

NFL players are grappling with a complex new reality. They’re aware of the money being bet on every catch, run and touchdown and generally think it’s good for the league’s (and thus their own) financial health. But they’re also—if you can say this about a professional football player—scared on a personal level and generally freaked out about running afoul of league rules. “It has struck fear into me,” says Miami Dolphins wide receiver River Cracraft. (A spokesman for the NFL says it’s “working tirelessly to ensure that the integrity of our game is preserved, our players, coaches and staff are educated on our gambling policy, and that our fans are protected.”)

In early August, Bloomberg Businessweek talked with a handful of current and former players, including some, like Cracraft, who are part of the Pro Athlete Community , an organization that helps athletes pursue new careers after they’re done playing. Here are edited excerpts from those conversations.

The rise of legal sports gambling is coming at the expense of stock investing, new study shows

• A new academic study said people are diverting stock investments into legal gambling.
• The researchers founded that household investments are reduced by roughly $2 for ever dollar wagered.
• This has had a disproportionately negative effect on lower-income households, the study found.

The surging popularity of legal sports betting has been met with fanfare from American consumers. But a new working study finds its rise is coming at the expense of stock investments.

The research, which has yet to be peer-reviewed, found that the net investments held by a household is reduced by roughly $2 for every dollar directed towards a bet.

"Our results suggest that access to online sports betting comes at the expense of equity market attachment and exacerbates financial difficulties faced by constrained households," a group of five academic researchers wrote.

Betting took over the modern American sports experience in 2018, when the Supreme Court overruled a federal law prohibiting it. States were left with the control, and 38 have since legalized it.

With gambling made as simple as downloading an app, billions have been wagered. Where the total amount bet in the US stood at $1.1 billion in January 2019, this figure catapulted to $14 billion the same month this year, data from the Sports Book Review shows.

The study said US households bet an average of $1,100 per year, or $280 a quarter — a number that's continued to grow by $25 per quarter.

Meanwhile, the researchers found that net investments typically fell nearly 14% in the two to three years after a legalization occurred in a state.

Further, the study noted that financially constrained households tend to contribute a larger chunk of their income toward sports gambling, and are therefore hit harder by the negative effects.

"These households, already in relatively bad financial shape, are more likely to divert funds from their investment portfolios to betting activity," the researchers wrote. "Given that sports betting has a negative expected value, this finding underscores the potential for sports betting legalization to exacerbate financial vulnerability and hardship."

A separate recent working paper reached a similar conclusion, outlining how credit has been damaged in areas where sports gambling is legal. In these areas, credit scores have dipped 1%, while debt collection and bankruptcies have jumped 8% and 28%, respectively.

"It's never enough," Michelle Malkin, the director of East Carolina University's Gambling Research & Policy Initiative, previously told Business Insider. "You've got to keep on gambling. So it's this cyclical thought pattern of, 'I can fix my problems by keeping gambling and getting that next win.'"

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