How Using Statistics Can Help You Find the Best Value Sports Betting Odds

Betting Academy

How Using Statistics Can Help You Find the Best Value Sports Betting Odds

Betting Academy Gyles Farran

In the world of sports betting, where everything moves so fast and trends change daily, intuition and luck are not the way to go; betting is not a lottery, it’s much more complex.

Top bettors don’t rely on luck and feelings, they follow a clear structure with heavy data-driven insights and betting tips playing a massive role, making it very important to know how to use statistics on every wager.

One of the main reasons that makes data and statistics so important in betting is trying to find the best value betting odds, trying to find outliers that can increase wins without heavily increasing the risks.
But how can you apply these statistics to find the best value bet possible?

The Concept of Value

Before starting with the different methods that top-tier bettors use to find the best value bets, it’s important to understand what exactly “value” is. Although there are many existing definitions for the word “value”, when it comes to betting, value refers to the occasion where bookmakers misprice a certain event, making the probability of an outcome occurring higher than the probability bookmakers have implied on their odds.

Therefore, to find the best value bets, it’s important to use statistics and know how to read the numbers given. For example, we may find an outlier reflected in the odds from NetBet, but, without data, we may not be able to identify such outlier, thus why it’s so important to know when to put a wager and where to do so.

Data 101: The Essentials

Now that we have explained the concept of value and why data is so important to identify outliers, understanding the basics is key to getting in touch with statistics. Although the range of data may be overwhelming and the amount of tips available on the internet may differ from website to website, these metrics are the fundamental pieces of your analyses.

We will use football metrics to explain this, but all sports have very similar metrics to help you identify outliers.

xG (Expected Goals): arguably the most important statistic, expected goals are the fundamental of any statistical analysis. xG measures the overall quality of a scoring chance and the probability of it ending in a goal. A great way to find outliers through xG is to find teams with a high xG but poor results could be a great outlier, as, maybe, poor results may have come from luck or poor form on a specific game.

Head-to-Head: another very important metric that mustn’t be overlooked is head-to-head comparisons. In football, there are specific matches where a team tends to perform a specific way, no matter what their situation. For example, a team may be battling for relegation but, when they must play against their local rivals, they may play better. Eventually, you’d want to take a close look at historical matchups where a team has been outperformed consistently for various seasons, finding an excellent outlier where you can place a winning bet.

Player Availability and Injuries: another tremendously important metric that can really change the game. Statistics can quantify how much a player’s absence can change how a team plays and their win-lose ratio, something that may slip under a bookmaker’s radar, who may not change their odds as they haven’t adjusted to lineup changes.

Data 101: How to Build a Data-Driven Strategy

Collecting statistics is vital, but it’s much more important to know how to interpret them correctly. A data-driven approach requires many things: combining quantitative analysis with bankroll management, decision-making and many more.

To build a good strategy, it’s important to create a simple model. Don’t make things very complex, start easy and build as you go, begin with a simple spreadsheet where you can quickly apply different formulas that calculate exact probabilities and then start comparing those probabilities with the bookmakers’ odds.

Once you understand how to interpret data with a simple strategy, expand to more complex data like player ratings, home advantage and more. Eventually, you don’t want to predict matches, you want to make intelligent decisions.

Data 101: The Human Part

Statistics may predict various events, but there are many things that it can’t capture. Therefore, it’s important to understand the context behind each bet you place. For example, statistics may show that a team has performed well in the last few seasons, but it can’t detect whether that team has changed manager or their style.

Therefore, try to control whatever depends on you, watch matches, be up to date with the latest news, read tactical analysis and try to understand what’s happening behind every club you are placing your bets in.

To find the best value bets, it’s not about finding the best statistical model, it’s about finding the sweet spot between statistics and personal experience (which is much different from taking emotional decisions), letting numbers guide you but using context to interpret and make the final decision.

How Using Statistics Can Help You Find the Best Value Sports Betting Odds

Betting Academy Gyles Farran

In the world of sports betting, where everything moves so fast and trends change daily, intuition and luck are not the way to go; betting is not a lottery, it’s much more complex.

Top bettors don’t rely on luck and feelings, they follow a clear structure with heavy data-driven insights and betting tips playing a massive role, making it very important to know how to use statistics on every wager.

One of the main reasons that makes data and statistics so important in betting is trying to find the best value betting odds, trying to find outliers that can increase wins without heavily increasing the risks.
But how can you apply these statistics to find the best value bet possible?

The Concept of Value

Before starting with the different methods that top-tier bettors use to find the best value bets, it’s important to understand what exactly “value” is. Although there are many existing definitions for the word “value”, when it comes to betting, value refers to the occasion where bookmakers misprice a certain event, making the probability of an outcome occurring higher than the probability bookmakers have implied on their odds.

Therefore, to find the best value bets, it’s important to use statistics and know how to read the numbers given. For example, we may find an outlier reflected in the odds from NetBet, but, without data, we may not be able to identify such outlier, thus why it’s so important to know when to put a wager and where to do so.

Data 101: The Essentials

Now that we have explained the concept of value and why data is so important to identify outliers, understanding the basics is key to getting in touch with statistics. Although the range of data may be overwhelming and the amount of tips available on the internet may differ from website to website, these metrics are the fundamental pieces of your analyses.

We will use football metrics to explain this, but all sports have very similar metrics to help you identify outliers.

xG (Expected Goals): arguably the most important statistic, expected goals are the fundamental of any statistical analysis. xG measures the overall quality of a scoring chance and the probability of it ending in a goal. A great way to find outliers through xG is to find teams with a high xG but poor results could be a great outlier, as, maybe, poor results may have come from luck or poor form on a specific game.

Head-to-Head: another very important metric that mustn’t be overlooked is head-to-head comparisons. In football, there are specific matches where a team tends to perform a specific way, no matter what their situation. For example, a team may be battling for relegation but, when they must play against their local rivals, they may play better. Eventually, you’d want to take a close look at historical matchups where a team has been outperformed consistently for various seasons, finding an excellent outlier where you can place a winning bet.

Player Availability and Injuries: another tremendously important metric that can really change the game. Statistics can quantify how much a player’s absence can change how a team plays and their win-lose ratio, something that may slip under a bookmaker’s radar, who may not change their odds as they haven’t adjusted to lineup changes.

Data 101: How to Build a Data-Driven Strategy

Collecting statistics is vital, but it’s much more important to know how to interpret them correctly. A data-driven approach requires many things: combining quantitative analysis with bankroll management, decision-making and many more.

To build a good strategy, it’s important to create a simple model. Don’t make things very complex, start easy and build as you go, begin with a simple spreadsheet where you can quickly apply different formulas that calculate exact probabilities and then start comparing those probabilities with the bookmakers’ odds.

Once you understand how to interpret data with a simple strategy, expand to more complex data like player ratings, home advantage and more. Eventually, you don’t want to predict matches, you want to make intelligent decisions.

Data 101: The Human Part

Statistics may predict various events, but there are many things that it can’t capture. Therefore, it’s important to understand the context behind each bet you place. For example, statistics may show that a team has performed well in the last few seasons, but it can’t detect whether that team has changed manager or their style.

Therefore, try to control whatever depends on you, watch matches, be up to date with the latest news, read tactical analysis and try to understand what’s happening behind every club you are placing your bets in.

To find the best value bets, it’s not about finding the best statistical model, it’s about finding the sweet spot between statistics and personal experience (which is much different from taking emotional decisions), letting numbers guide you but using context to interpret and make the final decision.