A Guide to Statistics in Sports Betting
If you’re a serious sports bettor, then it’s worth studying and analysing the numbers for any event that interests you. These figures will help you to identify the best possible outcome for your wager.
Principles of Application of Statistics in Betting
Statistics is the collecting, organising, analysing and interpretation of data. In sports betting, this would be the same as collecting information. The info you need is about the teams, the players and past performances and is required to calculate the best outcome.
Statistical analysis is used in sports betting by identifying the factors that have a secure connection to a probability of winning. This is information that won’t be obvious to the betting public. It requires a lot of effort but is worth it in the end.
How to Read the Data
When it comes to reading statistics, an important fact to understand is the “significance” in the data doesn’t mean that it’s relevant. This occurs when there’s no connection between the two variables, and it’s unlikely that an event happened, the result is said to have no significance.
For example, we state that that “games played percentage” play an important role in whether an NBA team wins or loses. To start, we must find information about a vast amount of historical NBA data. We then take a look at how often the team with the more significant number of games won their game.
We’d have a percentage of statistical significance, depending on that answer. This method can be used for lots of factors to get an idea of which variables impact losing or winning, and to what extent. The more significant the factor is, the more likely you can trust it to tie-in to winning.
Keep in mind that connections in data don’t necessarily mean that it will cause a result. Just because two variables have a link, it doesn’t mean that one caused the other.
What Findings and Conclusions does Statistics give?
Doing math isn’t enough for betting. You need to understand how it helps you to make the right decision. It’s only worth placing a wager on a bet if it has a positive value. The suggested possibility needs to be at a lower percentage than the likelihood you worked out from your analysis.
In this way, it gives the bet a positive value. If your calculations say the Chicago Bulls will win the event 45% of the time, but the odds show that the Bulls would only need to win 20% of the time to break even, then your bet has value.
How to Create a Strategy
To grow into a master sports gambler, you should do data analysis. Aim to figure out which of the factors have strong influences on the results of the game. After identifying the variables, you must calculate separate probabilities for each possible result. The final step is to compare the suggested results set by the bookies, against your percentages of likelihood.
It’s only worth placing a wager on a bet if it has a positive number. It will only have a positive number when the possibility figures are a smaller percentage than the likelihood that you calculated. The data gathered through the testing methods gives you a clear insight into whether or not a team or a player is likely to deliver an expected outcome. If your research doesn’t establish the certainty of the desired result, then don’t bet on it.
Types of Statistical Testing
There are various models that you can use to test the stats and to choose the right team. We explore some of the ones used for sports betting.
The most common stats tests for sports betting is Regression Analysis. It’s a set of actions used to discover the connection between one or more independent factors and one dependent variable. The dependent variable in this case for sports wagering is a win. The independent factors can be any pieces of information gathered about the upcoming event.
It could include info such as the “percentage of completed passes”. This method can be useful to find factors that match up, like home ground advantage and winning. However, it can’t prove that the team’s wins are caused by playing on their home field.
Most often used for sports betting, this system works on the idea that numerous factors can influence the outcome of the game. You can’t just pick one and hope to get a good result. The analysis studies various pieces of past data to guess an outcome. The oddsmaker examines this information and makes an educated guess about an anticipated outcome. The bookie decides on the likelihood of whether a specific team has strengths and weaknesses for future games, by using the past games information.
Using this data, the oddsmaker sets the odds for any upcoming events. The road to successfully using this method is to get as much historical info as possible. Data for both the teams and the players is essential. You can use the data to start narrowing the focus to specific factors that could lead to predicting precise outcomes.
Regression Analysis - Logistic
This system works by going through data in which the result is based on some independent factors. It gives a solution to queries such as “Will the chances of my team winning change, for every extra goal made above the standard?”.
This type of data is what oddsmakers use to get the odds ratio, even though there are many factors to consider. The conclusion is the impact that the combination of factors has on the desired outcome.
These methods provide results about the likelihood of the occurrence of various possible outcomes. Instead of just solving for the most probable outcome, they show the likelihood of each possible result. Once the results are apparent, you can build graphic models to show the range of possibilities.
These networks are graphs and models that are useful in making predictions. It consists of levels that have factors that can alter the match’s outcome. If you’re trying to base a prediction on the strength of the team, for example, level one would be the values for historical variations, average goals per game and team performance.
At level two, you would consider the previously mentioned factors, and also take into account each team’s injuries. You use this information to forecast the two teams, based on the additional filter.
The final step is to look at other info, such as how recently the teams were last on the field and whether they’re tired and drained. You need to add this to the different levels to make up level three and make the final forecast with this information.
This method is the most useful for sports such as soccer, hockey or NBA prop bets. Anything in sports where you would monitor the numbers in divisions of ones and the scoring is relatively uncommon. It would be best if you convert the figures into a range of possible outcomes, which you can study to predict results. A good example would be to predict the most likely score of a basketball game.
There’s no easy path to winning at betting on sports. A planned and researched approach takes a lot of effort. However, if done correctly, it can mean the difference between winning big or not winning at all.