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What is Regression Analysis?

One of the toughest aspects of sports betting for a lot of punters is learning how to incorporate mathematics.  Mathematics is at the heart of any sound betting strategy since you need to be able to analyse statistics and trends in order to make smart predictions about the future.  Many different methods are available for accomplishing this task, but one of the most widely used mathematical approaches is known as regression analysis. 


What is regression analysis?  This is a mathematical technique which is used to establish the relative importance of different factors that are all playing into the outcome of a sporting event.  Sports betting is unusual in this sense when you consider it in comparison to traditional casino games, which all have fixed odds.  With sports, all kinds of different variables are constantly impacting the odds, and the big challenge is to try and come to some kind of an educated hypothesis about what is going on given all those constantly changing inputs. 


There are two main steps to regression analysis.  First, you need to do some data mining and come up with statistical information that you can process mathematically.  Then, you need to use a regression equation to make a determination about an event.  There are a number of different types of regression analysis, including logistic regression, multivariate linear regression and multiple regression analysis.  While it can be a challenge to learn this mathematics on your own, you may find software to help you out.  And if you do it by hand, with a little practice, you can become quite good at it.


Regression analysis is considered one of the most reliable mathematical approaches to interpreting sports statistics.  Does it have any weaknesses?  One problem with this type of analysis is that it is great for determining correlations, but it does not establish causation.  For example, you might discover that a certain player failing to score a goal is associated with that player’s team losing matches, but the analysis does not actually prove that the player’s failure is resulting in the team’s loss. 


The biggest challenge with regression analysis is not learning the math—again, this is just a matter of applying yourself.  The real challenge lies in deciding which variables you should measure and compare in the first place.  If you are able to come up with a reliable set of variables, though, you can build a really strong regression system.  Just keep in mind that over time as variables continue to shift, your system may need adjustment.


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