## Issue #2

STATISTICS

What is Statistical Independence?

We will define a fundamental property in statistics that greatly simplifies building and computing statistical models.

Mathematical Jargon

Two events A and B are independent if the occurrence of event B provides no new information on the probability of A occurring. This can be mathematically expressed as:

Probability of A and B = Probability of A x Probability of B

Example

If I flip two coins at the same time, the result of one coin does not affect the result of the other. Before doing the math, we first note that all possible combinations of throwing 2 coins is the following set {HH, HT, TH, TT} of size 4. So what is the probability of obtaining a Heads and Tails, and are these events independent? Let's check:

1. P(Coin 1 is Heads AND Coin 2 is Tails) = {HT} / {HH, HT, TH, TT} = 1/4 = 25%

2. P(Coin 1 is Heads) x P(Coin 2 is Tails) = 50% x 50% = 25%

Both equations #1 and #2 are equal, satisfying the definition of independence.

In Football Terms

One advantage of assuming independence is that it helps reduce the mathematical complexity of problems. When events are not independent, the dependence between events has to be calculated, and before you know it these calculations balloon.

Lets take the Poisson model you see in your typical Excel for football model. It involves multiplying the Poisson distribution of goals scored by Home Team by goals scored by Away team:

POI(Home Avg. Scored; Goals) x POI(Away Avg. Scored; Goals) Look familiar? That is the independence assumption in action! The correct score heatmap above is a 5x5 matrix = 25 different possibilities.

If we had not assumed independence between Home and Away goals, we would've to calculate 2 x 25 = 50 possibilities because the order in which events occur is relevant. As an example, the probability of Home Scored = 1 when Away Scored = 0 is not the same as probability Away Scored = 0 when Home Scored = 1. Under the independence assumption, this order is irrelevant, but whether we can make this assumption is a whole other story.

What's new?

You can find a newly customizable Poisson Regression model that takes as input your view on the difference between Shots On Target between Home and Away team. The odds are computed accordingly depending on the difference (+/-) in Shots On Target you think the match will end with. New Section coming soon...

A new section will open up shortly that will be very different to anything on the site. Make sure to follow my Twitter if you want to keep up with the latest updates.

 Like what you read? I'd like to hear your ideas and suggestions! Contributors are welcome! Email me at [email protected]