If you like to bet on sports matches and look for matches with a lot of statistical information, surely you would like basketball as a sport a lot. For almost every basketball match we can find tons of statistics that can be used for our betting projects. Another benefit is that there are so many matches that they allow speedy testing of different betting strategies.

Basketball has one more advantage, which is unlike football, the chance does not play much of a role. For example, in a soccer match, a random ricochet may be fatal for one of the teams, but in basketball with nearly 100 points scored, the chance is not that influential. This fact also makes the various strategies for football statistical betting predictions (you can find such on sites like 24-bet.com) less successful than those for basketball.

One of the most fashionable ways for making statistical betting predictions for basketball matches is by using the so-called Poisson distribution. More about this statistical method can be found in Wikipedia at https://en.wikipedia.org/wiki/Poisson_distribution. Briefly explained through this mathematical method, when we have the average success rate statistics for a given metric, we can easily get a real chance for a result to happen.

How can we do that for basketball? There are many variants, but here is one.

We take the last 10 matches between two basketball teams that are going to play together, just picking up the matches played in the home team’s room. From these we collect the average number of points scored by both teams in these meetings. We take out the best and the lowest score for each of the teams, so we do not have any peak distortions, and from the other 8 scores we take the average number of points scored and allowed.

When we have this data, we use the Poisson distribution formula to check that each team can score all possible points. For example – less than 60, exactly 61, exactly 62, exactly 63 and so on until we reach the upper limit. Then we sum the probability percentages for all potentially possible outcomes and we can get a final estimate of what chances each team has to win the match and what are the chances to score more or less points than the bookmakers offer for Under Over for that match.