AI-driven Betting Predictions for NHL, NBA and MLB Sports Events

Case

AI-driven Betting Predictions for NHL, NBA and MLB Sports Events

Nowadays, a betting company need as quickly as possible process a large number of analytical reports and various sport statistics to set its betting line. More accurate and rapid predictions of game results is one of the key competences that has a significant impact on business margins.

Problem

It is essential for a betting company to set betting lines in the most precise way possible and change them promptly before the event starts.
It is possible thanks to hard and time-consuming work:
– Thorough analysis of the event plus reports from the experts.
– Calculating the betting margin.
– Essential comparison of a company’s betting odds with other companies’ odds.
– Avoiding situations when all gamblers bet on the same team and, as a result, having profitable odds for both sides.
– Finding out possible favourites and underdogs, controlling changes in the situation and setting new odds if necessary
This process requires the utmost automation to improve the speed and accuracy of calculations and to reduce risks of human error.

Solution

An AI module based on neural networks gets integrated into a betting company’s backend. The module analyses historical and current statistical data and calculates the probability of possible outcomes for sports events.

How it works

The trained AI module integrated into a betting company’s backend calculates betting odds using a large database:
– line-ups (starting line-ups and bench players);
– each team’s motivation;
– the list of players’ injuries and sending-offs;
– statistics of head-to-head meetings;
– event’s location (a home or an away game);
– referees (a strict or lenient referee can significantly influence the outcome);
– weather conditions (bad weather makes it difficult to expect high performance);
– general statistics for several years, which are daily updated;
– coaches (experienced coaches are more valued);
– news feed (sensational news about players and others involved);
– inside information (even such things as divorce or the loss of a loved one can affect a player’s performance);
– the season’s statistics, etc.

Benefits

Improvement of betting odds accuracy by up to 20%;
Reducing the cost of sports events analytics, also known as cappers;
Minimization of risks due to reduction of subjective human factor;

As a result, increased profits.

Technology stack

  • Python
  • Sklearn
  • Tensorflow
  • Keras
  • Pytorch
  • Lightgbm