Football Predictions Expert-football predictions and insights

Example

Comparing initial and live odds from multiple bookmakers to assess value bets.

Scenario

A user wants to determine if there is a significant shift in odds for a match between FC Barcelona and Real Madrid. By comparing the initial and live odds, the tool can identify potential value in betting on a specific outcome, such as a draw if the odds for a draw have improved significantly.

Example

Using Bayes' theorem to update the probability of a team winning based on new data.

Scenario

Before a match, the tool uses historical performance data and Bayesian analysis to predict the likelihood of Manchester United winning against Chelsea. As new information, like injuries or changes in team form, becomes available, the tool updates the probabilities to provide an accurate prediction.

Example

Estimating the total number of goals in a match using Poisson distribution.

Scenario

For a Bundesliga match between Bayern Munich and Borussia Dortmund, the tool uses Poisson distribution to calculate the expected number of goals. This helps in predicting over/under bets, indicating whether betting on over 2.5 goals is statistically favorable.