Abstract

The Indian Premier League is the most prestigious cricket league globally. There are significant finances in terms of both team ownership and player salaries. It is, therefore, essential to understanding if a team’s record is due to luck (good or bad) or if a team’s record is due to the team’s overall performance. The research presented here is motivated by how to accurately predict a team’s winning percentage in the Indian Premier League based on underlying statistics. A similar analysis has been done in other sports, mainly based on the concept of the Pythagorean expectation. This research derives a similar model for the IPL based on historical data. However, the structure of a match in the Indian Premier League is fundamentally different than the structure of games in other sports. As a result of this structural difference, this study creates additional models using both least absolute shrinkage and selection operator and stepwise regression to identify variables that are good predictors for calculating the expected winning percentage. These models compare favorably to the Pythagorean expectation model. This article presents a model combining both the determined variables and Pythagorean expectation.

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