Cricket Performance Forecasting: The SARIMA Approach

Sports Analytics and Data Science

Predicting individual player performances in high-stakes matches, such as the ICC World Cup, requires analyzing vast historical datasets of player statistics, pitch conditions, and team dynamics.

Time Series in Sports

In the ‘Sledge Hack: Ind vs Aus Cricket Hackathon’, I utilized Seasonal Autoregressive Integrated Moving Average (SARIMA) models to predict runs scored and wickets taken. The ensemble SARIMA techniques captured the inherent variance in player form.

Championship Results

The model secured the 1st Rank globally out of 1073 participants. This proves that rigorous data science and time-series methodologies can uncover predictable patterns even in highly dynamic sports environments.