Recently built a small project where I used a Monte Carlo simulation approach to model and predict IPL 2026 match outcomes. Wanted to share it with this community and get feedback from people who are much more experienced in sports analytics.

GitHub repo: IPL Monte Carlo Simulation Project

🔍 What the project does

• Simulates IPL matches using probabilistic outcomes based on team performance inputs
• Runs 50K simulations per match to estimate win probabilities
• Aggregates results to generate season-level insights like standings and playoff chances

📊 Approach

I’ve tried to model matches using a Monte Carlo framework where:

• Each team has a strength rating
• Match outcomes are probabilistic rather than deterministic
• Repeated simulations give distribution-based predictions instead of single-point forecasts

🤔 What I’m looking for

I’d really appreciate feedback on:

• How realistic the modeling assumptions are
• Ways to improve the team strength estimation
• Better data sources or features I could incorporate (player-level stats, ball-by-ball data, etc.)
• Any suggestions to make the simulation more 'cricket-realistic'

Below are the likely prediction for each team:

https://preview.redd.it/n9g3fsiehu0h1.png?width=1021&format=png&auto=webp&s=cd10f0f41877fb40983f280e93766517b619b7b8

This is still a learning project, so any criticism, suggestions, or ideas are very welcome.

Thanks in advance.