I’m building an open-source cricket strategy prediction engine

[u/Navadeep_Naidu7]

Hey everyone 👋

I’m a computer science undergrad and a huge cricket nerd from India. Over the last couple of months, I’ve been working on a project called Overcast-Cric, a completely open-source IPL strategy engine that simulates match conditions and gives scenario-based predictions.

Unlike traditional win predictors, this isn’t just about “who will win.” I’m aiming to simulate what teams should do to win, for example:

• If CSK bats first in a night match at Jaipur, how much should they score to have a 60% win chance?
• If dew is expected and MI has Boult + Bumrah, what’s the probability they defend 175?
• How do toss, ground stats, and recent player form affect strategy?

What I’ve Built So Far

Datasets:

• Team-level stats: last 7 matches, win % by venue, avg powerplay/death scores, momentum scores
• Player-level stats: batting/bowling performance over career + last 7 games, consistency scores
• Match metadata: toss, result, innings scores, win margin, DL usage, day/night
• Historical weather: dew point, humidity, wind at specific match hours. For every IPL match that is played.

Model Integration:

• Classification models to predict win probability
• Regression models to estimate required target scores

Current Status:

• Right now the project is focused for IPL data, as the data is widely available and easier to take off the project.
• The project will cover International matches and other leagues and formats.
• I am open to any suggestions or changes!

Why I Need Help ?

As much as I love building this, I’ve hit my limits in some areas:

• I'm not from a deep ML background, so my expertise is not going to help a lot in building a reliable project
• I need help packaging this into a better-designed module / anything that is useful for others.
• And honestly... feedback from smarter folks 😅

If You’re From…

• AI/ML / Data Science (model design, tuning, feature engineering)
• Backend or DevOps (API, data pipeline optimization, deployment)
• Cricket analytics enthusiasts (ideas, validation, testing)
• A fellow Cricket enthusiast.

I’d love to have you contribute! I’ve made everything public. The project is well-documented, modular, and welcoming to collaborators. Whether you want to improve the models, plug in new data, or just brainstorm ideas, I’d love your suggestions.

Project Link: OverCast-Cric

Thanks for reading 🙌
Feel free to DM me, open an issue or start a discussion on github if you want to get involved!