Overview
Machine learning platform predicting sports match outcomes using historical data and live statistics, achieving 15% improvement over baseline models with sub-500ms latency.
The Problem
Sports betting and analytics lack real-time, data-driven insights. Traditional prediction models don't incorporate live match dynamics and player form changes.
The Solution
Built ensemble prediction engine combining gradient boosting, neural networks, and time-series models. Ingests live match data via APIs, updates predictions in real-time, and provides confidence intervals.
Results & Impact
68%
Prediction Accuracy
Match outcome (win/loss/draw)
+15%
Improvement
Over baseline models
<500ms
Latency
Live prediction update
3
Sports Covered
Cricket, Football, Basketball
Key Impact
- Processed 500+ matches with live predictions
- Used by sports analytics platform with 10K+ users
- Improved betting ROI by 12% for users
Technologies Used
PythonScikit-learnXGBoostLightGBMPandasFlaskRedisPostgreSQLReal-time APIs