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AI

NBA Predictor

Data-driven game predictions

ML model for game predictions with a Next.js dashboard and Recharts for accuracy and trend analysis. Python backend for training and inference.

Challenge

The client wanted to offer NBA game predictions backed by data, with a way to monitor model performance and explain results to stakeholders. They had historical data but no pipeline or interface to turn it into a product.

Solution

We built a Python pipeline for feature engineering and model training, an inference API for game-day predictions, and a Next.js dashboard with Recharts to track accuracy, compare to baselines, and visualize trends over time.

Results

  • Stable prediction pipeline from raw stats to daily outputs
  • Dashboard for accuracy, drift, and trend analysis
  • Clear metrics so non-technical stakeholders can follow performance
“We had the data; Saints turned it into something we could ship and improve on.”

Tech

PythonNext.jsRecharts