DeepShot
NBA game predictor using rolling averages & ML
What it does
DeepShot is a machine learning model designed to predict NBA game outcomes using advanced team statistics and rolling averages. It combines historical performance trends with contextual game data to deliver highly accurate win predictions (66.45%)
Does a similar job
all alternatives →- IMI made a machine learning model to predict 66.45% of NBA games2025 · github.com · ▲17
Introducing DeepShot: An NBA Game Prediction Model Hey devs, sports fans, and data nerds! After weeks of work, I'm excited to share DeepShot – an advanced NBA game predictor powered by historical data from Basketball Reference, machine learning, and a clean NiceGUI-powered web interface. What it does: DeepShot uses team-level rolling averages (including Exponentially Weighted Moving Averages) and an Elo rating system to accurately predict NBA game outcomes. All predictions are visualized in real time through a sleek, responsive UI. Key Features: Data-Driven Predictions using past performance…
- DNDeepShot – NBA game predictor with 71% accuracy using ML and stats2025 · github.com · ▲5
Hey everyone, I’m an NBA fan and Python dev, and I recently built DeepShot — a machine learning model that predicts NBA game outcomes with about 71% accuracy based on historical stats and rolling performance metrics (EWMA). It features: Real NBA data from Basketball Reference Exponentially Weighted Moving Averages to track momentum Interactive NiceGUI interface with team comparison and predictions Full Python stack and open-source (MIT license) Here’s the GitHub repo: https://github.com/saccofrancesco/deepshot And if you like it, here’s my Buy Me a Coffee:…
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