Clone from Numeristical's https://github.com/numeristical/resources/tree/master/BaseballPred

A repository to follow along with Andrew Trask's "Grokking Deep Learning" by modelling baseball statistics using various architectures of neural networks built from scratch.

Predicting MLB Games Using Bayesian Models

Research project for the Institute for Computing in Research

MLB sports betting model. WIP

"I'd walk through hell in a gasoline suit to play baseball." - Pete Rose (Charlie Hustle). Python scripts to pull MLB Gameday and stats data, build models, predict outcomes, make plays.

Machine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)

This data science project aims to develop a machine learning model to predict the outcomes of MMA fights, using historical data and betting odds

Python implementation of Shin's method for calculating implied probabilities from bookmaker odds

script for downloading bets from oddsportal.com

Python script to scrape Bet365 odds using Selenium.

Prebuilt Docker images with Retrosheet's complete baseball history data for many analytical frameworks. Includes Postgres, cstore_fdw, MySQL, SQLite, Clickhouse, Drill, Parquet, and CSV.