Machine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)
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Updated
Feb 12, 2017 - Jupyter Notebook
Machine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)
SkillCorner Open Data with 9 matches of broadcast tracking data.
Repository which contains various scripts and work with various basketball statistics
An Implementation of the ANT+ Network on top of ant-arduino
An R package to quickly obtain clean and tidy college football play by play data
A Tennis dataset and models for event detection & commentary generation
Kaggle Competition for Predicting NCAA Basketball Tourney Games
Sport stats UI components
Python wrapper for the Sportradar APIs ⚽️🏈
Stattleship R Wrapper
Feature requests for the MySportsFeeds Sports Data API.
Based on NFL game data, we want to predict the success of a play. This can be used to insert different strategies before the play is called to determine the success probability.
A scraping and aggregating package using the CollegeFootballData API
R wrapper functions for the MySportsFeeds Sports Data API
An unofficial Python API wrapper for firstcycling.com
Stattleship API Ruby client
A college football recruiting package
A set of functions to visualize National Football League analysis in 'ggplot2'
Application for generating college football score and win probability predictions using neural networks
Python NHL API Wrapper 🏒🥅
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