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
A Tennis dataset and models for event detection & commentary generation
An R package to quickly obtain clean and tidy college football play by play data
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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