There are 17 repositories under nba-prediction topic.
NBA sports betting using machine learning
Scraping statistics, predicting NBA player performance with neural networks and boosting algorithms, and optimising lineups for Draft Kings with genetic algorithm
A project to deploy an online app that predicts the win probability for each NBA game every day. Demonstrates end-to-end Machine Learning deployment.
Predict scores of NBA games using regularized matrix completion
Using data analytics and machine learning to create a comprehensive and profitable system for predicting the outcomes of NBA games.
Predicts Daily NBA Games Using a Logistic Regression Model
🏀 predicting the NBA mvp (3/3 so far)
NBA game prediction model
NBA games' prediction
Use of Machine Learning tools with Python to observe the patterns in the logic of the MVP choice, verifying which are the most important statistics in this award.
Using decision tree and random forest models, predict the winner of an NBA regular season game
The NBA-Predictions Project uses Machine Learning to predict the score of NBA-games and the performance of individual players.
🔮 Predicting NBA games using statistics (65% accuracy so far)
This simple program predicts the result of an NBA match. Uses Monte-Carlo simulation to give the probability of each team winning the matchup.
finding patterns in up down sequences
Jupyter notebook that outlines the process of creating a machine learning predictive model. Predicts the peak "Wins Shared" by the current draft prospects based on numerous features such as college stats, projected draft pick, physical profile and age. I try out multiple models and pick the best performing one for the data from my judgement.
NBA players individual performance perdictions using Neural Networks. Comparison between LSTM and Feed Forward Architectures. Created by Meitar Bach, Mai Elenberg and Lior Ben-Ami
Predicting the outcome of shots based on the events and tracking data available for the 2015/16 season.
Predicting NBA results with Machine Learning models.
Predict the best lineup combination for each NBA team based on player clusters and and historical 5-man lineup performance.
Predicting the NBA outcome using a set of ML classification models
python program that lets you make two teams of any combination of current players and predicts the outcome based on latest stats. Uses BeautifulSoup and pandas libraries.
A comparative study of various models for prediction of Win/Loss of a basketball game based on the team’s as well as players’ past statistics. Also focused on the web scraping techniques to scrap raw datasets from the nba/stats website and feature engineering on the collected datasets to best suit the classification problem.
FanaticFi, empowered by machine learning, is a new financial investment platform where investors make payments to collegiate athletes to enable them with optimal training, diet, and equipment. While these elite athletes enter drafts and sign their contracts, investors will benefit under a predetermined investment return rate.
Estimating player value based on Win Share and Salary data
A wrapper site for NNNBA
The analysis of NBA Finals statistics which are likely to lead a Home Team to Win.
The code used for my year 11 Specialist Maths assignment
Python scripts that can be used to identify outstanding players for a given season as well as predict the output of a game given two teams
Work in-progress NBA Game Predictor using Spark