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

Predicts Daily NBA Games Using a Logistic Regression Model

Predict scores of NBA games using regularized matrix completion

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.

Using data analytics and machine learning to create a comprehensive and profitable system for predicting the outcomes of NBA games.

Reworked NBA Predictions (in Python)

NBA game prediction model

Using decision tree and random forest models, predict the winner of an NBA regular season game

Using AI to predict the outcomes of NBA games.

Analysis of NBA player stats and salaries of the 2016-17 for the 17-18 season

🏀 predicting the NBA mvp (3/3 so far)

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.

finding patterns in up down sequences

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.

🔮 Predicting NBA games using statistics (65% accuracy so far)

NBA games' prediction

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

A wrapper site for NNNBA