nba sports betting machine learning

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Quick description about nba sports betting machine learning:

NBA-Machine-Learning-Sports-Betting is an open-source Python project that applies machine learning techniques to predict outcomes of National Basketball Association games for analytical and betting-related research. The system gathers historical team statistics and game data spanning multiple seasons, beginning with the 2007–2008 NBA season and continuing through the present. Using this dataset, the project constructs matchup features that represent team performance trends and contextual information about each game. Machine learning models are then trained to estimate the probability that a team will win a game as well as whether the total score will fall above or below the sportsbook’s predicted total. In addition to predicting outcomes, the project evaluates expected value to determine whether a potential bet offers a statistical advantage compared with sportsbook odds.

Features:

• Machine learning models predicting NBA game winners and totals
• Historical dataset covering NBA seasons from 2007 onward
• Feature engineering for team statistics and matchup comparisons
• Expected value calculation based on sportsbook odds
• Optional Kelly Criterion betting stake sizing
• Python implementation for data analysis and predictive modeling

Programming Language: Python.
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