Sports betting analytics is about making informed decisions with data. Key metrics to track include win/loss records, ATS, over/under records, player statistics, and advanced metrics. Building a betting model involves gathering and cleaning data, choosing predictive variables, building and refining the model. Advanced strategies like Monte Carlo simulations, Bayesian inference, and machine learning algorithms can take your model to the next level. Avoid common pitfalls like overfitting and ignoring context. With effort, sports betting analytics can turn the tables on the bookies and lead to profits. Continue reading Sports Betting Analytics Guide: How to Turn Data into Dollars