SharpModels explores how modern machine learning and statistical frameworks can measure and forecast team and player performance across the NFL, NBA, MLB, NHL, and college football and basketball.
Created by Sharp Intelligence, built on over 25 years of experience in quantitative sports modeling and applied data analytics.
25+ years · millions of events analyzed · 6 major US leagues
Ratings are scaled around 1500, representing team strength adjusted for opponent, schedule, and recent performance.
Switch leagues below.
Explore how statistical and machine learning methods estimate probabilities, build rating systems, and forecast sporting outcomes through open examples that show how real models begin.
See how structured data, validation, and performance metrics reveal meaningful patterns and guide model development.
We show how models are built and validated from the ground up, focusing on understanding and methodology rather than complete production systems.
SharpModels is an educational and analytical project by Sharp Intelligence Ltd, created to make the process of sports modeling more open and understandable.
It focuses on how data, statistics, and machine learning methods can be applied to quantify performance, test predictive accuracy, and build transparent models that explain sporting outcomes.