Recent Articles
In-depth analysis, analytics strategies, and platform updates from the ATSwins team.
How to Compare MLB Projections to Prop Lines
Learn how to compare MLB player projections with prop lines using probabilities, fair prices, matchup data, variance, and model uncertainty.
Building a Machine Learning MLB Player Prop Model
Learn how machine learning models project MLB player props by analyzing matchups, park factors, and historical data to find value.
How to Calculate Edge on MLB Player Props
Learn how to calculate edge on MLB player props using projected probability, implied odds, fair lines, expected value, and no-vig market pricing.
MLB Player Prop Probability vs Odds: How to Compare Them
Learn how to compare MLB player prop probability with implied odds, calculate fair prices, account for vig, and evaluate model-based prop value.
MLB Strikeout Projection vs Sportsbook Line: How to Spot Real Edge
Compare MLB strikeout projections against sportsbook lines using pitch-level metrics, lineup splits, game contexts, and probability modeling to find edge.
MLB Player Prop Value Finder Guide | How Data Models Spot Edge
Learn how an MLB player prop value finder uses predictive models, simulation data, and probability math to find mispriced baseball lines every day.
MLB Player Prop Edge Finder: How to Identify Value in Baseball Player Props
An MLB player prop edge finder compares player projections with market lines and prices to identify potential value. This guide explains how ATSwins evaluates player skill, expected opportunity, matchups, park and weather conditions, probability distributions, and market pricing to uncover meaningful prop edges beyond simple recent trends.
High Confidence MLB Player Prop Projections: How Data Models Find Real Betting Edges
High-confidence MLB player prop projections go beyond recent stats by combining player skill, expected opportunity, matchup data, lineup context, ballpark conditions, weather, workload, and probability modeling. This guide explains how ATSwins evaluates uncertainty, fair probabilities, market prices, and value to build more disciplined, data-driven MLB player prop projections.
MLB Player Prop Market Inefficiencies: How Data Finds Value
Learn how MLB player prop market inefficiencies happen and how advanced AI models, pitch data, and weather metrics find true fair value lines.