OddsLine Blog
Insights on predictive modeling and AI in sports betting. How the model, the market, and the assistant actually work.
Elo for Sports Predictions: What It's Good For and How to Use It
Elo is one of the simplest models in sports analytics, and one of the most powerful. But it only delivers if you know what it's for and how it has to be run. If you bet on or analyse sports without understanding it, you're passing up a tool that has held up for decades. This post covers what Elo is good at, why "an Elo rating" can mean very different things depending on who runs it, and how we built ours at OddsLine.
EV Scanning Isn't the Edge You Think It Is
OddsJam's roughly $160m acquisition in 2024 says a lot about where EV scanning sits in sports betting today. The method is simple in principle: treat a sharp book's odds as the closest thing to a fair probability, then scan retail books for lines that lag behind it. It's become the default definition of "value betting" for a generation of bettors, and the services built around it have done well commercially. But commercial success and a sound strategy aren't the same thing — if pricing a bet against one bookmaker's odds were really enough to generate consistent profit, it would be one of the easiest edges in the market to run at scale.
Why Most AI Betting Tools Fail (and How to Actually Use AI for Betting)
Every week, another self-styled "AI betting guru" promises guaranteed wins. Here's what they won't tell you: the hype has raced ahead of the substance. AI-branded betting services and pick promotions have become something of a trend in sports betting, yet reliable information on where AI actually helps is scarce, drowned out by overselling. This article sets out to cut through that noise and lay out, concretely, the genuine ways AI can be useful in sports betting, and what its real role should actually be.