NCAAB Edge Finder
An efficiency model spread against the line the most books offer. The board is not live yet.
Coming soon
The NCAAB board is not live yet. The model below is built and documented, and it will be published once we can show what it has actually done rather than what it projects.
How it works, the formula and the FAQ are below.
View all NCAAB matchups →How the Edge Finder Works
The Formula
Every team has a scoring margin: points scored per game minus points allowed. A team scoring 80 and allowing 70 has a margin of +10. The gap between two teams' margins, multiplied by 0.68, gives the model's spread on a neutral site.
The 0.68 factor is a fixed scale the model applies to that gap. It is taken from efficiency ratings counted per 100 possessions (a college basketball game has about 68), while the margins here are counted per game.
// Edge Finder formula
homeNet = homePPG - homeOppPPG
awayNet = awayPPG - awayOppPPG
neutral = (homeNet - awayNet) x 0.68
model = neutral + 3.5 pts (home)
// gap = model + marketSpread
Finding Value
Sportsbooks use efficiency data when setting lines, which means gaps are usually small. But inefficiencies appear when injuries create uncertainty, when public money pushes lines, or when a team efficiency is trending faster than the market adjusts.
The strongest signal is a gap of 2.5 points or more that the line has not moved toward yet. Bet early: lines adjust quickly as public money moves in.
Strong edge (2.5+ pts)
Significant model-market disagreement. Worth analyzing with full pick context.
Moderate edge (1 to 2.5 pts)
Monitor alongside other signals, especially line movement
Efficient market (under 1 pt)
Model and market agree. No efficiency-based edge identified.
Efficiency Ratings and NCAAB Betting
Advanced efficiency metrics transformed how serious bettors approach college basketball. Raw win-loss records miss context. A team beating bad opponents looks identical to one beating ranked opponents. Efficiency ratings normalize for pace and opponent strength, measuring points per possession rather than points per game.
Ken Pomeroy popularized this approach with his adjusted efficiency ratings, which account for tempo and strength of schedule in greater detail. The GODDS Edge Finder uses a much simpler measure: season-long points scored and allowed per game, with no adjustment for tempo or opponents, turned into a spread by the formula above (scoring margin gap x 0.68 + home advantage). It has not yet been shown to predict covers.
Sportsbooks have incorporated efficiency data into their lines for years. This means the market spread is rarely far from what efficiency models project. The opportunities are in the gaps: when public betting pressure moves a line away from its efficiency anchor, when injury news creates uncertainty that has not fully priced in, or when a team efficiency is trending in a direction the market has not yet acknowledged.
Once its board is live, the GODDS Edge Finder will do this daily. Instead of manually calculating gaps for every game, the tool highlights the games where model and market disagree most, layers in the GODDS AI pick, and shows the price at the market line across 8 offshore sportsbooks. The goal is a single page that gives you everything you need to make an informed decision, or to quickly confirm that a game has no edge worth pursuing.