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NCAAB Predictions & Picks

College Basketball • Model Predictions for every game • Picks

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> Our college basketball prediction model outputs moneyline lean, spread cover probability, and over/under direction for D1 games every day of the season. Three model versions run in parallel -- V1 broadest, V3 tightest -- and all three have been in the 69-72% ML range every season since 2020. With hundreds of games on the board nightly, this model works primarily as a filter: surfacing which matchups have the clearest implied probability gap worth researching. Full season records are on the historical records page.

NFL 2025-26 Season Complete

47-38 | +100.5u

vs last season: +55.3u improvement ↑

Season begins October 2026

CFL 2025-26 Season Complete

47-38 | +100.5u

vs last season: +55.3u improvement ↑

Season begins October 2026

Today's Games • Apr 18

No games schedule today

Model 2 & 3 Predictions are for Premium Members -- unlock all models for $10/month

MODEL PERFORMANCE

TEAM PERFORMANCE

Season: 12-8 | +4.50u

Today's Picks • Apr 17

No picks posted yet for today

Last night: 1-0 | +0.91u

No results yet

LAST NIGHT: 1-3 • -2.17u

BETTING RECORD

1-3 | -2.17u

TEAM PICKS RECORDS

Updated Apr 10, 9:00 AM

Navigating 300+ Games A Night

The hardest part of betting college basketball isn't finding information -- it's knowing which games to care about. On any given weeknight during conference play, the model flags the matchups where tonight's line diverges most from historical expectation. Not all of those are actionable bets. But narrowing a 300-game slate to a focused shortlist is most of the work, and that's what these outputs do.

 

V1 ML has been between 69.6% and 72.5% in every season since 2020. V2 and V3 run slightly tighter selections with consistent results across the same period.

Model Output vs. Curated Picks

The NCAAB Picks page shows which games from this table cleared the full filter process -- strong model signal, supported by matchup context and an actionable line. Both views are published so you can use the model on your own or follow the curated selection. If you disagree with a pick, the predictions table shows you exactly why it was in consideration.

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