March Madness Picks 2026
AI-powered bracket predictions for every NCAA Tournament game. Upset alerts, sleeper picks, and round-by-round best bets. Our model analyzes 350+ teams using KenPom-style efficiency ratings to find edges the market misses.
How We Rank Tournament Picks
Highest confidence picks. Multiple factors all pointing the same direction.
AI-detected upset opportunities. Lower seed with matchup advantages the market undervalues.
Dark horse plays. Mid-majors and Cinderellas with efficiency profiles that match past tournament runs.
Picks by Round
First Four + Round of 64. Most games, most upsets, most value.
Round of 32. Chalk starts to crack. Mid-majors prove it or go home.
Regional semifinals. Elite matchups where seeding matters less.
Regional finals. Four games decide the Final Four. Every point matters.
National semifinals. The best 4 teams in college basketball.
The title game. One game for the national championship.
What Our March Madness AI Does
Upset Detection
AI flags overseeded teams with weak efficiency metrics facing underseeded opponents with strong defensive profiles. 12-over-5 upsets happen 35% of the time — the model identifies which ones.
Bracket Optimizer
Round-by-round picks optimized for bracket pools. The AI balances chalk (safe picks) with calculated upsets to maximize bracket scoring potential.
Live Updates
Picks updated before each session as injury reports, lineup changes, and last-minute odds movement are factored into the model.
Every Game Covered
Win probabilities for all 63 tournament games from the First Four through the Championship. No game left unanalyzed.
KenPom-Style Efficiency
Adjusted offensive and defensive efficiency ratings normalized for strength of schedule. The most predictive metric in college basketball.
Public Transparency
Every prediction tracked publicly on our dashboard. Past tournament accuracy fully visible — wins and losses, no cherry-picking.
How AI Predicts March Madness
March Madness is the hardest event in sports to predict because single-elimination amplifies variance. One bad shooting half ends your season. But within that chaos, data patterns exist. Our AI identifies them.
The model starts with adjusted efficiency ratings for all 350+ Division I teams. Offensive efficiency (points per 100 possessions) and defensive efficiency (points allowed per 100 possessions) are the most predictive metrics in college basketball. We normalize these for strength of schedule so that a 25-5 record in a weak conference is properly compared to a 20-10 record in the Big 12 or SEC.
Tournament-specific factors add a layer that regular-season models miss. Coaching experience in March (coaches with 10+ tournament appearances outperform first-timers), team tempo (slow-paced defensive teams upset higher seeds more often), free throw shooting (games tighten in March and FT% becomes critical), and travel distance (teams playing close to home gain a measurable advantage).
The upset detection algorithm compares each lower seed's efficiency profile against historical upset data. When a 12-seed has the defensive efficiency, pace, and free throw shooting profile that matches past 12-over-5 upsets, the model flags it. Not every flagged upset hits, but the hit rate significantly outperforms chalk picking.
Every Tournament Game. 99¢. Lifetime.
First Four through the Championship. Bracket picks + best bets + upset alerts.
99¢ — One Payment, Forever Access (All 5 Sports)
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