2025-26 College Basketball Season | 2026 College Football Season
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Machine Learning Analytics

Sports Predictions Built on Advanced Machine Learning

Every team carries a power rating fit on point margins across the season, anchored to a preseason projection and pulled toward its own results as the evidence accumulates.

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Football model still warming up. Not enough of this season's games have been played yet, so ratings are still leaning on preseason projections and last season's results.

How Last Week's Recommended Games Finished

2026-09-07 4.8 pt edge
SMU 27
Florida State 24
ML × Spread ×
We projected Florida State by 2.3 · 58%
Final SMU by 3
Vegas line SMU -2.5
We recommended Florida State Yellow
How it finished Moneyline lost Spread loss
2026-09-06 6.1 pt edge
Central Michigan 7
New Mexico 38
ML ✓ Spread ✓
We projected New Mexico by 16.6 · 92%
Final New Mexico by 31
Vegas line New Mexico -10.5
We recommended New Mexico Green
How it finished Moneyline won Spread win
2026-09-06 3.4 pt edge
Wisconsin 13
Notre Dame 41
ML ✓ Spread ✓
We projected Notre Dame by 23.9 · 97%
Final Notre Dame by 28
Vegas line Notre Dame -20.5
We recommended Notre Dame Yellow
How it finished Moneyline won Spread win
2026-09-06 3.7 pt edge
Washington State 10
Washington 24
ML ✓ Spread ✓
We projected Washington by 19.8 · 94%
Final Washington by 14
Vegas line Washington -23.5
We recommended Washington State Yellow
How it finished Moneyline won Spread win
2026-09-05 9.2 pt edge
East Carolina 10
Alabama 48
ML ✓ Spread ×
We projected Alabama by 19.3 · 94%
Final Alabama by 38
Vegas line Alabama -28.5
We recommended East Carolina Green
How it finished Moneyline won Spread loss
2026-09-05 3.4 pt edge
Boston College 15
Cincinnati 34
ML ✓ Spread ✓
We projected Cincinnati by 10.9 · 83%
Final Cincinnati by 19
Vegas line Cincinnati -7.5
We recommended Cincinnati Yellow
How it finished Moneyline won Spread win
2026-09-05 5.4 pt edge
North Texas 16
Indiana 52
ML ✓ Spread ✓
We projected Indiana by 35.1 · 99%
Final Indiana by 36
Vegas line Indiana -40.5
We recommended North Texas Green
How it finished Moneyline won Spread win
2026-09-05 6.3 pt edge
Northern Illinois 0
Iowa 40
ML ✓ Spread ✓
We projected Iowa by 37.8 · 100%
Final Iowa by 40
Vegas line Iowa -31.5
We recommended Iowa Green
How it finished Moneyline won Spread win
2026-09-05 10.5 pt edge
Liberty 13
James Madison 20
ML ✓ Spread ✓
We projected James Madison by 17.1 · 92%
Final James Madison by 7
Vegas line James Madison -6.5
We recommended James Madison Green
How it finished Moneyline won Spread win
2026-09-05 3.2 pt edge
Clemson 10
LSU 51
ML ✓ Spread ×
We projected LSU by 7.2 · 74%
Final LSU by 41
Vegas line LSU -10.5
We recommended Clemson Yellow
How it finished Moneyline won Spread loss
2026-09-05 8.4 pt edge
Arkansas State 24
Memphis 42
ML ✓ Spread ✓
We projected Memphis by 16.9 · 92%
Final Memphis by 18
Vegas line Memphis -8.5
We recommended Memphis Green
How it finished Moneyline won Spread win
2026-09-05 3.6 pt edge
Toledo 20
Michigan State 30
ML ✓ Spread –
We projected Michigan State by 6.5 · 72%
Final Michigan State by 10
Vegas line Michigan State -10.0
We recommended Toledo Yellow
How it finished Moneyline won Spread push

Today's Featured Pick

Free Preview
High Value
Arkansas
vs
Georgia
Football
Model Spread Georgia -28.1
Vegas Line Georgia -17.5
Edge +10.6
Win % 98.2%

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Daily Predictions

Machine learning powered predictions with proven edge detection

Today, 7:00 PM ET High Edge
Duke vs UNC
Today, 9:00 PM ET Med Edge
Kansas vs Baylor

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Power Rankings

# Team Rating
1 Indiana 38.8
2 Notre Dame 36.9
3 Georgia 36.8
4 Ohio State 36.7
5 Miami 36.7
6 Texas A&M 33.7
7 Texas 32.6
8 Alabama 32.1
9 Utah 32.0
10 LSU 30.4
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How Our Model Works

Advanced machine learning trained on thousands of games

1. Data Collection

We analyze 2,000+ games worth of comprehensive statistics and game outcomes. We include offensive efficiency, defensive ratings, turnover ratios, and advanced metrics for every FBS or D1 team.

2. Machine Learning

Our regression model weighs dozens of factors to calculate team strength ratings. The algorithm learns optimal weights from historical performance to maximize prediction accuracy. These weights learn from every game that is played.

3. Prediction Generation

For each matchup, the model considers team ratings, statistical differentials, home court advantage, and neutral site factors to predict the margin and win probability. The model outputs the predicted winner, point margin along with the edge versus the vegas line

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