Model Notes
Buckeye Gridiron Predictions uses past results and matchup context to estimate a winner and margin. It is an analytics tool, not a guarantee or betting advice.
What This Is
The model looks at team performance, scoring margin, schedule strength, location, and recent context. It turns that information into one projected winner and one projected margin. Our strategy uses machine learning to learn team strength from historical game results, then adjust each projection with matchup-specific context before checking predictions against final scores.
How To Read A Projection
- Winner
- The team the model favors.
- Margin
- The estimated scoring difference.
- Confidence
- How clear the edge looks. Large projected margins earn higher confidence.
- Risk
- The most important reason the projection may be less steady.
When To Be Careful
- Close projected margins are naturally harder to separate.
- Upset Possible marks favorites with a real chance of losing outright.
- Blowout Possible games can swing well past the projected margin.
- A Models Disagree flag means our internal models are not fully aligned on the winner.
- Injuries, weather, and roster changes are only reflected when they show up in team results.
How We Check Ourselves
The Past Results page tracks how projections performed after final scores are available, including winner accuracy and margin error.