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# Predict the Next NCAA Champion With Minitab Solution Center
[Cheryl Pammer](https://blog.minitab.com/en/blog/author/cheryl-pammer) | 11/13/2025
Topics: [Predictive Analytics](https://blog.minitab.com/en/blog/tag/predictive-analytics), [AI](https://blog.minitab.com/en/blog/tag/ai), [Minitab Solution Center](https://blog.minitab.com/en/blog/tag/minitab-solution-center)
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Can data really predict who’ll take home the NCAA trophy before the season’s even over?
Spoiler: it can—and it does.
## Why It Matters
In State College, Pennsylvania, the home of Minitab headquarters and Penn State University, fall means one thing: football.
As the air cools and the playoff race heats up, it’s the perfect time to crunch some numbers and see which team’s performance won’t “turn over” when it matters most.
## Finding the Right Data
To predict the 2025 national champion, I pulled data from [**sports-reference.com**](https://www.sports-reference.com/cfb/), a treasure trove of stats going all the way back to 1869 (yes, really!) when Princeton ruled the gridiron. But college football has changed—drastically. So instead of digging through dusty history, I focused on the College Football Playoff (CFP) era, which began in 2014.
**Fun fact:** Since 2014, *every national champion has been ranked no lower than #5 in the final November AP Poll.*
Translation: by November, the true contenders are already in view.
That insight led me to focus only on Top 10 teams, trimming the noise from the non-contenders.
## Modeling the X’s and Y’s
My mission: predict the probability that each Top 10 team will win it all. Using classification models like Logistic Regression, Random Forests, and TreeNet, I trained Minitab to think like a football coach—with a spreadsheet.
Here’s what went into the model:
- **OSRS & DSRS:** Offensive and Defensive Simple Rating Systems—efficiency adjusted for schedule difficulty.
- **Scoring Offense & Defense:** Points for and against.
- **Passing & Rushing Efficiency:** Balance and adaptability on both sides of the ball.
- **Total Offense & Defense:** Yardage-based performance.
- **SRS:** Overall strength combining offense and defense.
- **Win–Loss Record:** The ultimate measure of consistency.
**In short:** everything that separates champions from teams that just look good in September.
## Prepping the Data
I exported stats from 2014–2024 and sent them through the [**Minitab Data Center**](https://blog.minitab.com/en/blog/streamlined-data-management-with-the-data-center-in-the-minitab-solution-center?hsLang=en) for cleaning and prep. With [Minitab AI](https://www.minitab.com/en-us/products/minitab-solution-center/#tabs-15b44edbeb-gqj7eirkjk-tab-3) allowing much of the clean-up to be done through natural language plus the ability to save and automate repetitive steps, what used to take hours now runs like a well-oiled offense.
Because let’s be honest—no one wants to clean up 10 years of football data by hand.
## Building the Model
Once the data was ready, I stacked it in **Minitab Statistical Software** and used: **Automated Machine Learning > Discover Best Model (Binary Response)**
That’s Minitab’s Predictive Analytics solution for quickly testing multiple models and identifying the one that scores best.
The winner? [**Random Forest.**](https://www.minitab.com/en-us/solutions/analytics/statistical-analysis-predictive-analytics/random-forests/)It delivered the most accurate predictions for “Winner” vs. “Loser.”
## Key Insights
The Random Forest model uncovered the four biggest predictors of championship success:
1. **Win–Loss Record**
2. **Defensive Strength (DSRS)**
3. **Overall Strength (SRS)**
4. **Scoring Defense**
**Takeaway:** Defense still wins championships—confirmed by data, not just coaches.
## 2025 Predictions
**Drum roll, please…**
Using 2025 midseason stats for the Top 10 teams, I calculated each team’s probability of winning the title and standardized the results so they total to 100%.
As of **November 12th, 2025**, the model predicts:
**Ohio State** and **Indiana** have the best shot at the national title. Things are looking good for the Big Ten. Sorry, Georgia—this might not be your year.
## Visualizing the Race
To make the results easier to follow, I built an interactive [**Minitab Dashboard**](https://blog.minitab.com/en/blog/from-data-to-decisions-with-minitab-dashboards?hsLang=en).
With **Minitab AI**, it’s as simple as connecting your data source—charts, tables, and model results automatically combine into one dynamic view. It’s like your own version of *ESPN’s College GameDay*—minus the mascot heads.
Because the dashboard updates automatically as new data comes in, you can instantly see which teams are trending up or falling behind. It’s a real-time, data-driven way to follow the championship race.
## What the Data Says
- **Defense still wins championships.** It’s the strongest differentiator between champions and contenders.
- **Efficiency drives success.** Balance wins games—and titles.
- **Consistency counts.** Teams with multiple losses rarely lift the trophy.
- **Offense helps—but defense defines greatness.**
- **Data beats gut instinct.** Minitab’s Predictive Analytics module distills chaos into clarity.
**In short:** stop guessing. Start modeling.
## Final Thoughts
This analysis proves what football fans already know: championships aren’t decided by hype or headlines.
**Defense, discipline, and data win championships—on the field and in business.**
### Want to Uncover Your Own Data Story? Let’s Model It Together With Minitab [](https://blog.minitab.com/hs/cta/wi/redirect?encryptedPayload=AVxigLKR5Qr1VMqpnG6R1%2Fzr%2FhS%2FuiG4Vjq6lyfFhMb1NgpdFzVdylexjA7TnWMchHR7OhsesPOGy%2FBhB4HndfsHk45rdLxgEIlxptHEK49HGtvvMKHiSc8mikOB1C9doo%2FbOzH75GHo6k%2FVum1NdT4BTwCYGAxzacab0W%2Bndeed%2FAHYx5WuHzI%2B1DOXoP1UnRRnxbc%3D&webInteractiveContentId=199214245666&portalId=3447555&hsLang=en)
*The author, Cheryl Pammer, with her children at the 2019 National Championship game. *
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