About

What Is College Golf Data?

College Golf Data is a data platform for NCAA college golf, built by two people who believe the sport deserves better tools and deeper coverage. The vision is something like what d1baseball.com built for college baseball - a genuine home for data, analysis, and historical context - but for golf.

We started with the S-curve regional prediction tool because it answers one of the most common questions in the sport every spring: “Where is my team going to regionals?” Coaches are fanatic about this, and nobody was providing an interactive version based on real data. But the S-curve is just the entry point. We are building toward a comprehensive platform with analytical tools, team season reports, schedule optimization, historical record books, and our own ranking system.

The free tools get eyes on the platform. The paid products - season reports, schedule analysis, record books - answer questions that coaches and programs actually spend money on. We are not a media outlet chasing pageviews. We are building data products for people who work in college golf.

How the S-Curve Works

The NCAA selects 81 teams for the Division I Men's Golf Championship (72 for women's), distributed across six regional sites. The selection committee uses a serpentine (S-curve) distribution to balance competitive strength: the top 6 seeds go to regionals 1 through 6, seeds 7-12 are assigned in reverse order (6 through 1), seeds 13-18 go forward again, and so on. This ensures no single regional is stacked with all the top-ranked teams.

Committee vs. Strict S-Curve

Our tool offers two modes. The Strict S-Curve is the pure mathematical serpentine - what a computer would output with no human judgment applied. The Committee Prediction replicates how the NCAA selection committee actually operates, with three key adjustments:

1. Top-seed proximity: The committee assigns the top 6 seeds to whichever regional site is closest to them geographically, rather than following the strict serpentine order. This is why a team like Texas typically lands at the Bryan Regional, not wherever the math says.
2. Host school guarantee: If a host school is in the field, they play at their home regional. The team that would have been placed there swaps with the host within the same seed tier.
3. Auto-qualifier preference: Automatic qualifiers from smaller conferences (typically seeded around 12-13) usually get some geographic consideration. The committee avoids shipping them across the country when a closer regional is available.

You can toggle between these two modes on the predictions page to see how human judgment changes the regional assignments versus a pure mathematical approach. The differences tell you a lot about where the committee is likely to deviate from the numbers.

The Advancement Line

In the regional view, you will see a red dashed line between the 5th and 6th team in each regional. The top 5 teams from each regional advance to the NCAA Championship. This makes the matchups around that cutoff line the most interesting - those are the bubble teams where head-to-head records, course familiarity, and momentum matter most.

Why Geography Matters

Travel distance is one of the most underappreciated factors in regional performance. Teams that fly across the country face jet lag, unfamiliar course conditions, and altitude or climate changes. The NCAA selection committee considers geography when finalizing placements, but competitive balance takes priority. Our distance calculations and interactive travel map help fans and coaches see which teams drew favorable or unfavorable travel and how that might influence results.

What We're Building Next

The S-curve is just the beginning. Here is what is on the roadmap:

Key Dates - 2026 Postseason

The Team