Cross country fans have long suspected that Wisconsin dominates the sport, but are the Badgers really the best of all time? Now you can quantify any teams’ long-term excellence using historical data in Faster Than Forty’s “All-Time NCAA Cross Country Program Rankings.”
Wisconsin bested Arkansas by a solid 326 points, based on the schools’ performances in NCAA Cross Country Championships going back 50 years to 1961. Colorado, Providence, and Oregon rounded out the top five programs, respectively. The full set of rankings is available for free via a downloadable Excel file available here:
(Note: This is a “Read Only” file – so choose “Read Only” when prompted. You can’t save changes to it; but you can use all the standard Excel tools to search/sort the data and play with it however you see fit.)
Perhaps more surprising than the schools who made the top-10 list are the names of some of the schools that did not – including Stanford, Dartmouth and Iona. But 50 years is a long time, and the schools in the upper echelon had more than just a handful of recent podium performances – they turned in consistent Championship appearances year in and year out. (Wisconsin appeared in no fewer than 40 NCAA Championships during the 50-year period.)
How Did We Build This List?
We gathered all NCAA Cross Country Championships team results data from 1961 to 2010 and scored every school that made at least one appearance in the championship meet during that period. Each school received composite points depending on how well they finished in the championships on a given year, then all the points were totaled. (Think of the scoring as similar to a track meet: first place gets the most points, second place gets a few fewer points, etc. For the exact formula, see the FAQs below…) The available composite points vary slightly from year to year and favor more recent performances because points are awarded based on the total number of NCAA Division-I schools.
We believe this is the first time anyone has compiled 50 years’ worth of NCAA cross country results into one sortable spreadsheet, and when you scan the data you can recognize seismic shifts in the fortunes of certain programs. For example, with nine top-10 finishes in the last 10 years (three podium finishes), you might expect Iona to sit near the top of the all-time cross-country list, but as you scroll back in time, it becomes evident that the Gaels (#23) are a relative Johnny-come-lately to big-time Division-I cross country.
Conversely, East Tennessee had so much talent in the 1970s that they still rank #28 on our list – even though no one has heard from the Bucs in years.
Other surprises: Boston College – home of Faster Than Forty’s Coach @ and renowned for recruiting top New England runners – finished at only #131 in the rankings. Cross-town rival Boston University, however, reached #38 on the strength of some great late 80s/early 90s teams. (We knew BU well; they tortured us up and down the courses in the Northeast while we attended Northeastern University, #89.) The University of Houston, not seen in November in generations, landed at #34 after some outstanding showings in the 1960s. Tennessee (#7) led the SEC, despite recent excellence from Alabama (#22). UTEP was disqualified from not one, but two, NCAA Cross Country Championships — the only “winning” school to be DQ’d at all.
Other non-surprises: Dartmouth led the Ivy League (#25). William & Mary’s consistent excellence earned the #13 spot. NC State was the top-ranked ACC school.
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In total, 148 schools qualified for the list – a number we thought to be low, given that there are 347 D-I schools at present, and more than 300 of them field a cross country team. However even schools known for producing great cross country athletes (like Liberty University) have been unable to qualify full teams for the NCAA Championships, and even some long-time programs (Yale) and powerhouse conference schools (like the SEC’s Ole Miss and Mississippi State) didn’t make the cut – proving just how rarified this field of schools is.
So what can you do with this data, besides argue with your friends (or us) about it? Probably not much; but the next time you’re in a bar listening to some yakoff argue that Oregon is hands-down the number-one cross country school of all time, you can pull up this spreadsheet on your iPhone and shut him up.
Frequently Asked Questions
Q. How did you calculate the scores?
A. We ascribed composite points based on a school’s finish at the NCAA Cross Country Championships. The total points available each year are primarily based on the total number of D-I schools and some minor intangibles related to competitiveness. This number is called a competition multiplier. In 2010 the multiplier was 347. Then we subtracted the school’s NCAA Championships finish from the competition multiplier to arrive at their composite points for the year. Schools that failed to make the NCAAs earned zero points for the year.
Q. The competition multiplier goes up by a few points each year. Why? Doesn’t that devalue older performances?
A. Yes it does. But we think that’s justified. Collegiate cross country gets progressively more competitive as more schools join Division I and as the fluidity of information exchange becomes more prominent. In the 1970s, perhaps only a handful of coaches understood the science of training elite distance athletes – but as more information becomes freely available via the Internet, the gaps in coaching knowledge narrow. “New School” is tougher than “Old School” in this case.
Q. I’m trying to manipulate the data on the “Calculations” tab in your spreadsheet, but when I sort things the data seems wrong. What did you screw up?
A. Something in the convoluted formula we wrote is freaking Excel out. We cut and pasted the correct ranking data into the “Presentation Summary” tab, and you can sort that data by score, by year, and by pretty much anything you want. We also made the “Presentation Summary” prettier to look at.
Q. How come you only go back to 1961? Did that cutoff date affect any schools’ rankings?
A. For one, we’re lazy. None of this data was easy to manipulate digitally. We literally had to retype old fax machine printouts and type-written pages; 50 years was a nice round cutoff number. But also, some things about the sport changed dramatically in the 1950s. For example, they only ran 4-mile championships back then, instead of 6 miles/10K. Second, only a handful of teams could qualify for the NCAA Cross Country Championships back then – usually 12-15 teams. We felt that would impact the scoring too greatly…
And yes, two schools probably got screwed by our lethargy. Michigan State absolutely crushed the nation from 1948-1959, and Drake University three-peated from 1944 to 1946. The Spartans would probably be a top-20 team with those years included, and Drake would certainly be better than #83.
Q. Do you plan to update these rankings?
A. Yes. They won’t likely change dramatically from year to year, but we plan to update them at the end of each season. If enough people express an interest, we’ll create a similar ranking for the women’s teams. (It’s unbelievably time consuming though, so unless lot’s of people download the men’s rankings, we may not bother…)
Q. I want to use this data in a report/news article/blog post/etc. Can I do so freely?
A. Yes, but you must credit Faster Than Forty and link back to our site: www.fasterthanforty.com
Q. Where did you find the data?
A. The NCAA provided some, but the best source was a great page buried deep in the Track and Field News Web site. It has PDF links to the printed results data going all the way back to 1938.
Q. Who is to blame for this nonsense?
Q. I think these rankings suck, and I have a bone to pick with you about them.
A. That’s cool; we’re open to suggestions. We actually created several methodologies to rank the teams — and each yielded slightly different results — so we know this is open for debate. Contact us or comment below.
Rick Miller and Mark Gomes co-founded Faster Than Forty. They ran cross country for Northeastern University and were not very good at it. They have spent most of their professional lives creating data models somewhat similar to this one — and hopefully they are better at that than running.
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