These predictions were meticulously made by a
"washed-up grad student" in a recent post on the message boards of
LetsRun.com
He must have had a lot of time!

“Cross. . . country. . . time is relative” – Albert Einstein
These rankings are calculated using the following algorithm:
- Gather all of the meets which the teams in the region competed
in. For each pair of meets, use the individuals who ran in both meets
to evaluate the difference in their speed.
- Use least-squares to get an overall adjustment score for each meet.
- Gather the teams from last year’s regional results and form their top 7 from their most recent results.
SOME TEAMS DID NOT RUN THEIR TOP 7 IN THE MOST RECENT MEET. IF THIS IS
THE CASE FOR YOUR TEAM PLEASE EMAIL ME AND I WILL FIX IT. (bmazaher at caltech dot edu)
- For each member of a team’s top 7, adjust all of their performances according to the meet’s score.
- Average
each runner’s performances over the season. More weight is given to
recent performances. More weight is also given to performances whose
adjustment is more certain.
- Rank all of the individuals in the meet and score the simulated results.
Interpret the results in the following way:
[Place] [Time] [Time behind leader] [Uncertainty of time] [Name] [School]
The uncertainty of the times is in seconds. That is, someone with a
“time behind leader” of 30 and an uncertainty of 10 will likely run
between 20 and 40 seconds behind the winner.
I have copied the Penn State top 7 predictions using 5000 simulations:
- Kathryn Munks 30th (24th-62nd)
- Alison Willingmyre 108th (88-131)
- Danae Rivers 112th (94-151)
- Julia Paternain 137th (98-153)
- Megan Ciasullo 194th (157-214)
- Kileigh Kane 219th (192-248)
- Julia Guerra 238th (200-247)
And here's the Team Scores for all the B1G teams:
- 4th Michigan State (4-6)
- 5th Michigan (5-8)
- 7th Wisconsin (6-10)
- 15th Illinois (14-19)
- 16th Ohio State (14-19)
- 17th Penn State (15-20)
- 22nd Indiana (19-25)
- 26th Minnesota (22-28)