| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | University of Michigan | Wolverines | 13–3 | |
| 2 | University of Wisconsin | Badgers | 12–4 | |
| 3 | University of Minnesota | Gophers | 9–6 | |
| 4 | Northwestern University | Wildcats | 3–12 | |
| 5 | University of Illinois | Illini | 1–8 |
Each side is the sum of its three boats (the skipper's fleet rating times 0.72 plus a team race offset learned from their past matches, plus the crew's offset and a small experience term) plus the school's team race strength and a home-water edge for the host. The win probability is a logistic function of the difference. The forecast was made before the event: the model was refitted on every match sailed before the first day, with fleet ratings as of the week before.
Fitted on the 3,697 team race matches sailed before 2014-04-19, using the line-ups that actually raced. It called 27 of 33 matches (82%) with a log-loss of 0.284 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness −0.11 ± 0.32: a typical event, more orderly than 31% of college team race events (temperature of the forecast log-odds that best fits the results, relative to the league average; nothing about the field, venue or wind predicts it, see the Weather tab). vs forecast is a team's wins minus the wins the model expected from the matches it sailed: positive means it beat its rating.
| Place | School | Pred. | Strength | Boats (skipper / crew, boat value) | Pred. win % | Record | vs forecast |
|---|---|---|---|---|---|---|---|
| 1 | University of Michigan Wolverines | 2 | 9.09 school +0.15 | Will Cyr / Elizabeth Wallace 2.64 Ryan Seago / Scott Ismail 3.01 Alex Ramos / Karinne Smolenyak 3.19 | 77% | 12–3 (80%) | +0.4 |
| 2 | University of Wisconsin Badgers | 1 | 9.09 school −0.18, home +0.34 | Connor Trepton / Katrina Debbink 3.01 Michael Lee / Erin Monahan 2.97 George Kutschenreuter / Jennifer Burke 3.15 7–4 John Kinzel / Caya Mcfalls 4–0 | 84% | 11–4 (73%) | −1.6 |
| 3 | University of Minnesota Gophers | 3 | 6.90 | Drake Lundeen / Sarah Ellis Ryan Grosch / Paige Boegeman Wheeler Morris / Emily Johnson 2.22 | 46% | 8–6 (57%) | +1.5 |
| 4 | Northwestern University Wildcats | 4 | 4.14 school +0.33 | Jacob Bruce / Aislinn Mcmillan 1.02 Travis Cottle / Yi Zhang 1.48 Robert Johnston / Allison Park 1.08 | 15% | 2–12 (14%) | −0.1 |
| 5 | University of Illinois Illini | 5 | 1.93 | Melinda Lee / Diana Perez Charles Diamond / Filippa Malmqvist Emily Slabe / Melinda Lee | 3% | 0–8 (0%) | −0.2 |
For each side, the performance strength is the value that would have made its record least surprising: the strength at which the model's expected wins over exactly these opponents equal the actual wins, with every opponent fixed at its pre-event strength. For a skipper, the same shift is applied only to their boat in the matches they sailed, with team-mates and opponents fixed; team-mates who sailed every match together therefore get the same number. Surprise is in bits: -log2 of the probability of the record at the pre-event strength minus the same at the performance strength. P(this good or better) treats matches as independent coin flips at the model's pre-event probabilities, so it ignores form within the day; read it as a rough guide.
Pre-event strength against the strength that would have made each record least surprising, everything else fixed. Δ is in the model's logit units, the same scale as the boat values above (a side is three boats plus the school term); green is a clear over-performance, red a clear under-performance. Skippers need three or more matches.
| Place | School | Strength | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| 3 | University of Minnesota | 6.90 | 8.20 | 8–6 | 6.5 | +1.30 | 1.6 | 12% |
| 1 | University of Michigan | 9.09 | 9.33 | 12–3 | 11.6 | +0.24 | 0.1 | 54% |
| 4 | Northwestern University | 4.14 | 3.83 | 2–12 | 2.1 | −0.31 | 0.0 | 87% |
| 2 | University of Wisconsin | 9.09 | 8.20 | 11–4 | 12.6 | −0.90 | 1.0 | 95% |
| 5 | University of Illinois | 1.93 | -1.07 | 0–8 | 0.2 | ≤−3.00 | 0.3 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| John Kinzel | University of Wisconsin | 1.77 | 4.77 | 4–0 | 3.9 | ≥+3.00 | 0.1 | 93% |
| Drake Lundeen | University of Minnesota | 2.08 | 3.38 | 8–6 | 6.5 | +1.30 | 1.6 | 12% |
| Ryan Grosch | University of Minnesota | 1.84 | 3.15 | 8–6 | 6.5 | +1.30 | 1.6 | 12% |
| Ryan Seago | University of Michigan | 3.01 | 3.25 | 12–3 | 11.6 | +0.24 | 0.1 | 54% |
| Alex Ramos | University of Michigan | 3.19 | 3.43 | 12–3 | 11.6 | +0.24 | 0.1 | 54% |
| Jacob Bruce | Northwestern University | 1.02 | 0.71 | 2–12 | 2.1 | −0.31 | 0.0 | 87% |
| Travis Cottle | Northwestern University | 1.48 | 1.17 | 2–12 | 2.1 | −0.31 | 0.0 | 87% |
| Robert Johnston | Northwestern University | 1.08 | 0.77 | 2–12 | 2.1 | −0.31 | 0.0 | 87% |
| Connor Trepton | University of Wisconsin | 3.01 | 2.11 | 11–4 | 12.6 | −0.90 | 1.0 | 95% |
| Michael Lee | University of Wisconsin | 2.97 | 2.07 | 11–4 | 12.6 | −0.90 | 1.0 | 95% |
| George Kutschenreuter | University of Wisconsin | 3.15 | 2.15 | 7–4 | 8.6 | −1.00 | 1.2 | 96% |
| Melinda Lee | University of Illinois | 1.07 | -1.93 | 0–8 | 0.2 | ≤−3.00 | 0.3 | >99% |
| Charles Diamond | University of Illinois | 0.96 | -2.04 | 0–8 | 0.2 | ≤−3.00 | 0.3 | >99% |
| Emily Slabe | University of Illinois | -0.78 | -3.78 | 0–8 | 0.2 | ≤−3.00 | 0.3 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Wolverines | Badgers | Gophers | Wildcats | Illini | |
|---|---|---|---|---|---|---|---|
| University of Michigan Wolverines | 6–1 | ✕ | W | L | W | W | |
| University of Wisconsin Badgers | 5–2 | L | ✕ | W | W | W | |
| University of Minnesota Gophers | 4–3 | W | L | ✕ | W | W | |
| Northwestern University Wildcats | 1–6 | L | L | L | ✕ | W | |
| University of Illinois Illini | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Wolverines | Badgers | Gophers | Wildcats | Illini | |
|---|---|---|---|---|---|---|---|
| University of Michigan Wolverines | 6–2 | ✕ | W | L | W | W | |
| University of Wisconsin Badgers | 6–2 | L | ✕ | W | W | W | |
| University of Minnesota Gophers | 4–3 | W | L | ✕ | W | W | |
| Northwestern University Wildcats | 1–6 | L | L | L | ✕ | W | |
| University of Illinois Illini | 0–4 | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Wolverines | 1-2-6 | def. | Gophers | 3-4-5 | ||
| 2 | Wildcats | 2-3-4 | def. | Illini | 1-5-6 | ||
| 3 | Wolverines | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 4 | Badgers | 1-2-3 | def. | Illini | 4-5-6 | ||
| 5 | Wolverines | 1-2-3 | def. | Illini | 4-5-6 | ||
| 6 | Badgers | 1-2-5 | def. | Gophers | 3-4-6 | ||
| 7 | Gophers | 1-2-5 | def. | Wildcats | 3-4-6 | ||
| 8 | Wolverines | 1-2-6 | def. | Badgers | 3-4-5 | ||
| 9 | Gophers | 1-2-3 | def. | Illini | 4-5-6 | ||
| 10 | Badgers | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 21 | Gophers | 2-3-5 | def. | Wolverines | 1-4-6 | ||
| 22 | Badgers | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 23 | Wolverines | 1-2-6 | def. | Wildcats | 3-4-5 | ||
| 24 | Badgers | 1-2-5 | def. | Gophers | 3-4-6 | ||
| 25 | Gophers | 1-2-4 | def. | Wildcats | 3-5-6 | ||
| 26 | Wolverines | 2-3-4 | def. | Badgers | 1-5-6 | ||
| 11 | Badgers | 1-2-3 | def. | Illini | 4-5-6 | ||
| 12 | Gophers | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 13 | Badgers | 1-2-5 | def. | Wolverines | 3-4-6 | ||
| 14 | Wildcats | 1-3-5 | def. | Illini | 2-4-6 | ||
| 15 | Wolverines | 1-2-6 | def. | Gophers | 3-4-5 | ||
| 16 | Badgers | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 17 | Wolverines | 1-2-4 | def. | Illini | 3-5-6 | ||
| 18 | Badgers | 1-2-5 | def. | Gophers | 3-4-6 | ||
| 19 | Wolverines | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 20 | Gophers | 1-2-3 | def. | Illini | 4-5-6 | ||
| 27 | Gophers | 1-3-5 | def. | Wolverines | 2-4-6 | ||
| 28 | Badgers | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 29 | Wolverines | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 30 | Badgers | 1-3-6 | def. | Gophers | 2-4-5 | ||
| 31 | Gophers | 1-2-3 | def. | Wildcats | 4-5-6 | ||
| 32 | Wolverines | 1-2-5 | def. | Badgers | 3-4-6 | ||
| 33 | Wolverines | 1-3-5 | def. | Badgers | 2-4-6 | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| University of Michigan | Wolverines | Alex Ramos '15 Ryan Seago '14 Will Cyr '14 |
Karinne Smolenyak '15 Scott Ismail '14 Elizabeth Wallace '15 |
|
| University of Wisconsin | Badgers | Connor Trepton '15 George Kutschenreuter '15 John Kinzel '14 Michael Lee '14 |
Katrina Debbink '15 Jennifer Burke '16 Caya Mcfalls '16 Erin Monahan '14 |
|
| University of Minnesota | Gophers | Drake Lundeen '14 Ryan Grosch '14 Wheeler Morris '16 |
Sarah Ellis '14 Paige Boegeman '14 Emily Johnson '16 |
|
| Northwestern University | Wildcats | Jacob Bruce '16 Robert Johnston '15 Travis Cottle '15 |
Aislinn Mcmillan '17 Allison Park '17 Yi Zhang '17 |
|
| University of Illinois | Illini | Charles Diamond '15 Emily Slabe '15 Melinda Lee '16 |
Filippa Malmqvist '15 Melinda Lee '16 Diana Perez '17 |
Orderliness is how tightly a fleet race’s finishing order follows the pre-regatta ratings, relative to a typical event (0): positive is the favourites’ day, negative the underdogs’. A value of ±0.22 means a rating gap counts about 19% more than on a typical day. This event is not a fleet race the rating model scores, so there is no actual value for it: this is what this venue’s fleet racing history says about the breeze on the day, read off the chart at the star. How this is estimated · compare venues.
Short write-ups of what the ratings and results show, with the numbers and how they were computed.