| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | University of Michigan | Wolverines | 9–1 | |
| 2 | Northwestern University | Wildcats | 8–2 | |
| 3 | University of Saint Thomas | Tommies | 6–4 | |
| 4 | University of Wisconsin | Badgers | 5–5 | |
| 5 | University of Notre Dame | Fighting Irish | 2–8 | |
| 6 | Purdue University | Boilermakers | 0–10 |
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 27,057 team race matches sailed before 2025-04-04, using the line-ups that actually raced. It called 26 of 30 matches (87%) with a log-loss of 0.318 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.45 ± 0.36: an orderly event, more orderly than 90% 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.
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) |
|---|---|---|---|---|---|---|---|---|
| 1 | University of Michigan | 6.07 | 7.01 | 9–1 | 7.9 | +0.94 | 0.7 | 33% |
| 2 | Northwestern University | 5.48 | 6.35 | 8–2 | 6.7 | +0.87 | 0.8 | 26% |
| 3 | University of Saint Thomas | 4.60 | 5.27 | 6–4 | 4.8 | +0.66 | 0.6 | 29% |
| 4 | University of Wisconsin | 5.46 | 4.48 | 5–5 | 6.8 | −0.99 | 1.3 | 96% |
| 5 | University of Notre Dame | 4.02 | 2.57 | 2–8 | 3.5 | −1.45 | 1.4 | 98% |
| 6 | Purdue University | 1.40 | -1.60 | 0–10 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Nicholas Chesemore | Northwestern University | 1.94 | 2.80 | 8–2 | 6.7 | +0.87 | 0.8 | 26% |
| George Warfel | Northwestern University | 1.09 | 1.95 | 8–2 | 6.7 | +0.87 | 0.8 | 26% |
| Theodore Graham | University of Saint Thomas | 1.69 | 2.35 | 6–4 | 4.8 | +0.66 | 0.6 | 29% |
| Quinn Kaiser | University of Wisconsin | 1.43 | 0.45 | 5–5 | 6.8 | −0.99 | 1.3 | 96% |
| Nathanael Green | Purdue University | 0.79 | -2.21 | 0–10 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Mathis Destouches | Purdue University | -0.06 | -3.06 | 0–10 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Alexander Sau Hang Ching | Purdue University | 0.50 | -2.50 | 0–10 | 0.3 | ≤−3.00 | 0.4 | >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 | Wildcats | Tommies | Badgers | Irish | Boilermakers | |
|---|---|---|---|---|---|---|---|---|
| University of Michigan Wolverines | 4–1 | ✕ | W | W | L | W | W | |
| Northwestern University Wildcats | 4–1 | L | ✕ | W | W | W | W | |
| University of Saint Thomas Tommies | 3–2 | L | L | ✕ | W | W | W | |
| University of Wisconsin Badgers | 3–2 | W | L | L | ✕ | W | W | |
| University of Notre Dame Fighting Irish | 1–4 | L | L | L | L | ✕ | W | |
| Purdue University Boilermakers | 0–5 | L | L | L | L | L | ✕ |
| Team | Rec. | Wolverines | Wildcats | Tommies | Badgers | Irish | Boilermakers | |
|---|---|---|---|---|---|---|---|---|
| University of Michigan Wolverines | 5–0 | ✕ | W | W | W | W | W | |
| Northwestern University Wildcats | 4–1 | L | ✕ | W | W | W | W | |
| University of Saint Thomas Tommies | 3–2 | L | L | ✕ | W | W | W | |
| University of Wisconsin Badgers | 2–3 | L | L | L | ✕ | W | W | |
| University of Notre Dame Fighting Irish | 1–4 | L | L | L | L | ✕ | W | |
| Purdue University Boilermakers | 0–5 | L | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Wildcats | 1-2-3 | def. | Boilermakers | 4-5-6 | ||
| 2 | Tommies | 1-2-6 | def. | Fighting Irish | 3-4-5 | ||
| 3 | Badgers | 1-2-4 | def. | Wolverines | 3-5-6 | ||
| 4 | Wildcats | 1-2-5 | def. | Fighting Irish | 3-4-6 | ||
| 5 | Badgers | 1-3-4 | def. | Boilermakers | 2-5-6 | ||
| 6 | Wolverines | 1-2-6 | def. | Tommies | 3-4-5 | ||
| 7 | Badgers | 1-2-5 | def. | Fighting Irish | 3-4-6 | ||
| 8 | Wildcats | 1-2-6 | def. | Tommies | 3-4-5 | ||
| 9 | Wolverines | 1-2-4 | def. | Boilermakers | 3-5-6 | ||
| 10 | Tommies | 2-3-4 | def. | Badgers | 1-5-6 | ||
| 11 | Fighting Irish | 1-2-5 | def. | Boilermakers | 3-4-6 | ||
| 12 | Wolverines | 1-2-6 | def. | Wildcats | 3-4-5 | ||
| 13 | Tommies | 1-2-5 | def. | Boilermakers | 3-4-6 | ||
| 14 | Wildcats | 1-2-6 | def. | Badgers | 3-4-5 | ||
| 15 | Wolverines | 1-2-4 | def. | Fighting Irish | 3-5-6 | ||
| 16 | Wildcats | 1-2-6 | def. | Boilermakers | 3-4-5 | ||
| 17 | Tommies | 1-3-4 | def. | Fighting Irish | 2-5-6 | ||
| 18 | Wolverines | 2-3-4 | def. | Badgers | 1-5-6 | ||
| 19 | Wildcats | 1-2-5 | def. | Fighting Irish | 3-4-6 | ||
| 20 | Badgers | 1-2-5 | def. | Boilermakers | 3-4-6 | ||
| 21 | Wolverines | 1-3-4 | def. | Tommies | 2-5-6 | ||
| 22 | Badgers | 1-2-4 | def. | Fighting Irish | 3-5-6 | ||
| 23 | Wildcats | 1-3-4 | def. | Tommies | 2-5-6 | ||
| 24 | Wolverines | 1-2-4 | def. | Boilermakers | 3-5-6 | ||
| 25 | Tommies | 1-2-6 | def. | Badgers | 3-4-5 | ||
| 26 | Fighting Irish | 1-2-4 | def. | Boilermakers | 3-5-6 | ||
| 27 | Wolverines | 2-3-5 | def. | Wildcats | 1-4-6 | ||
| 28 | Tommies | 2-3-5 | def. | Boilermakers | 1-4-6 | ||
| 29 | Wildcats | 2-3-4 | def. | Badgers | 1-5-6 | ||
| 30 | Wolverines | 1-2-5 | def. | Fighting Irish | 3-4-6 | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| University of Michigan | Wolverines | Billy Vogel '25 Braden Vogel '27 Jack Hammett '26 Jack Homa '27 |
Alexander Reynolds '28 Nina Gonzalez '27 Abigail Paul '25 Ben Visco '28 |
|
| Northwestern University | Wildcats | George Warfel '26 Jake Weinstein '27 Nicholas Chesemore '27 |
Maddie Fitzgerald '26 Cora Star '26 Samantha Forgosh '26 |
|
| University of Saint Thomas | Tommies | Greg Bittle '25 Rakesh Dhiman '26 Theodore Graham '26 |
Lily Lupardus '27 Naomi Peters '26 Leila Montoya '28 |
|
| University of Wisconsin | Badgers | Calvin Lutton '26 Quinn Kaiser '26 Ryan Tatelbaum '25 |
Cansin Ozsoy '26 Ella Engel '27 Carter Harms '27 |
|
| University of Notre Dame | Fighting Irish | Jack O'Connor '26 Payden Pittman '28 Timothy Hesse '27 |
John Sullivan '26 Joseph Opferman '27 Kate Norman '26 |
|
| Purdue University | Boilermakers | Alexander Sau Hang Ching '28 Mathis Destouches '25 Nathanael Green '28 |
Max Liu '26 Annette Wadley '26 Nok In Chan '25 |
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 ±0.00 means a rating gap counts about 1% less 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.