| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | University of Wisconsin | Badgers | 12–0 | |
| 2 | University of Minnesota | Gophers 1 | 9–3 | |
| 3 | University of Wisconsin Milwaukee | Panthers | 6–6 | |
| 4 | University of Minnesota | Gophers 2 | 3–9 | |
| 5 | Marquette University | Golden Eagles | 0–12 |
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 11,764 team race matches sailed before 2018-09-22, using the line-ups that actually raced. It called 27 of 30 matches (90%) with a log-loss of 0.175 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.42 ± 0.37: an orderly event, more orderly than 87% 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 Wisconsin Badgers | 1 | 6.87 school −0.06 | Samuel Bartel / Patrick Stiles Douglas Wake / Thomas Kelly Jonathan Bailey / Zach Childs | 92% | 12–0 (100%) | +0.9 |
| 2 | University of Minnesota Gophers 1 | 2 | 5.88 school +0.37, home +0.42 | Carl Eaton / Kendall Van Horne 2.46 Michael Stone / Bailey Adkins 1.49 Alexander Mckee / Jenna Pleshek | 81% | 9–3 (75%) | −0.7 |
| 3 | University of Wisconsin Milwaukee Panthers | 4 | 2.09 school −0.06 | Tom Rorrer / Susie Voltz Dominique Hamilton / Adam Stollenwerk Sydney Maxwell / Alphia Korpela 6–0 Sydney Maxwell / Jack Bertram 0–6 | 30% | 6–6 (50%) | +2.3 |
| 4 | University of Minnesota Gophers 2 | 3 | 2.44 school +0.37, home +0.42 | Clara Brown / Meara Cline Maya Smith / Matthew Granstrom 0.32 Victor Nartovich / Madeline Jones | 36% | 3–9 (25%) | −1.4 |
| 5 | Marquette University Golden Eagles | 5 | 0.86 school −0.50 | Colin Higgins / Jonathan Watzka 0.46 Etain Mckinney / Brennan Long Brynn Mesec / Erik Floyd | 10% | 0–12 (0%) | −1.2 |
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) |
|---|---|---|---|---|---|---|---|---|
| 1 | University of Wisconsin Badgers | 6.87 | 9.87 | 12–0 | 11.1 | ≥+3.00 | 1.5 | 33% |
| 3 | University of Wisconsin Milwaukee Panthers | 2.09 | 4.07 | 6–6 | 3.7 | +1.97 | 3.2 | 5% |
| 2 | University of Minnesota Gophers 1 | 5.88 | 4.97 | 9–3 | 9.7 | −0.91 | 0.5 | 94% |
| 4 | University of Minnesota Gophers 2 | 2.44 | 1.44 | 3–9 | 4.4 | −1.00 | 1.0 | 95% |
| 5 | Marquette University Golden Eagles | 0.86 | -2.14 | 0–12 | 1.2 | ≤−3.00 | 1.9 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Tom Rorrer | University of Wisconsin Milwaukee | 1.19 | 3.16 | 6–6 | 3.7 | +1.97 | 3.2 | 5% |
| Dominique Hamilton | University of Wisconsin Milwaukee | -0.07 | 1.90 | 6–6 | 3.7 | +1.97 | 3.2 | 5% |
| Alexander Mckee | University of Minnesota | 0.91 | 0.00 | 9–3 | 9.7 | −0.91 | 0.5 | 94% |
| Maya Smith | University of Minnesota | 0.32 | -0.67 | 3–9 | 4.4 | −1.00 | 1.0 | 95% |
| Victor Nartovich | University of Minnesota | -0.12 | -1.11 | 3–9 | 4.4 | −1.00 | 1.0 | 95% |
| Colin Higgins | Marquette University | 0.46 | -2.54 | 0–12 | 1.2 | ≤−3.00 | 1.9 | >99% |
| Brynn Mesec | Marquette University | 0.77 | -2.23 | 0–12 | 1.2 | ≤−3.00 | 1.9 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Rd | # | Winner | Loser | P(winner) | |
|---|---|---|---|---|---|
| 1 | 1 | University of Minnesota Gophers 1 | University of Minnesota Gophers 2 | 97% | |
| 1 | 2 | University of Wisconsin Milwaukee Panthers | Marquette University Golden Eagles | 76% | |
| 1 | 3 | University of Wisconsin Badgers | University of Minnesota Gophers 1 | 66% | |
| 1 | 4 | University of Minnesota Gophers 2 | Marquette University Golden Eagles | 83% | |
| 1 | 5 | University of Wisconsin Badgers | University of Wisconsin Milwaukee Panthers | 99% | |
| 1 | 6 | University of Minnesota Gophers 1 | Marquette University Golden Eagles | 99% | |
| 1 | 7 | University of Wisconsin Milwaukee Panthers | University of Minnesota Gophers 2 | 41% | upset |
| 1 | 8 | University of Wisconsin Badgers | Marquette University Golden Eagles | 100% | |
| 1 | 9 | University of Minnesota Gophers 1 | University of Wisconsin Milwaukee Panthers | 98% | |
| 1 | 10 | University of Wisconsin Badgers | University of Minnesota Gophers 2 | 99% | |
| 2 | 11 | University of Minnesota Gophers 1 | University of Minnesota Gophers 2 | 97% | |
| 2 | 12 | University of Wisconsin Milwaukee Panthers | Marquette University Golden Eagles | 78% | |
| 2 | 13 | University of Wisconsin Badgers | University of Minnesota Gophers 1 | 72% | |
| 2 | 14 | University of Minnesota Gophers 2 | Marquette University Golden Eagles | 83% | |
| 2 | 15 | University of Wisconsin Badgers | University of Wisconsin Milwaukee Panthers | 99% | |
| 2 | 16 | University of Minnesota Gophers 1 | Marquette University Golden Eagles | 99% | |
| 2 | 17 | University of Wisconsin Milwaukee Panthers | University of Minnesota Gophers 2 | 42% | upset |
| 2 | 18 | University of Wisconsin Badgers | Marquette University Golden Eagles | 100% | |
| 2 | 19 | University of Minnesota Gophers 1 | University of Wisconsin Milwaukee Panthers | 98% | |
| 2 | 20 | University of Wisconsin Badgers | University of Minnesota Gophers 2 | 99% | |
| 3 | 21 | University of Minnesota Gophers 1 | University of Minnesota Gophers 2 | 97% | |
| 3 | 22 | University of Wisconsin Milwaukee Panthers | Marquette University Golden Eagles | 78% | |
| 3 | 23 | University of Wisconsin Badgers | University of Minnesota Gophers 1 | 74% | |
| 3 | 24 | University of Minnesota Gophers 2 | Marquette University Golden Eagles | 83% | |
| 3 | 25 | University of Wisconsin Badgers | University of Wisconsin Milwaukee Panthers | 99% | |
| 3 | 26 | University of Minnesota Gophers 1 | Marquette University Golden Eagles | 99% | |
| 3 | 27 | University of Wisconsin Milwaukee Panthers | University of Minnesota Gophers 2 | 42% | upset |
| 3 | 28 | University of Wisconsin Badgers | Marquette University Golden Eagles | 100% | |
| 3 | 29 | University of Minnesota Gophers 1 | University of Wisconsin Milwaukee Panthers | 98% | |
| 3 | 30 | University of Wisconsin Badgers | University of Minnesota Gophers 2 | 99% |
| Team | Rec. | Badgers | 1 | Panthers | 2 | Eagles | |
|---|---|---|---|---|---|---|---|
| University of Wisconsin Badgers | 4–0 | ✕ | W | W | W | W | |
| University of Minnesota Gophers 1 | 4–4 | L | ✕ | W | ✕ | W | |
| University of Wisconsin Milwaukee Panthers | 2–2 | L | L | ✕ | L | W | |
| University of Minnesota Gophers 2 | 4–4 | L | ✕ | W | ✕ | W | |
| Marquette University Golden Eagles | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Badgers | 1 | Panthers | 2 | Eagles | |
|---|---|---|---|---|---|---|---|
| University of Wisconsin Badgers | 4–0 | ✕ | W | W | W | W | |
| University of Minnesota Gophers 1 | 4–4 | L | ✕ | W | ✕ | W | |
| University of Wisconsin Milwaukee Panthers | 2–2 | L | L | ✕ | L | W | |
| University of Minnesota Gophers 2 | 4–4 | L | ✕ | W | ✕ | W | |
| Marquette University Golden Eagles | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Badgers | 1 | Panthers | 2 | Eagles | |
|---|---|---|---|---|---|---|---|
| University of Wisconsin Badgers | 4–0 | ✕ | W | W | W | W | |
| University of Minnesota Gophers 1 | 4–4 | L | ✕ | W | ✕ | W | |
| University of Wisconsin Milwaukee Panthers | 2–2 | L | L | ✕ | L | W | |
| University of Minnesota Gophers 2 | 4–4 | L | ✕ | W | ✕ | W | |
| Marquette University Golden Eagles | 0–4 | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Gophers 1 | 1-2-4 | def. | Gophers 2 | 3-5-6 DNS | ||
| 2 | Panthers | 1-2-4 | def. | Golden Eagles | 3-5-6 | ||
| 3 | Badgers | 1-3-4 | def. | Gophers 1 | 2-5-6 | ||
| 4 | Gophers 2 | 1-2-3 | def. | Golden Eagles | 4-5-6 | ||
| 5 | Badgers | 1-2-3 | def. | Panthers | 4-5-6 | ||
| 6 | Gophers 1 | 1-2-3 | def. | Golden Eagles | 4-5-6 | ||
| 7 | Panthers | 1-3-5 | def. | Gophers 2 | 2-4-6 | ||
| 8 | Badgers | 1-2-3 | def. | Golden Eagles | 4-5-6 | ||
| 9 | Gophers 1 | 1-2-3 | def. | Panthers | 4-5-6 | ||
| 10 | Badgers | 1-2-3 | def. | Gophers 2 | 4-5-6 | ||
| 11 | Gophers 1 | 1-2-3 | def. | Gophers 2 | 4-5-6 | ||
| 12 | Panthers | 1-2-4 | def. | Golden Eagles | 3-5-6 | ||
| 13 | Badgers | 1-2-4 | def. | Gophers 1 | 3-5-6 | ||
| 14 | Gophers 2 | 1-3-6 | def. | Golden Eagles | 2-4-5 | ||
| 15 | Badgers | 1-2-3 | def. | Panthers | 4-5-6 | ||
| 16 | Gophers 1 | 1-2-4 | def. | Golden Eagles | 3-5-6 | ||
| 17 | Panthers | 2-3-4 | def. | Gophers 2 | 1-5-6 | ||
| 18 | Badgers | 1-2-3 | def. | Golden Eagles | 4-5-6 | ||
| 19 | Gophers 1 | 1-2-3 | def. | Panthers | 4-5-6 | ||
| 20 | Badgers | 1-2-3 | def. | Gophers 2 | 4-5-6 | ||
| 21 | Gophers 1 | 1-2-4 | def. | Gophers 2 | 3-5-6 | ||
| 22 | Panthers | 1-2-4 | def. | Golden Eagles | 3-5-6 | ||
| 23 | Badgers | 1-2-5 | def. | Gophers 1 | 3-4-6 | ||
| 24 | Gophers 2 | 1-3-5 | def. | Golden Eagles | 2-4-6 | ||
| 25 | Badgers | 1-2-4 | def. | Panthers | 3-5-6 | ||
| 26 | Gophers 1 | 1-2-3 | def. | Golden Eagles | 4-5-6 | ||
| 27 | Panthers | 2-3-4 | def. | Gophers 2 | 1-5-6 DNS | ||
| 28 | Badgers | 1-2-3 | def. | Golden Eagles | 4-5-6 | ||
| 29 | Gophers 1 | 1-2-3 | def. | Panthers | 4-5-6 | ||
| 30 | Badgers | 1-2-3 | def. | Gophers 2 | 4-5-6 | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| University of Wisconsin | Badgers | Douglas Wake '22 Jonathan Bailey '22 Samuel Bartel '22 |
Thomas Kelly '20 Zach Childs '21 Patrick Stiles '22 |
|
| University of Minnesota | Gophers 1 | Alexander Mckee '19 Carl Eaton '21 Michael Stone '19 |
Jenna Pleshek '20 Kendall Van Horne '20 Bailey Adkins '19 |
|
| University of Wisconsin Milwaukee | Panthers | Dominique Hamilton '22 Sydney Maxwell '21 Tom Rorrer '22 |
Adam Stollenwerk '22 Jack Bertram '22 Alphia Korpela '22 Susie Voltz '19 |
|
| University of Minnesota | Gophers 2 | Clara Brown '22 Maya Smith '19 Victor Nartovich '21 |
Meara Cline '20 Matthew Granstrom '21 Madeline Jones '20 |
|
| Marquette University | Golden Eagles | Brynn Mesec '22 Colin Higgins '21 Etain Mckinney '22 |
Erik Floyd '21 Jonathan Watzka '22 Brennan Long '21 |
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 ±0.01 means a rating gap counts about 1% 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.