| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | University of Wisconsin | Badgers 1 | 9–1 | |
| 2 | University of Wisconsin | Badgers 2 | 8–2 | |
| 3 | University of Minnesota | Gophers 1 | 7–3 | |
| 4 | University of Wisconsin Milwaukee | Panthers | 5–3 | |
| 5 | University of Wisconsin | Badgers 3 | 4–4 | |
| 6 | University of Wisconsin | Badgers 4 | 1–7 | |
| 7 | Marquette University | Golden Eagles | 2–6 | |
| 8 | University of Minnesota | Gophers 2 | 1–7 | |
| 9 | Iowa State University | Cyclones | 0–8 | |
| 10 | University of Minnesota | Gophers 3 | 0–0 |
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 5,939 team race matches sailed before 2015-10-17, using the line-ups that actually raced. It called 32 of 39 matches (82%) with a log-loss of 0.328 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.05 ± 0.30: a typical event, more orderly than 48% 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) |
|---|---|---|---|---|---|---|---|---|
| 4 | University of Wisconsin Milwaukee Panthers | 3.05 | 4.85 | 5–3 | 3.0 | +1.79 | 2.7 | 6% |
| 2 | University of Wisconsin Badgers 2 | 4.73 | 6.52 | 8–2 | 5.6 | +1.79 | 3.0 | 5% |
| 3 | University of Minnesota Gophers 1 | 5.49 | 5.48 | 7–3 | 7.0 | −0.01 | 0.0 | 68% |
| 1 | University of Wisconsin Badgers 1 | 6.87 | 6.74 | 9–1 | 9.1 | −0.13 | 0.0 | 78% |
| 6 | University of Wisconsin Badgers 4 | 3.59 | 2.91 | 3–5 | 3.7 | −0.67 | 0.3 | 88% |
| 8 | University of Minnesota Gophers 2 | 1.29 | 0.30 | 1–7 | 1.4 | −0.99 | 0.2 | 95% |
| 5 | University of Wisconsin Badgers 3 | 5.12 | 3.59 | 4–4 | 5.7 | −1.53 | 1.9 | 99% |
| 7 | Marquette University Golden Eagles | 3.36 | 1.73 | 2–6 | 3.4 | −1.62 | 1.5 | 98% |
| 9 | Iowa State University Cyclones | -1.15 | -4.15 | 0–8 | 0.1 | ≤−3.00 | 0.2 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Andre Deriaz | University of Wisconsin Milwaukee | 1.15 | 2.94 | 5–3 | 3.0 | +1.79 | 2.7 | 6% |
| Zachary Aasen | University of Wisconsin Milwaukee | 1.29 | 3.08 | 5–3 | 3.0 | +1.79 | 2.7 | 6% |
| John Schmidt | University of Wisconsin Milwaukee | 0.22 | 2.01 | 5–3 | 3.0 | +1.79 | 2.7 | 6% |
| James Sitter | University of Wisconsin | 1.72 | 3.50 | 8–2 | 5.6 | +1.79 | 3.0 | 5% |
| Noah Janssen | University of Wisconsin | 1.52 | 3.31 | 8–2 | 5.6 | +1.79 | 3.0 | 5% |
| Elliot Busta | University of Wisconsin | 1.10 | 2.89 | 8–2 | 5.6 | +1.79 | 3.0 | 5% |
| Alison Kent | University of Minnesota | 2.54 | 2.53 | 7–3 | 7.0 | −0.01 | 0.0 | 68% |
| Isabella Hamilton | University of Minnesota | 1.50 | 1.49 | 7–3 | 7.0 | −0.01 | 0.0 | 68% |
| Eric Villadsen | University of Minnesota | 1.01 | 1.00 | 7–3 | 7.0 | −0.01 | 0.0 | 68% |
| Soren Walljasper | University of Wisconsin | 2.68 | 2.54 | 9–1 | 9.1 | −0.13 | 0.0 | 78% |
| Ian Norman | University of Wisconsin | 1.65 | 1.52 | 9–1 | 9.1 | −0.13 | 0.0 | 78% |
| Charlie Kutschenreuter | University of Wisconsin | 2.23 | 2.09 | 9–1 | 9.1 | −0.13 | 0.0 | 78% |
| Brian Tobelmann | University of Wisconsin | 1.37 | 0.70 | 3–5 | 3.7 | −0.67 | 0.3 | 88% |
| Ari Tessitore | University of Wisconsin | 0.93 | 0.26 | 3–5 | 3.7 | −0.67 | 0.3 | 88% |
| Elizabeth Hayes | University of Wisconsin | 0.77 | 0.10 | 3–5 | 3.7 | −0.67 | 0.3 | 88% |
| Michael Valverde | University of Minnesota | 1.08 | 0.09 | 1–7 | 1.4 | −0.99 | 0.2 | 95% |
| Michael Adkins | University of Minnesota | 0.34 | -0.65 | 1–7 | 1.4 | −0.99 | 0.2 | 95% |
| Christian Palo | University of Minnesota | -0.79 | -1.78 | 1–7 | 1.4 | −0.99 | 0.2 | 95% |
| Megan Mcmahon | University of Wisconsin | 1.12 | -0.41 | 4–4 | 5.7 | −1.53 | 1.9 | 99% |
| Katherine Zimmerman | University of Wisconsin | 1.14 | -0.39 | 4–4 | 5.7 | −1.53 | 1.9 | 99% |
| No Show | Marquette University | 0.90 | -0.72 | 2–6 | 3.4 | −1.62 | 1.5 | 98% |
| Noah Carter | Iowa State University | -0.65 | -3.65 | 0–8 | 0.1 | ≤−3.00 | 0.2 | >99% |
| Tate Carlson | Iowa State University | -0.47 | -3.47 | 0–8 | 0.1 | ≤−3.00 | 0.2 | >99% |
| James Sincox | Iowa State University | -0.68 | -3.68 | 0–8 | 0.1 | ≤−3.00 | 0.2 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | 1 | 2 | 1 | Panthers | 3 | 4 | Eagles | 2 | Cyclones | 3 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| University of Wisconsin Badgers 1 | 21–11 | ✕ | ✕ | W | W | ✕ | ✕ | W | W | W | W | |
| University of Wisconsin Badgers 2 | 21–11 | ✕ | ✕ | W | W | ✕ | ✕ | W | W | W | W | |
| University of Minnesota Gophers 1 | 8–8 | L | L | ✕ | L | L | L | L | ✕ | W | ✕ | |
| University of Wisconsin Milwaukee Panthers | 5–3 | L | L | W | ✕ | L | L | W | W | W | W | |
| University of Wisconsin Badgers 3 | 21–11 | ✕ | ✕ | W | W | ✕ | ✕ | W | W | W | W | |
| University of Wisconsin Badgers 4 | 21–11 | ✕ | ✕ | W | W | ✕ | ✕ | W | W | W | W | |
| Marquette University Golden Eagles | 2–6 | L | L | W | L | L | L | ✕ | W | W | W | |
| University of Minnesota Gophers 2 | 8–8 | L | L | ✕ | L | L | L | L | ✕ | W | ✕ | |
| Iowa State University Cyclones | 0–8 | L | L | L | L | L | L | L | L | ✕ | L | |
| University of Minnesota Gophers 3 | 8–8 | L | L | ✕ | L | L | L | L | ✕ | W | ✕ |
| Team | Rec. | 1 | 2 | 1 | 3 | 4 | 2 | 3 | |
|---|---|---|---|---|---|---|---|---|---|
| University of Wisconsin Badgers 1 | 3–1 | ✕ | ✕ | W | ✕ | ✕ | W | W | |
| University of Wisconsin Badgers 2 | 3–1 | ✕ | ✕ | W | ✕ | ✕ | W | W | |
| University of Minnesota Gophers 1 | 0–2 | L | L | ✕ | L | L | ✕ | ✕ | |
| University of Wisconsin Badgers 3 | 3–1 | ✕ | ✕ | W | ✕ | ✕ | W | W | |
| University of Wisconsin Badgers 4 | 3–1 | ✕ | ✕ | W | ✕ | ✕ | W | W | |
| University of Minnesota Gophers 2 | 0–2 | L | L | ✕ | L | L | ✕ | ✕ | |
| University of Minnesota Gophers 3 | 0–2 | L | L | ✕ | L | L | ✕ | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Gophers 1 | 1-2-4 | def. | Golden Eagles | 3-5-6 | ||
| 2 | Gophers 2 | 1-2-4 | def. | Cyclones | 3-5-6 | ||
| 3 | Badgers 2 | 1-2-6 | def. | Badgers 4 | 3-4-5 | ||
| 4 | Panthers | 1-4-5 | def. | Badgers 3 | 2-3-6 | ||
| 5 | Gophers 1 | 1-2-3 | def. | Gophers 2 | 4-5-6 | ||
| 6 | Badgers 2 | 1-2-5 | def. | Golden Eagles | 3-4-6 | ||
| 7 | Panthers | 1-2-3 | def. | Cyclones | 4-5-6 | ||
| 8 | Badgers 1 | 1-2-4 | def. | Badgers 3 | 3-5-6 | ||
| 9 | Badgers 2 | 1-2-3 | def. | Gophers 2 | 4-5-6 | ||
| 10 | Gophers 1 | 1-2-5 | def. | Panthers | 3-4-6 | ||
| 11 | Badgers 3 | 1-2-3 | def. | Cyclones | 4-5-6 | ||
| 12 | Badgers 1 | 1-2-4 | def. | Badgers 4 | 3-5-6 | ||
| 13 | Badgers 2 | 1-3-6 | def. | Panthers | 2-4-5 | ||
| 14 | Gophers 1 | 2-3-4 | def. | Badgers 3 | 1-5-6 | ||
| 15 | Badgers 4 | 2-3-4 | def. | Golden Eagles | 1-5-6 DSQ | ||
| 16 | Badgers 1 | 1-2-3 | def. | Cyclones | 4-5-6 | ||
| 17 | Badgers 2 | 1-3-5 | def. | Badgers 3 | 2-4-6 | ||
| 18 | Badgers 4 | 1-2-5 | def. | Gophers 2 | 3-4-6 | ||
| 19 | Gophers 1 | 1-2-3 | def. | Cyclones | 4-5-6 | ||
| 20 | Badgers 1 | 1-2-3 | def. | Golden Eagles | 4-5-6 | ||
| 21 | Panthers | 2-3-4 | def. | Badgers 4 | 1-5-6 | ||
| 22 | Badgers 2 | 1-2-3 | def. | Cyclones | 4-5-6 | ||
| 23 | Golden Eagles | 1-4-5 | def. | Gophers 2 | 2-3-6 | ||
| 24 | Gophers 1 | 1-2-6 | def. | Badgers 1 | 3-4-5 | ||
| 25 | Badgers 3 | 1-2-5 | def. | Badgers 4 | 3-4-6 | ||
| 26 | Panthers | 1-2-6 | def. | Golden Eagles | 3-4-5 | ||
| 27 | Badgers 2 | 2-4-6 | def. | Gophers 1 | 1-3-5 DSQ | ||
| 28 | Badgers 1 | 1-2-3 | def. | Gophers 2 | 4-5-6 | ||
| 29 | Badgers 4 | 1-2-3 | def. | Cyclones | 4-5-6 | ||
| 30 | Badgers 3 | 1-2-4 | def. | Golden Eagles | 3-5-6 | ||
| 31 | Panthers | 1-3-4 | def. | Gophers 2 | 2-5-6 | ||
| 32 | Badgers 1 | 1-2-3 | def. | Badgers 2 | 4-5-6 | ||
| 33 | Golden Eagles | 1-2-3 | def. | Cyclones | 4-5-6 | ||
| 34 | Gophers 1 | 1-2-6 | def. | Badgers 4 | 3-4-5 | ||
| 35 | Badgers 3 | 1-2-4 | def. | Gophers 2 | 3-5-6 | ||
| 36 | Badgers 1 | 1-2-4 | def. | Panthers | 3-5-6 | ||
| 37 | Badgers 2 | 1-2-6 | def. | Gophers 1 | 3-4-5 | ||
| 38 | Badgers 1 | 1-2-6 | def. | Gophers 1 | 3-4-5 | ||
| 39 | Badgers 1 | 1-2-5 | def. | Badgers 2 | 3-4-6 | ||
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 ±0.05 means a rating gap counts about 4% 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.