| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Brown University | Bears 1 | 5–1 |
| 2 |  |
University of Rhode Island | Rams 1 | 4–2 |
| 3 | |
Brown University | Bears 2 | 2–4 |
| 4 | |
University of Rhode Island | Rams 2 | 1–5 |
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 15,606 team race matches sailed before 2021-04-24, using the line-ups that actually raced. It called 9 of 12 matches (75%) with a log-loss of 0.461 (a coin flip scores 0.693), so the event went about as expected for the forecast. Orderliness +0.04 ± 0.51: a typical event, more orderly than 46% 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 | Brown University Bears 1 | 1 | 10.32 school +0.24, home +0.36 | Olivia Belda / Annabelle Hutchinson 3.37 Tucker Weed / Madeleine Montagner 2.92 Jack Murphy / Madeleine Mcgrath 3.40 4–0 Jack Murphy / Emma Montgomery 3.47 1–1 | 87% | 5–1 (83%) | −0.2 |
| 2 | University of Rhode Island Rams 1 | 2 | 9.17 school −0.18 | Luke Ingalls / Caitlin Abel 3.33 Michael O'Flaherty / Maguire Bennett 2.86 Aidan Naughton / Taylor Borges 3.15 | 61% | 4–2 (67%) | +0.4 |
| 3 | Brown University Bears 2 | 3 | 8.04 school +0.24, home +0.36 | Caroline Bayless / Nora Ong Elizabeth Rolfes / Justin Chiang 2.09 1–3 Hunter Zonnenberg / Catherine Mcclenahan 2.34 1–3 Elizabeth Rolfes / Izzy Cox 2.13 1–1 Hunter Zonnenberg / Mo Liu 2.36 1–1 | 32% | 2–4 (33%) | +0.1 |
| 4 | University of Rhode Island Rams 2 | 4 | 7.57 school −0.18 | Parker Colantuono / Clare Laroche 2.76 Ben Rosenberg / Katie Coughlin 2.58 Zachary Champney / Emilia Marino 2.34 | 20% | 1–5 (17%) | −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) |
|---|---|---|---|---|---|---|---|---|
| 2 | University of Rhode Island Rams 1 | 9.17 | 9.54 | 4–2 | 3.6 | +0.36 | 0.1 | 58% |
| 3 | Brown University Bears 2 | 8.04 | 8.14 | 2–4 | 1.9 | +0.10 | 0.0 | 65% |
| 4 | University of Rhode Island Rams 2 | 7.57 | 7.30 | 1–5 | 1.2 | −0.28 | 0.0 | 77% |
| 1 | Brown University Bears 1 | 10.32 | 10.00 | 5–1 | 5.2 | −0.32 | 0.1 | 83% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Michael O'Flaherty | University of Rhode Island | 2.86 | 3.22 | 4–2 | 3.6 | +0.36 | 0.1 | 58% |
| Aidan Naughton | University of Rhode Island | 3.15 | 3.52 | 4–2 | 3.6 | +0.36 | 0.1 | 58% |
| Ben Rosenberg | University of Rhode Island | 2.58 | 2.31 | 1–5 | 1.2 | −0.28 | 0.0 | 77% |
| Zachary Champney | University of Rhode Island | 2.34 | 2.07 | 1–5 | 1.2 | −0.28 | 0.0 | 77% |
| Olivia Belda | Brown University | 3.37 | 3.05 | 5–1 | 5.2 | −0.32 | 0.1 | 83% |
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 Rhode Island Rams 1 | Brown University Bears 2 | 76% | |
| 1 | 2 | Brown University Bears 1 | University of Rhode Island Rams 2 | 94% | |
| 1 | 3 | University of Rhode Island Rams 1 | University of Rhode Island Rams 2 | 84% | |
| 1 | 4 | Brown University Bears 1 | Brown University Bears 2 | 91% | |
| 1 | 5 | Brown University Bears 2 | University of Rhode Island Rams 2 | 62% | |
| 1 | 6 | Brown University Bears 1 | University of Rhode Island Rams 1 | 77% | |
| 2 | 7 | Brown University Bears 2 | University of Rhode Island Rams 1 | 24% | upset |
| 2 | 8 | Brown University Bears 1 | University of Rhode Island Rams 2 | 94% | |
| 2 | 9 | University of Rhode Island Rams 1 | University of Rhode Island Rams 2 | 83% | |
| 2 | 10 | Brown University Bears 1 | Brown University Bears 2 | 91% | |
| 2 | 11 | University of Rhode Island Rams 2 | Brown University Bears 2 | 39% | upset |
| 2 | 12 | University of Rhode Island Rams 1 | Brown University Bears 1 | 23% | upset |
| Team | Rec. | 1 | 1 | 2 | 2 | |
|---|---|---|---|---|---|---|
| Brown University Bears 1 | 4–2 | ✕ | W | ✕ | W |
| University of Rhode Island Rams 1 | 2–4 | L | ✕ | L | ✕ |
| Brown University Bears 2 | 4–2 | ✕ | W | ✕ | W |
| University of Rhode Island Rams 2 | 2–4 | L | ✕ | L | ✕ |
| Team | Rec. | 1 | 1 | 2 | 2 | |
|---|---|---|---|---|---|---|
| Brown University Bears 1 | 3–3 | ✕ | L | ✕ | L |
| University of Rhode Island Rams 1 | 3–3 | W | ✕ | W | ✕ |
| Brown University Bears 2 | 3–3 | ✕ | L | ✕ | L |
| University of Rhode Island Rams 2 | 3–3 | W | ✕ | W | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Rams 1 | 1-2-3 | def. | |
Bears 2 | 4-5-6 |
| 2 | |
Bears 1 | 1-2-5 | def. | |
Rams 2 | 3-4-6 |
| 3 | |
Rams 1 | 1-2-3 | def. | |
Rams 2 | 4-5-6 |
| 4 | |
Bears 1 | 2-3-4 | def. | |
Bears 2 | 1-5-6 |
| 5 | |
Bears 2 | 1-2-6 | def. | |
Rams 2 | 3-4-5 |
| 6 | |
Bears 1 | 1-2-5 | def. | |
Rams 1 | 3-4-6 |
| 7 | |
Bears 2 | 1-2-4 | def. | |
Rams 1 | 3-5-6 |
| 8 | |
Bears 1 | 1-2-3 | def. | |
Rams 2 | 4-5-6 |
| 9 | |
Rams 1 | 1-2-3 | def. | |
Rams 2 | 4-5-6 |
| 10 | |
Bears 1 | 1-2-4 | def. | |
Bears 2 | 3-5-6 |
| 11 | |
Rams 2 | 2-3-4 | def. | |
Bears 2 | 1-5-6 |
| 12 | |
Rams 1 | 1-3-4 | def. | |
Bears 1 | 2-5-6 |
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
|
Brown University | Bears 1 | Jack Murphy '22 Olivia Belda '22 Tucker Weed '22 |
Emma Montgomery '22 Madeleine Mcgrath '22 Annabelle Hutchinson '21 Madeleine Montagner '22 |
|
University of Rhode Island | Rams 1 | Aidan Naughton '22 Luke Ingalls '21 Michael O'Flaherty '21 |
Taylor Borges '22 Caitlin Abel '21 Maguire Bennett '21 |
|
Brown University | Bears 2 | Caroline Bayless '23 Elizabeth Rolfes '21 Hunter Zonnenberg '23 |
Nora Ong '23 Justin Chiang '21 Izzy Cox '23 Catherine Mcclenahan '21 Mo Liu '22 |
|
University of Rhode Island | Rams 2 | Ben Rosenberg '23 Parker Colantuono '22 Zachary Champney '22 |
Katie Coughlin '24 Clare Laroche '23 Emilia Marino '22 |
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 ±0.09 means a rating gap counts about 8% 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.
