| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | Harvard University | Crimson 2 | 13–0 | |
| 2 | Brown University | Bears | 8–5 | |
| 3 | Harvard University | Crimson 1 | 6–7 | |
| 4 | Boston College | Eagles | 4–9 | |
| 5 | University of Rhode Island | Rams | 9–4 | |
| 6 | Massachusetts Institute of Technology | Engineers 1 | 7–6 | |
| 7 | Northeastern University | Huskies | 5–8 | |
| 8 | Massachusetts Institute of Technology | Engineers 2 | 0–13 |
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 16,901 team race matches sailed before 2022-03-19, using the line-ups that actually raced. It called 53 of 62 matches (86%) with a log-loss of 0.399 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.42 ± 0.25: 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.
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 | Harvard University Crimson 2 | 9.41 | 12.41 | 13–0 | 9.8 | ≥+3.00 | 5.5 | 2% |
| 5 | University of Rhode Island Rams | 7.47 | 7.76 | 10–7 | 9.1 | +0.29 | 0.2 | 41% |
| 4 | Boston College Eagles | 7.38 | 7.67 | 6–11 | 5.2 | +0.29 | 0.2 | 41% |
| 7 | Northeastern University Huskies | 6.67 | 6.71 | 5–8 | 4.9 | +0.03 | 0.0 | 60% |
| 2 | Brown University Bears | 9.23 | 8.97 | 12–5 | 12.8 | −0.26 | 0.1 | 78% |
| 6 | Massachusetts Institute of Technology Engineers 1 | 7.27 | 6.96 | 7–10 | 8.0 | −0.32 | 0.2 | 80% |
| 3 | Harvard University Crimson 1 | 8.79 | 8.21 | 9–8 | 10.8 | −0.57 | 0.7 | 91% |
| 8 | Massachusetts Institute of Technology Engineers 2 | 5.32 | 2.32 | 0–13 | 1.5 | ≤−3.00 | 2.2 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Dylan Ascencios | Harvard University | 3.06 | 6.06 | 13–0 | 9.8 | ≥+3.00 | 5.5 | 2% |
| Eric Hansen | Harvard University | 2.66 | 5.66 | 13–0 | 9.8 | ≥+3.00 | 5.5 | 2% |
| Jonas Nelle | Harvard University | 3.20 | 6.20 | 13–0 | 9.8 | ≥+3.00 | 5.5 | 2% |
| Kerem Erkmen | University of Rhode Island | 3.15 | 3.44 | 10–7 | 9.1 | +0.29 | 0.2 | 41% |
| Zachary Champney | University of Rhode Island | 2.29 | 2.58 | 10–7 | 9.1 | +0.29 | 0.2 | 41% |
| Chip Kreuzkamp | Boston College | 1.91 | 2.20 | 6–11 | 5.2 | +0.29 | 0.2 | 41% |
| Joshua Dillon | Northeastern University | 2.00 | 2.04 | 5–8 | 4.9 | +0.03 | 0.0 | 60% |
| Cordelia Burn | Harvard University | 2.45 | 1.88 | 9–8 | 10.8 | −0.57 | 0.7 | 91% |
| Sarah Burn | Harvard University | 2.91 | 2.34 | 9–8 | 10.8 | −0.57 | 0.7 | 91% |
| Emily Mueller | Brown University | 2.07 | 1.19 | 2–1 | 2.4 | −0.89 | 0.3 | 92% |
| Max Katz-Christy | Massachusetts Institute of Technology | 1.83 | -1.17 | 0–13 | 1.5 | ≤−3.00 | 2.2 | >99% |
| Raymond Huffman | Massachusetts Institute of Technology | 1.04 | -1.96 | 0–13 | 1.5 | ≤−3.00 | 2.2 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | 2 | Bears | 1 | Eagles | Rams | 1 | Huskies | 2 | |
|---|---|---|---|---|---|---|---|---|---|---|
| Harvard University Crimson 2 | 14–4 | ✕ | L | ✕ | W | W | W | W | W | |
| Brown University Bears | 8–3 | W | ✕ | W | W | W | W | W | W | |
| Harvard University Crimson 1 | 14–4 | ✕ | L | ✕ | W | W | W | W | W | |
| Boston College Eagles | 6–5 | L | L | L | ✕ | W | W | W | W | |
| University of Rhode Island Rams | 7–7 | L | L | L | L | ✕ | L | W | L | |
| Massachusetts Institute of Technology Engineers 1 | 6–18 | L | L | L | L | W | ✕ | L | ✕ | |
| Northeastern University Huskies | 3–7 | L | L | L | L | L | W | ✕ | W | |
| Massachusetts Institute of Technology Engineers 2 | 6–18 | L | L | L | L | W | ✕ | L | ✕ |
| Team | Rec. | Rams | 1 | Huskies | 2 | |
|---|---|---|---|---|---|---|
| University of Rhode Island Rams | 3–0 | ✕ | W | W | W | |
| Massachusetts Institute of Technology Engineers 1 | 1–5 | L | ✕ | L | ✕ | |
| Northeastern University Huskies | 2–1 | L | W | ✕ | W | |
| Massachusetts Institute of Technology Engineers 2 | 1–5 | L | ✕ | L | ✕ |
| Team | Rec. | 2 | Bears | 1 | Eagles | |
|---|---|---|---|---|---|---|
| Harvard University Crimson 2 | 8–4 | ✕ | W | ✕ | W | |
| Brown University Bears | 4–2 | L | ✕ | L | W | |
| Harvard University Crimson 1 | 8–4 | ✕ | W | ✕ | W | |
| Boston College Eagles | 0–6 | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Crimson 2 | 1-2-6 | def. | Engineers 1 | 3-4-5 | ||
| 2 | Crimson 1 | 1-2-3 | def. | Engineers 2 | 4-5-6 | ||
| 3 | Bears | 1-3-6 | def. | Huskies | 2-4-5 | ||
| 4 | Eagles | 1-2-5 | def. | Rams | 3-4-6 | ||
| 5 | Crimson 2 | 1-2-5 | def. | Crimson 1 | 3-4-6 | ||
| 6 | Engineers 1 | 1-2-6 | def. | Bears | 3-4-5 | ||
| 7 | Rams | 1-2-4 DSQ | def. | Engineers 2 | 3-5-6 DSQ | ||
| 8 | Eagles | 1-2-5 | def. | Huskies | 3-4-6 RAF | ||
| 9 | Bears | 1-2-5 | def. | Crimson 1 | 3-4-6 | ||
| 10 | Crimson 2 | 1-3-5 | def. | Rams | 2-4-6 | ||
| 11 | Engineers 1 | 1-2-5 | def. | Huskies | 3-4-6 | ||
| 12 | Eagles | 1-2-5 | def. | Engineers 2 | 3-4-6 | ||
| 13 | Rams | 1-3-4 | def. | Bears | 2-5-6 | ||
| 14 | Crimson 1 | 2-3-4 | def. | Huskies | 1-5-6 | ||
| 15 | Crimson 2 | 1-2-3 | def. | Engineers 2 | 4-5-6 | ||
| 16 | Engineers 1 | 2-3-4 | def. | Eagles | 1-5-6 | ||
| 17 | Rams | 1-2-3 | def. | Huskies | 4-5-6 | ||
| 18 | Bears | 1-2-5 | def. | Engineers 2 | 3-4-6 | ||
| 19 | Crimson 1 | 1-2-5 | def. | Engineers 1 | 3-4-6 | ||
| 20 | Crimson 2 | 1-2-3 | def. | Eagles | 4-5-6 | ||
| 21 | Huskies | 1-2-6 | def. | Engineers 2 | 3-4-5 | ||
| 22 | Rams | 1-2-3 | def. | Engineers 1 | 4-5-6 | ||
| 23 | Crimson 2 | 1-2-5 | def. | Bears | 3-4-6 | ||
| 24 | Eagles | 2-3-5 | def. | Crimson 1 | 1-4-6 | ||
| 25 | Engineers 1 | 1-2-4 | def. | Engineers 2 | 3-5-6 | ||
| 26 | Crimson 2 | 1-2-3 | def. | Huskies | 4-5-6 | ||
| 27 | Crimson 1 | 1-2-5 | def. | Rams | 3-4-6 | ||
| 28 | Bears | 2-3-5 | def. | Eagles | 1-4-6 | ||
| 29 | Eagles | 2-3-4 | def. | Rams | 1-5-6 | ||
| 30 | Bears | 1-3-5 | def. | Crimson 1 | 2-4-6 | ||
| 31 | Rams | 1-2-6 | def. | Engineers 1 | 3-4-5 | ||
| 32 | Crimson 1 | 1-3-4 | def. | Eagles | 2-5-6 | ||
| 33 | Bears | 1-2-5 | def. | Engineers 1 | 3-4-6 | ||
| 34 | Crimson 1 | 2-3-4 | def. | Rams | 1-5-6 | ||
| 35 | Bears | 1-2-5 | def. | Eagles | 3-4-6 | ||
| 36 | Crimson 1 | 1-2-5 | def. | Engineers 1 | 3-4-6 | ||
| 37 | Bears | 1-2-5 | def. | Rams | 3-4-6 | ||
| 38 | Eagles | 1-2-4 | def. | Engineers 1 | 3-5-6 | ||
| 41 | Engineers 1 | 1-2-6 | def. | Engineers 2 | 3-4-5 | ||
| 42 | Rams | 2-3-4 | def. | Huskies | 1-5-6 | ||
| 49 | Huskies | 1-2-6 | def. | Engineers 1 | 3-4-5 | ||
| 50 | Rams | 1-3-4 | def. | Engineers 2 | 2-5-6 | ||
| 57 | Huskies | 1-2-4 | def. | Engineers 2 | 3-5-6 | ||
| 58 | Engineers 1 | 2-3-5 | def. | Rams | 1-4-6 | ||
| 45 | Engineers 1 | 1-2-5 | def. | Engineers 2 | 3-4-6 | ||
| 46 | Rams | 1-2-3 | def. | Huskies | 4-5-6 | ||
| 53 | Huskies | 2-3-4 | def. | Engineers 1 | 1-5-6 | ||
| 54 | Rams | 1-2-6 | def. | Engineers 2 | 3-4-5 | ||
| 61 | Huskies | 1-2-5 | def. | Engineers 2 | 3-4-6 | ||
| 62 | Rams | 1-2-4 | def. | Engineers 1 | 3-5-6 | ||
| 39 | Bears | 1-3-4 | def. | Crimson 1 | 2-5-6 | ||
| 40 | Crimson 2 | 1-2-4 | def. | Eagles | 3-5-6 | ||
| 43 | Bears | 1-2-6 | def. | Crimson 1 | 3-4-5 | ||
| 44 | Crimson 2 | 1-2-3 | def. | Eagles | 4-5-6 | ||
| 47 | Bears | 1-2-4 | def. | Eagles | 3-5-6 | ||
| 48 | Crimson 2 | 1-2-4 | def. | Crimson 1 | 3-5-6 | ||
| 51 | Bears | 1-2-6 | def. | Eagles | 3-4-5 | ||
| 52 | Crimson 2 | 1-2-4 | def. | Crimson 1 | 3-5-6 | ||
| 55 | Crimson 1 | 1-2-4 | def. | Eagles | 3-5-6 | ||
| 56 | Crimson 2 | 1-2-4 | def. | Bears | 3-5-6 | ||
| 59 | Crimson 1 | 2-3-4 | def. | Eagles | 1-5-6 | ||
| 60 | Crimson 2 | 1-2-5 | def. | Bears | 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 ±0.06 means a rating gap counts about 5% 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.