| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Tufts University | Jumbos | 7–1 |
| 2 |  |
Brown University | Bears | 6–2 |
| 3 |  |
University of Rhode Island | Rams | 6–2 |
| 4 |  |
Northeastern University | Huskies | 5–3 |
| 5 |  |
Boston University | Terriers | 4–4 |
| 6 |  |
Massachusetts Institute of Technology | Engineers 2 | 3–5 |
| 7 |  |
U. S. Coast Guard Academy | Bears | 3–5 |
| 8 |  |
Roger Williams University | Hawks | 2–6 |
| 9 | |
Massachusetts Institute of Technology | Engineers 1 | 0–8 |
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 16,723 team race matches sailed before 2022-03-12, using the line-ups that actually raced. It called 22 of 34 matches (65%) with a log-loss of 0.661 (a coin flip scores 0.693), so the event went poorly for the forecast. Orderliness −0.65 ± 0.31: an upset-heavy event, more orderly than 7% 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) |
|---|---|---|---|---|---|---|---|---|
| 5 | Boston University Terriers | 5.44 | 7.57 | 4–4 | 1.1 | +2.14 | 5.0 | 1% |
| 4 | Northeastern University Huskies | 6.59 | 7.72 | 4–3 | 2.7 | +1.13 | 1.1 | 20% |
| 6 | Massachusetts Institute of Technology Engineers 2 | 6.95 | 7.81 | 3–2 | 2.4 | +0.87 | 0.4 | 40% |
| 1 | Tufts University Jumbos | 8.69 | 9.30 | 6–1 | 5.5 | +0.60 | 0.2 | 52% |
| 3 | University of Rhode Island Rams | 7.71 | 8.13 | 5–3 | 4.4 | +0.42 | 0.2 | 47% |
| 2 | Brown University Bears | 8.88 | 8.69 | 7–2 | 7.3 | −0.19 | 0.0 | 76% |
| 8 | Roger Williams University Hawks | 7.06 | 5.77 | 2–5 | 3.3 | −1.30 | 1.2 | 97% |
| 7 | U. S. Coast Guard Academy Bears | 8.04 | 6.18 | 3–6 | 6.2 | −1.86 | 4.4 | >99% |
| 9 | Massachusetts Institute of Technology Engineers 1 | 5.17 | 2.17 | 0–8 | 1.2 | ≤−3.00 | 2.2 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Max Katz-Christy | Massachusetts Institute of Technology | 1.69 | 4.69 | 3–0 | 1.3 | ≥+3.00 | 4.4 | 3% |
| Elliott Mendenhall | Boston University | 2.17 | 4.30 | 4–4 | 1.1 | +2.14 | 5.0 | 1% |
| Nick Hardy | Boston University | 0.74 | 2.88 | 4–4 | 1.1 | +2.14 | 5.0 | 1% |
| Tiare Sierra | Boston University | 2.20 | 4.33 | 4–4 | 1.1 | +2.14 | 5.0 | 1% |
| Joshua Dillon | Northeastern University | 1.94 | 3.08 | 4–3 | 2.7 | +1.13 | 1.1 | 20% |
| Will Priebe | Northeastern University | 2.35 | 3.49 | 4–3 | 2.7 | +1.13 | 1.1 | 20% |
| Patrick Mulcahy | Tufts University | 2.65 | 3.25 | 6–1 | 5.5 | +0.60 | 0.2 | 52% |
| Kerem Erkmen | University of Rhode Island | 3.10 | 3.52 | 5–3 | 4.4 | +0.42 | 0.2 | 47% |
| Jed Bell | Brown University | 2.98 | 2.78 | 7–2 | 7.3 | −0.19 | 0.0 | 76% |
| Raymond Huffman | Massachusetts Institute of Technology | 1.02 | -1.98 | 0–6 | 0.5 | ≤−3.00 | 0.7 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Jumbos | Bears | Rams | Huskies | Terriers | 2 | Bears | Hawks | 1 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Tufts University Jumbos | 7–1 | ✕ | W | L | W | W | W | W | W | W |
| Brown University Bears | 6–2 | L | ✕ | W | W | W | W | L | W | W |
| University of Rhode Island Rams | 6–2 | W | L | ✕ | L | W | W | W | W | W |
| Northeastern University Huskies | 5–3 | L | L | W | ✕ | W | W | W | L | W |
| Boston University Terriers | 4–4 | L | L | L | L | ✕ | W | W | W | W |
| Massachusetts Institute of Technology Engineers 2 | 4–13 | L | L | L | L | L | ✕ | W | L | ✕ |
| U. S. Coast Guard Academy Bears | 3–6 | L | W | L | L | L | L | ✕ | W | L |
| Roger Williams University Hawks | 2–6 | L | L | L | W | L | W | L | ✕ | W |
| Massachusetts Institute of Technology Engineers 1 | 4–13 | L | L | L | L | L | ✕ | W | L | ✕ |
| Team | Rec. | Bears | Rams | |
|---|---|---|---|---|
| Brown University Bears | 1–0 | ✕ | W |
| University of Rhode Island Rams | 0–1 | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Engineers 2 | 1-2-4 | def. | |
Engineers 1 | 3-5-6 |
| 2 | |
Huskies | 1-2-5 | def. | |
Bears | 3-4-6 |
| 3 | |
Terriers | 1-3-4 | def. | |
Hawks | 2-5-6 |
| 4 | |
Jumbos | 1-2-6 | def. | |
Bears | 3-4-5 |
| 5 | |
Rams | 1-2-3 | def. | |
Engineers 1 | 4-5-6 |
| 6 | |
Engineers 2 | 1-2-5 | def. | |
Bears | 3-4-6 |
| 7 | |
Huskies | 1-2-5 | def. | |
Terriers | 3-4-6 |
| 8 | |
Bears | 1-2-4 | def. | |
Hawks | 3-5-6 |
| 9 | |
Rams | 1-2-4 | def. | |
Jumbos | 3-5-6 |
| 10 | |
Bears | 2-3-4 | def. | |
Engineers 1 | 1-5-6 |
| 11 | |
Terriers | 1-2-4 | def. | |
Engineers 2 | 3-5-6 |
| 12 | |
Bears | 2-5-6 | def. | |
Huskies | 1-3-4 DSQ |
| 13 | |
Jumbos | 1-2-5 | def. | |
Hawks | 3-4-6 |
| 14 | |
Rams | 2-3-5 | def. | |
Bears | 1-4-6 |
| 15 | |
Terriers | 1-2-3 | def. | |
Engineers 1 | 4-5-6 |
| 16 | |
Bears | 2-4-5 | def. | |
Engineers 2 | 1-3-6 DSQ |
| 17 | |
Jumbos | 1-2-3 | def. | |
Huskies | 4-5-6 |
| 18 | |
Rams | 1-2-5 | def. | |
Hawks | 3-4-6 |
| 19 | |
Terriers | 2-3-5 | def. | |
Bears | 1-4-6 |
| 20 | |
Bears | 1-2-3 | def. | |
Engineers 1 | 4-5-6 |
| 21 | |
Jumbos | 1-2-3 | def. | |
Engineers 2 | 4-5-6 |
| 22 | |
Hawks | 1-2-6 | def. | |
Huskies | 3-4-5 DSQ |
| 23 | |
Rams | 1-2-4 | def. | |
Terriers | 3-5-6 |
| 24 | |
Bears | 2-3-5 | def. | |
Bears | 1-4-6 |
| 25 | |
Jumbos | 1-2-3 | def. | |
Engineers 1 | 4-5-6 |
| 26 | |
Engineers 2 | 1-3-6 | def. | |
Hawks | 2-4-5 |
| 27 | |
Huskies | 1-3-5 | def. | |
Rams | 2-4-6 |
| 28 | |
Bears | 1-2-6 | def. | |
Terriers | 3-4-5 |
| 29 | |
Jumbos | 1-3-6 | def. | |
Bears | 2-4-5 |
| 30 | |
Hawks | 1-2-5 | def. | |
Engineers 1 | 3-4-6 |
| 31 | |
Huskies | 1-3-6 | def. | |
Engineers 2 | 2-4-5 |
| 32 | |
Bears | 1-2-4 | def. | |
Rams | 3-5-6 |
| 33 | |
Jumbos | 1-2-5 | def. | |
Terriers | 3-4-6 |
| 34 | |
Bears | 1-2-3 | def. | |
Hawks | 4-5-6 |
| 35 | |
Huskies | 1-2-4 | def. | |
Engineers 1 | 3-5-6 |
| 36 | |
Rams | 1-3-5 | def. | |
Engineers 2 | 2-4-6 |
| 38 | |
Engineers 2 | 1-2-5 | def. | |
Bears | 3-4-6 |
| 37 | |
Bears | 1-2-3 | def. | |
Rams | 4-5-6 |
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 ±0.04 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.
