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2023 Intercollegiate Tech Dinghy Championship

SchoolSailor R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 TOT
Boston College Boston College Aidan Cunningham '26 3 1 7 2 10 3 3 6 8 2 45
Massachusetts Institute of Technology Massachusetts Institute of Technology Alexander Horne '26 9 5 4 4 6 5 4 5 3 9 54
Roger Williams University Roger Williams University Ian Hopkins Guerra '26 22 4 2 1 1 13 9 7 1 3 63
University of Rhode Island University of Rhode Island Willem Weinberg '24 20 2 3 8 4 1 11 2 13 1 65
Boston College Boston College John (Jack) Plavan '23 4 9 1 6 5 7 12 4 14 7 69
Boston College Boston College Jack Redmond '26 5 7 8 7 11 14 14 3 2 6 77
Dartmouth College Dartmouth College Michael Hanrahan '24 10 18 5 5 8 6 8 8 10 5 83
Boston College Boston College Graham Ness '23 6 6 13 3 13 8 6 13 6 11 85
Dartmouth College Dartmouth College Rob Mailley '24 18 17 10 10 3 4 16 11 11 10 110
University of Rhode Island University of Rhode Island Thomas Johnson '23 19 8 12 9 2 2 24 1 19 17 113
Dartmouth College Dartmouth College Christopher Long '23 12 24 6 13 7 15 2 14 18 4 115
Northeastern University Northeastern University Oliver Dietter '27 7 15 9 14 17 12 13 19 4 12 122
Boston College Boston College Cole Canuel '26 11 13 16 25 15 21 5 9 9 8 132
Northeastern University Northeastern University Reid Wishner '24 2 11 23 12 12 23 15 18 7 19 142
Roger Williams University Roger Williams University George Higham '23 1 21 22 23 9 11 19 RAF 5 15 152
Massachusetts Institute of Technology Massachusetts Institute of Technology Lucas Escandon '26 14 12 20 16 18 16 1 22 20 14 153
Dartmouth College Dartmouth College Connor Vogel '25 15 25 15 11 22 10 7 16 15 20 156
Roger Williams University Roger Williams University Hank Bailey '24 23 16 11 15 16 17 18 10 12 25 163
Tufts University Tufts University Blake Vogel '26 13 3 19 17 19 22 10 23 23 16 165
University of Rhode Island University of Rhode Island Tyler Miller '23 25 19 14 18 25 9 23 15 17 13 178
Roger Williams University Roger Williams University Ethan Burt '26 24 22 18 19 14 24 20 12 21 18 192
Northeastern University Northeastern University Aidan Boni '26 17 10 21 21 24 19 17 21 25 21 196
Tufts University Tufts University Meredith Broadus '25 8 14 24 22 21 25 21 17 24 22 198
Tufts University Tufts University Stefano Chiampo '26 16 23 25 20 20 18 22 20 22 24 210
Roger Williams University Roger Williams University Callum Robbins '22 21 20 17 24 23 20 25 24 16 23 213

Performance rating asks, for each skipper: holding every other boat fixed, which rating makes my actual race-by-race finishes least surprising? Boats are valued with the singlehanded rating rather than the fleet rating: 0.79 × the skipper's fleet rating from the week before the event (unrated skippers start at 1.11); the skipper's own singlehanded offset. Strength differences are scaled by 0.80 before they become probabilities, the value that calibrates the model on seasons it had not seen. Non-finishes (OCS, DNF and similar) are left out of the fitting, as in the rating model.

Percentile places a rating among the 309 ICSA sailors with a singlehanded rating who raced the discipline in the last three seasons. Surprise is how many bits more surprising the finishes were at the pre-event rating than at the performance rating. P(this good or better) simulates the event 3,000 times at the pre-event ratings, with the same regatta-form model as the fleet analysis pages, and reports how often the skipper would score this many points or fewer in the races they sailed.

The singlehanded offsets are the current ones (the discipline files keep no weekly history), so a skipper's own offset has already seen this event; offsets are shrunk hard, so the effect is a few hundredths at most. Only skippers are rated.

  • u no fleet rating — the model's level for unrated skippers is the baseline.

Division A  25 boats · 10 races

FinSkipperSchool Races Rating
before		 Perf.
rating		 Δ Percentile
before → perf.		 Surprise
(bits)		 P(this good
or better)		 Avg finish
actual / exp.
1Aidan Cunningham '26Boston College Eagles 410/102.504.03+1.5463rd → 95th6.61%4.5 / 10.2
2Alexander Horne '26Massachusetts Institute of Technology Engineers 110/102.503.77+1.2764th → 94th4.87%5.4 / 10.3
3Ian Hopkins Guerra '26Roger Williams University Hawks 310/102.792.97+0.1875th → 81st0.121%6.3 / 9.3
4Willem Weinberg '24University of Rhode Island Rams 310/101.073.15+2.0825th → 84th11.41%6.5 / 15.3
5John (Jack) Plavan '23Boston College Eagles 110/102.953.19+0.2581st → 85th0.233%6.9 / 8.8
6Jack Redmond '26Boston College Eagles 210/103.092.99−0.0983rd → 82nd0.047%7.7 / 8.3
7Michael Hanrahan '24Dartmouth College Big Green 210/101.912.91+0.9948th → 78th3.216%8.3 / 12.3
8Graham Ness '23Boston College Eagles 510/102.652.82+0.1770th → 77th0.141%8.5 / 9.7
9Rob Mailley '24Dartmouth College Big Green 410/101.542.33+0.7938th → 60th2.226%11.0 / 13.6
10Thomas Johnson '23University of Rhode Island Rams 210/101.651.82+0.1741st → 44th0.130%11.3 / 13.4
11Christopher Long '23Dartmouth College Big Green 110/101.851.91+0.0646th → 48th0.042%11.5 / 12.5
12Oliver Dietter '27Northeastern University Huskies 210/101.572.07+0.5039th → 54th0.937%12.2 / 13.6
13Cole Canuel '26Boston College Eagles 310/101.791.53−0.2644th → 38th0.356%13.2 / 12.8
14Reid Wishner '24Northeastern University Huskies 310/101.38u1.48+0.1133rd → 37th0.050%14.2 / 14.2
15George Higham '23Roger Williams University Hawks 410/102.031.42−0.6153rd → 34th1.680%15.2 / 12.0
16Lucas Escandon '26Massachusetts Institute of Technology Engineers 210/101.221.41+0.1929th → 34th0.155%15.3 / 14.8
17Connor Vogel '25Dartmouth College Big Green 310/101.351.22−0.1331st → 29th0.162%15.6 / 14.4
18Hank Bailey '24Roger Williams University Hawks 510/101.25u1.14−0.1129th → 25th0.067%16.3 / 14.5
19Blake Vogel '26Tufts University Jumbos 110/101.171.07−0.1027th → 25th0.064%16.5 / 15.0
20Tyler Miller '23University of Rhode Island Rams 110/101.500.68−0.8338th → 17th2.785%17.8 / 13.8
21Ethan Burt '26Roger Williams University Hawks 210/101.640.85−0.7940th → 19th3.194%19.2 / 13.3
22Aidan Boni '26Northeastern University Huskies 110/101.040.59−0.4524th → 15th0.988%19.6 / 15.4
23Meredith Broadus '25Tufts University Jumbos 210/101.270.42−0.8530th → 12th3.292%19.8 / 14.6
24Stefano Chiampo '26Tufts University Jumbos 310/100.630.46−0.1717th → 13th0.188%21.0 / 16.9
25Callum Robbins '22Roger Williams University Hawks 110/100.93u0.22−0.7121st → 10th2.095%21.3 / 15.7

Conditions — 04/22/2023 (8am–6pm)

☁️Overcast
Humidity 77%  ·  Pressure 1019.9 hPa

Temperature

49°F
↑ 52°F   ↓ 46°F
Feels like 42°F

Wind

● from   ▲ toward
10.8 kn
avg  ·  max 12.0 kn
Gusts to 22.5 kn
From E (83°)

Sky & Precipitation

Cloud cover100% Sunshine6.6 hrs Humidity77% Pressure1019.9 hPa

What this breeze does at MIT — from fleet racing

Breeze: E about 12 kn (weather reanalysis in the scorer’s units)
In fleet races at MIT in this breeze: a typical day (+0.02)
Nothing in this breeze favours either side in fleet racing here: results follow the ratings about as usual.

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 ±0.02 means a rating gap counts about 2% 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.

Orderliness beyond the fleet at MIT by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (112 labelled fleet-race days at MIT).

From the notes

Short write-ups of what the ratings and results show, with the numbers and how they were computed.

All notes →