Oyster Bowl Coed — Analysis

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Performance rating answers one question for each skipper: holding every other skipper's rating fixed, which rating makes my actual race-by-race finishes least surprising? It is the maximum-likelihood rating under the same Plackett–Luce model that produces the power rankings (how accurate it is), with each opponent fixed at their rating from the last rated week before this event (2026-W41). Substitute skippers are scored only on the races they sailed, and races the boat did not finish (OCS, DNF and similar) are left out.

Percentile places a rating among the 2,053 ICSA skippers who were rated within the year before this event, so it reads as “better than X% of the skippers racing in this league right now”. The arrow shows where the sailor stood going in and where this performance would put them.

Surprise is how many bits more surprising the sailor's finishes were at their pre-event rating than at their performance rating (0 = exactly as expected). P(this good or better) simulates the regatta 3,000 times with the sailor at their pre-event rating against the actual fleet, and reports how often they would score this many points or fewer in the races they skippered. Races in one regatta are not independent, so each simulation also gives every skipper a good or bad regatta, form that drifts from race to race, and the speed of each boat the rotation puts them in (why). Low means an unusually good regatta, high means an unusually poor one. It deliberately ignores how rivals actually sailed, so it agrees with the performance rating rather than with the division finish, which also depends on everyone else's day. Ratings are shown on the rankings scale (model rating × 100). Only skippers are rated; crews are not part of the model.

Combined divisions  14 boats · 14 races

Fin Skipper School Races Rating
before
Perf.
rating
Δ Percentile
before → perf.
Surprise
(bits)
P(this good
or better)
Avg finish
actual / exp.
Rating
after
1 Cole Fanchi '30 U. S. Naval Academy Midshipmen B 14/14 299 365 +66 87th → 94th 2.9 14% 4.9 / 7.1 300
2 Umi Noritake '28 U. S. Naval Academy Midshipmen A 14/14 362 333 -28 94th → 92nd 0.7 69% 6.1 / 5.4 362
3 Ryan D’Orsi '30 University of Pennsylvania Quakers B 14/14 285 331 +46 85th → 92nd 1.6 33% 6.2 / 7.4 285
4 Nathan Finkelstein '30 Fordham University Rams B 14/14 277 304 +27 85th → 88th 0.5 38% 7.0 / 7.7 277
5 Jason Folvig '30 Hobart and William Smith Colleges Statesmen B 14/14 264 311 +48 83rd → 89th 1.6 36% 7.1 / 8.0 264
6 Conrad Cook '29 Georgetown University Hoyas B 14/14 298 307 +9 87th → 88th 0.1 52% 7.1 / 7.1 297
7 James Kopack '28 Hobart and William Smith Colleges Statesmen A 14/14 314 288 -26 89th → 86th 0.5 62% 7.2 / 6.7 314
8 Esme Gonzalez '28 University of Pennsylvania Quakers A 14/14 266 275 +8 83rd → 84th 0.0 40% 7.4 / 8.0 267
9 Erickson Rankin '27 Fordham University Rams A 14/14 294 265 -28 87th → 83rd 0.6 58% 7.6 / 7.2 294
10 David Karcher '30 Old Dominion University Monarchs B 14/14 212 286 +74 75th → 85th 3.8 26% 8.1 / 9.4 212
11 Stone Dewey '30 Old Dominion University Monarchs A 14/14 265 249 -16 83rd → 81st 0.2 64% 8.7 / 8.0 265
12 Davide Bazzoni '30 St. Mary's College of Maryland Seahawks A 14/14 331 233 -98 92nd → 78th 8.6 90% 8.8 / 6.2 331
13 Jake Julien '28 Georgetown University Hoyas A 14/14 257 246 -11 82nd → 80th 0.1 62% 9.0 / 8.2 265
14 Scott Opert '28 St. Mary's College of Maryland Seahawks B 14/14 240 240 +0 80th → 80th 0.0 74% 9.9 / 8.7 238