SAISA North Top 6 Invite — 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-W37). 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 1,767 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.

  • n no rating before this event — the model's estimate from this week is used as the baseline.
  • — in the performance column means the skipper finished last in every race they sailed, so no finite least-surprisal rating exists.

Division A  6 boats · 8 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 John Lieber '30 College of Charleston 8/8 247 293 +47 84th90th 0.5 >99% 4.6 / 2.1 251
2 Mitchell Hnatt '28 Clemson University 8/8 214 182 -33 80th74th 0.3 >99% 6.6 / 2.4 212
3 Olivia Burdette '29 North Carolina State University 8/8 89 130 +41 57th65th 0.5 >99% 8.4 / 3.6 92
5 Henry Elmore '29 University of South Carolina 8/8 59 57 -3 51st51st 0.0 >99% 10.8 / 3.9 56
6 Noah Essick '30 University of North Carolina at Wilmington 8/8 -144 31 +175 13th46th 6.0 >99% 11.4 / 5.4 -136

Division B  6 boats · 8 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 Connor Jewett '30 College of Charleston 8/8 240 340 +101 83rd94th 2.0 96% 3.4 / 2.3 244
2 Adam Nilsson '29 North Carolina State University 8/8 160 278 +118 71st88th 3.8 91% 3.9 / 3.0 174
3 Ian Richardson '29 Clemson University 8/8 207 221 +14 78th81st 0.1 98% 4.0 / 2.6 204
4 Sarah Plants '29 University of South Carolina 8/8 11 143 +132 42nd67th 5.6 >99% 11.5 / 4.3 9
5 Olivia Anderson '29 University of North Carolina at Wilmington 8/8 -197 37 +234 5th47th 9.8 >99% 14.6 / 5.6 -199

Division C  6 boats · 8 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 Viggo Westerlind '30 College of Charleston 8/8 207n 284 +77 78th89th 1.2 98% 4.8 / 2.6 207
2 Luke Adams '28 Clemson University 8/8 147 196 +48 68th77th 0.6 >99% 5.6 / 3.0 154
4 Lyla Solway '28 North Carolina State University 8/8 131 99 -32 65th59th 0.3 >99% 8.5 / 3.2 129
5 Molly Loring '28 University of South Carolina 8/8 86 42 -44 57th48th 0.5 >99% 10.1 / 3.6 77
6 Lulu Riesenberg '28 University of North Carolina at Wilmington 4/8 -96n 22nd 1.4 >99% 16.5 / 5.1 -96