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SAISA Fall Coed Dinghy Championship — Analysis

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* This regatta is not official yet. Ratings marked * are from the last weekly update and have not absorbed this event; the performance columns use the results posted so far, and everything refreshes as scoring is finalised.

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 (2015-W44). 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 2,501 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.

Division A  12 boats · 12 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 Charles Rees '16 College of Charleston 12/12 423* 440 +17 99th → 99th 0.1 25% 2.0 / 2.6 423*
2 Jason D'Agostino '17 Eckerd College 12/12 324* 416 +92 92nd → 99th 3.8 4% 2.4 / 4.1 327*
3 Daniel Lawless '17 Jacksonville University 12/12 291* 355 +64 87th → 95th 2.1 10% 3.3 / 4.7 294*
4 Andrew Baird '18 University of South Florida 12/12 304* 288 -16 89th → 87th 0.2 48% 4.3 / 4.5 304*
5 John Roberts '17 Clemson University 12/12 231* 305 +74 75th → 89th 3.0 17% 4.6 / 5.9 232*
6 Marten Kendrick '15 Georgia Institute of Technology 9/12 191* 198 +6 68th → 69th 0.0 63% 7.0 / 6.6 191*
6 Conner Killham '18 Georgia Institute of Technology 3/12 186* 227 +41 66th → 75th 0.3 49% 6.7 / 6.8 186*
7 Cassie Todd '16 University of North Carolina at Wilmington 12/12 89* 163 +74 43rd → 61st 2.8 12% 7.2 / 8.6 91*
8 Benjamin Ringrose '19 University of Miami 6/12 97* 227 +130 45th → 75th 4.3 12% 6.2 / 8.3 98*
8 Max Thompson '19 University of Miami 6/12 185* 93 -92 66th → 44th 3.2 98% 9.8 / 6.8 185*
9 Alexander Katsis '14 Duke University 6/12 91* 96 +4 44th → 45th 0.0 64% 9.0 / 8.5 91*
9 John Sipp '18 Duke University 6/12 121* 214 +94 51st → 72nd 2.5 29% 7.2 / 8.2 120*
10 Mark Thompson '18 North Carolina State University 12/12 145* 102 -42 57th → 47th 1.2 89% 9.1 / 7.6 141*
12 Ryan Welch '16 Davidson College 12/12 -62* -45 +17 12th → 16th 0.1 86% 11.6 / 10.7 -62*

Division B  12 boats · 12 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 Ryan Davidson '16 College of Charleston 12/12 395* 459 +64 98th → 99th 1.6 9% 1.8 / 2.9 397*
2 Sean Cornell '18 University of South Florida 12/12 379* 405 +26 98th → 99th 0.3 20% 2.3 / 3.2 385*
3 Timothy Siemers '16 Eckerd College 9/12 294* 388 +94 87th → 98th 3.1 6% 2.8 / 4.6 301*
3 Andrew Schoene '18 Eckerd College 3/12 297* 349 +52 88th → 95th 0.4 33% 3.3 / 4.5 298*
4 Stephan Verhulst '19 Jacksonville University 10/12 279* 307 +27 85th → 89th 0.3 27% 3.8 / 4.9 281*
4 Peter Steo '19 Jacksonville University 2/12 270* 186 -84 83rd → 66th 0.9 79% 6.5 / 5.0 270*
5 Kyle Magno '18 University of Miami 12/12 196* 203 +6 69th → 70th 0.0 41% 6.0 / 6.4 196*
6 Abbie Probst '19 Clemson University 12/12 119* 175 +56 51st → 64th 1.9 29% 7.1 / 8.0 122*
7 Kara Wheeler '18 North Carolina State University 12/12 114* 176 +62 49th → 64th 2.3 26% 7.2 / 8.0 117*
8 Kailey Savacool '16 University of North Carolina at Wilmington 12/12 132* 145 +13 54th → 57th 0.1 59% 8.0 / 7.7 133*
9 Vincent Miao '18 Duke University 12/12 149* 123 -26 58th → 52nd 0.4 77% 8.3 / 7.4 146*
10 Joshua Kim '17 Georgia Institute of Technology 6/12 79* 67 -13 41st → 39th 0.0 72% 9.7 / 8.7 78*
10 Jack Sparkman '19 Georgia Institute of Technology 3/12 111* 195 +84 49th → 68th 1.0 33% 7.0 / 8.1 111*
10 Stuart Wallace '18 Georgia Institute of Technology 3/12 115* 171 +56 50th → 63rd 0.5 39% 7.3 / 8.1 126*
11 Clifford Gilman '19 Davidson College 12/12 55* 82 +27 37th → 41st 0.4 80% 10.2 / 9.1 54*

From the notes

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

All notes →