PCCSC Men's Singlehanded Champs

SchoolSailor R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 TOT
Stanford University Stanford University Oliver Toole '14 4 5 2 2 1 3 4 1 3 3 2 1 31
University of California at Santa Barbara University of California at Santa Barbara Stephen Long '17 2 6 3 1 2 4 2 3 2 1 3 3 32
Stanford University Stanford University Mateo Vargas '14 3 1 4 4 4 2 1 2 4 2 4 2 33
Stanford University Stanford University Kieran Chung '15 1 2 1 3 5 5 6 4 1 4 1 5 38
University of California at Santa Barbara University of California at Santa Barbara Keenan Chung '18 5 10 7 7 7 1 7 5 9 5 6 6 75
University of California at Berkeley University of California at Berkeley Jacob Hiew '15 7 4 8 9 3 8 3 9 11 10 5 7 84
University of Hawaii University of Hawaii Mackenzie Cook '17 10 3 6 8 8 6 5 12 6 8 8 11 91
University of Southern California University of Southern California Cameron Hutcheson '14 9 8 5 6 6 12 9 6 5 6 9 13 94
University of California at Irvine University of California at Irvine Nicholas Weis '15 6 7 11 12 10 9 8 8 8 9 7 4 99
University of Hawaii University of Hawaii Giacomo Paoletti '15 8 11 9 10 14 11 12 13 7 7 10 10 122
University of California at San Diego University of California at San Diego John Olson '14 14 9 10 11 9 10 13 14 13 11 12 8 134
University of California at Los Angeles University of California at Los Angeles Robert Loughnan '15 11 12 13 13 13 13 10 11 12 13 11 9 141
University of Southern California University of Southern California Brandon Yuen '14 13 13 12 14 12 7 11 10 14 12 13 12 143
University of California at San Diego University of California at San Diego Tyler Wooldridge '14 12 DNF DNF 5 11 15 15 7 10 14 14 14 149
University of California at San Diego University of California at San Diego Jiachao Yang '15 15 14 DNF 15 15 14 14 15 15 15 15 15 178

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.

Division A  15 boats · 12 races

FinSkipperSchool Races Rating
before
Perf.
rating
Δ Percentile
before → perf.
Surprise
(bits)
P(this good
or better)
Avg finish
actual / exp.
1Oliver Toole '14Stanford University Cardinal12/123.114.32+1.2284th → 98th4.53%2.6 / 4.8
2Stephen Long '17University of California at Santa Barbara Gauchos 112/122.904.27+1.3878th → 98th5.75%2.7 / 5.3
3Mateo Vargas '14Stanford University White12/123.104.15+1.0584th → 97th3.48%2.8 / 4.9
4Kieran Chung '15Stanford University Red12/123.313.73+0.4288th → 93rd0.617%3.2 / 4.5
5Keenan Chung '18University of California at Santa Barbara Gauchos 212/121.742.25+0.5043rd → 59th1.028%6.2 / 7.5
6Jacob Hiew '15University of California at Berkeley12/121.061.91+0.8524th → 48th2.818%7.0 / 8.9
7Mackenzie Cook '17University of Hawaii Rainbow Wahine12/121.161.78+0.6227th → 44th1.629%7.6 / 8.7
8Cameron Hutcheson '14University of Southern California Trojans 112/122.181.53−0.6557th → 38th2.173%7.8 / 6.6
9Nicholas Weis '15University of California at Irvine12/120.981.47+0.4922nd → 37th1.034%8.2 / 9.1
10Giacomo Paoletti '15University of Hawaii Rainbows12/121.610.69−0.9240th → 17th4.388%10.2 / 7.8
11John Olson '14University of California at San Diego Tritons 112/121.330.30−1.0331st → 11th5.593%11.2 / 8.3
12Robert Loughnan '15University of California at Los Angeles12/12-0.580.31+0.882nd → 11th2.845%11.8 / 11.8
13Brandon Yuen '14University of Southern California Trojans 212/120.170.03−0.149th → 6th0.174%11.9 / 10.6
14Tyler Wooldridge '14University of California at San Diego Tritons 212/121.03-0.52−1.5624th → 2nd8.397%12.4 / 8.9
15Jiachao Yang '15University of California at San Diego Tritons 312/12-0.85-2.61−1.751st → 1st4.3>99%14.8 / 12.3

Conditions — 10/26/2013 (8am–6pm)

☁️Overcast
Humidity 64%  ·  Pressure 1016.4 hPa

Temperature

71°F
↑ 76°F   ↓ 59°F
Feels like 71°F

Wind

● from   ▲ toward
4.9 kn
avg  ·  max 8.7 kn
Gusts to 15.6 kn
From WSW (242°)

Sky & Precipitation

Cloud cover92% Sunshine10.8 hrs Humidity64% Pressure1016.4 hPa

What this breeze does at Southern Cal — from fleet racing

Breeze: SW about 8 kn (weather reanalysis in the scorer’s units)
In fleet races at Southern Cal in this breeze: a typical day (−0.01)
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 ±0.01 means a rating gap counts about 1% 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.

Orderliness beyond the fleet at Southern Cal by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (only 8 labelled days at Southern Cal, so the surface is mostly the all-venue pattern).

From the notes

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

All notes →