PCCSC Match Race Championship

# SchoolTeam A TOT
1 Stanford University Stanford University Cardinal 1 1
2 University of California at Santa Barbara University of California at Santa Barbara Gauchos 2 2
3 Cal Poly University S.L.O. Cal Poly University S.L.O. Mustangs 3 3
4 California Maritime Academy California Maritime Academy Keelhaulers 4 4
SchoolTeam R1 TOT
Stanford University Stanford University Cardinal 1 1
University of California at Santa Barbara University of California at Santa Barbara Gauchos 2 2
Cal Poly University S.L.O. Cal Poly University S.L.O. Mustangs 3 3
California Maritime Academy California Maritime Academy Keelhaulers 4 4

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 keelboat rating rather than the fleet rating: 0.41 × the skipper's fleet rating from the week before the event (unrated skippers start at 0.47); 0.28 × the mean fleet rating of the rated crew aboard; the skipper's own keelboat offset; the school's program effect. Non-finishes (OCS, DNF and similar) are left out of the fitting, as in the rating model.

Percentile places a rating among the 207 ICSA sailors with a keelboat 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 keelboat 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.

  • — in the performance column: last in every race sailed, so no finite least-surprisal rating exists.

Division A  4 boats · 1 races

FinSkipperSchool Races Rating
before
Perf.
rating
Δ Percentile
before → perf.
Surprise
(bits)
P(this good
or better)
Avg finish
actual / exp.
1Thomas Sitzmann '27Stanford University1/12.847.00++4.1699th → 99th0.850%1.0 / 1.8
2Caleb Yoslov '25University of California at Santa Barbara1/11.292.80+1.5186th → 99th0.736%2.0 / 2.9
3Jack Kisling '25Cal Poly University S.L.O.1/11.241.74+0.5083rd → 94th0.163%3.0 / 2.9
4Ben Louttit '26California Maritime Academy1/11.87——97th → —2.8>99%4.0 / 2.5

Conditions — 10/14/2023 (8am–6pm)

☀️Clear sky
Humidity 39%  ·  Pressure 1016.9 hPa

Temperature

77°F
↑ 82°F   ↓ 63°F
Feels like 76°F

Wind

● from   ▲ toward
3.1 kn
avg  ·  max 4.8 kn
Gusts to 16.3 kn
From SW (222°)

Sky & Precipitation

Cloud cover0% Sunshine10.9 hrs Humidity39% Pressure1016.9 hPa

What this breeze does at UC Santa Barbara — from fleet racing

Breeze: SW about 6 kn (weather reanalysis in the scorer’s units)
In fleet races at UC Santa Barbara 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% 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 UC Santa Barbara by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (46 labelled fleet-race days at UC Santa Barbara).

From the notes

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

All notes →