Corona del Mar High School '20
How much better or worse boats do with this sailor crewing than their skipper's rating predicts, shown on the skipper scale so crews can be lined up across teams. Percentiles compare against rostered crews that season (league) or teammates (team).
How crew ratings work →Crew effect over their whole career, not scaled to a team: 63.14 percentile among ICSA crews with 30+ races. Uncertainty ±0.087 rating points from 185 races with rated skippers.
How crew ratings work →Includes linked high school and college seasons.
| Season | Team | Rating | Range | League percentile |
Team percentile |
On team | Races | Team page |
|---|---|---|---|---|---|---|---|---|
| Spring 2024 | Harvard University | 4.34 | 93.56 | 68.75 | 3 of 8 | 48 | Team page | |
| Fall 2023 | Harvard University | 4.29 | 93.44 | 83.33 | 3 of 15 | 76 | Team page | |
| Spring 2023 | Harvard University | 3.83 | 88.39 | 68.18 | 4 of 11 | 11 | Team page |
Each discipline has its own scale, built from the sailor's main rating and their results in that discipline. The numbers are not comparable with the main rating or with each other.
How these ratings work →| Discipline | Rating | Rank | Races | Last raced |
|---|---|---|---|---|
| Keelboat | 1.48 | unranked (fewer than 10 races or not active) | 13 | Fall 2021 |
A team race rating is what the sailor brings to one of the three boats: 0.72 x their fleet rating plus a team-race offset learned from every match they sailed, shrunk toward zero so a few matches cannot move it far. Sides are compared by the sum of their three boats plus the school's team race strength.
| Rating | Rank | vs fleet rating | Record |
|---|---|---|---|
| 2.23 (fleet 3.60) | unranked (fewer than 30 matches as skipper, or not active) | −0.00 ± 0.18 about what the fleet rating predicts |
as skipper 2–6 (25%) as crew 4–7 (36%) |
| Season | Regattas | Skipper W–L | Crew W–L |
|---|---|---|---|
| Spring 2019 | 1 | 2–6 | — |
| Spring 2018 | 2 | — | 4–7 |
For each regatta, the boat value that would have made this sailor's record least surprising: the shift applied to their boat alone, in the matches they sailed, with team-mates and opponents fixed at the pre-event forecast. A boat's skipper and crew share the boat, so they get the same number when they sailed every match together. Surprise is in bits at the pre-event value minus at the performance value; P(this good or better) treats the matches as independent at the forecast probabilities. Regattas forecast from fewer than 1,000 training matches are left out.
Over 3 graded regattas (19 matches) the record is 6–13 against 7.1 wins the pre-event forecasts expected (−1.1). 0 regattas clearly above the rating (P ≤ 20%), 1 clearly below (P ≥ 80%); 0 bits of surprise in all.
| Date | Regatta | Role | Value | Perf. | Record | Exp. wins |
Δ | Surprise (bits) |
P(this good or better) |
|---|---|---|---|---|---|---|---|---|---|
| 2019-04-27 | 2019 PCISA Team Race Championships | skipper | 2.15 | 1.53 | 2–6 | 2.6 | −0.62 | 0.2 | 84% |
| 2018-05-26 | High School Team Racing Nationals - Baker Trophy | crew | 2.31 | 1.87 | 2–4 | 2.4 | −0.44 | 0.1 | 79% |
| 2018-04-28 | PCISA Team Racing PCCs | crew | 2.20 | 2.10 | 2–3 | 2.1 | −0.10 | 0.0 | 78% |
| League | Name | School | Year |
|---|---|---|---|
| ICSA | Marbella Marlo |  Harvard University |
'24 |
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
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