Gulliver Preparatory School '19
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: 97.95 percentile among ICSA crews with 30+ races. Uncertainty ±0.081 rating points from 288 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 | University of Miami | 4.25 | 92.97 | 93.75 | 1 of 8 | 20 | Team page | |
| Spring 2023 | University of Miami | 4.40 | 94.33 | 91.67 | 1 of 6 | 11 | Team page | |
| Fall 2022 | University of Miami | 3.93 | 91.12 | 95.00 | 1 of 10 | 24 | Team page |
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 |
|---|---|---|---|
| 0.74 (fleet 1.20) | unranked (fewer than 30 matches as skipper, or not active) | +0.00 about what the fleet rating predicts |
as crew 20–30 (40%) |
| Season | Regattas | Skipper W–L | Crew W–L |
|---|---|---|---|
| Spring 2018 | 1 | — | 10–8 |
| Spring 2017 | 1 | — | 5–13 |
| Spring 2016 | 1 | — | 5–9 |
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 (50 matches) the record is 20–30 against 24.6 wins the pre-event forecasts expected (−4.6). 0 regattas clearly above the rating (P ≤ 20%), 2 clearly below (P ≥ 80%); 4 bits of surprise in all.
| Date | Regatta | Role | Value | Perf. | Record | Exp. wins |
Δ | Surprise (bits) |
P(this good or better) |
|---|---|---|---|---|---|---|---|---|---|
| 2018-05-05 | SAISA District Team Race Champs | crew | 2.26 | 2.55 | 10–8 | 9.2 | +0.29 | 0.1 | 44% |
| 2017-03-25 | SAISA Baker Qualifier | crew | 2.43 | 1.08 | 5–13 | 8.1 | −1.36 | 2.2 | 98% |
| 2016-04-30 | SAISA District Team Race Champs | crew | 2.17 | 1.07 | 5–9 | 7.3 | −1.10 | 1.4 | 96% |
| League | Name | School | Year |
|---|---|---|---|
| ICSA | Teddy Bueres |  University of Miami |
'24 |
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
To have this profile removed, email quinnbrighton2005@gmail.com.
