Ranney 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: 30.10 percentile among ICSA crews with 30+ races. Uncertainty ±0.116 rating points from 11 races with rated skippers. Few races, so the estimate stays near the middle.
How crew ratings work →No season rating yet: needs 8+ crewed races in a season.
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 |
|---|---|---|---|---|
| Singlehanded | 3.28 | unranked (fewer than 10 races or not active) | 88 | Fall 2019 |
| Keelboat | 1.76 | unranked (fewer than 10 races or not active) | 4 | Fall 2022 |
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 |
|---|---|---|---|
| 2.63 (fleet 4.28) | unranked (fewer than 30 matches as skipper, or not active) | −0.01 ± 0.18 about what the fleet rating predicts |
as skipper 45–12 (79%) |
| Season | Regattas | Skipper W–L | Crew W–L |
|---|---|---|---|
| Spring 2019 | 3 | 20–11 | — |
| Fall 2018 | 1 | 10–0 | — |
| Fall 2017 | 2 | 15–1 | — |
Rating before each regatta driven (solid; dots green when the boat won 60% or more of its matches there, red under 40%) and what the fleet rating alone would give (dashed). The gap is the team race offset as it stood at the time. Hover a dot for the regatta; click to open it.
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 5 graded regattas (55 matches) the record is 43–12 against 43.8 wins the pre-event forecasts expected (−0.8). 1 regatta clearly above the rating (P ≤ 20%), 2 clearly below (P ≥ 80%); 7 bits of surprise in all.
| Date | Regatta | Role | Value | Perf. | Record | Exp. wins |
Δ | Surprise (bits) |
P(this good or better) |
|---|---|---|---|---|---|---|---|---|---|
| 2019-04-27 | MASSA Team Race Championship (Baker Qualifier) | skipper | 2.77 | 1.59 | 12–9 | 14.8 | −1.18 | 1.9 | 97% |
| 2019-04-08 | NJISA 2019 Spring Team Race Qualifier | skipper | 2.68 | 1.33 | 6–2 | 7.1 | −1.35 | 0.9 | 95% |
| 2018-09-30 | NJISA Fall Team Champs | skipper | 2.82 | 5.82 | 10–0 | 9.3 | ≥+3.00 | 1.0 | 46% |
| 2017-10-15 | NJISA 2017 Fall Team Race Qualifer | skipper | 2.37 | 5.37 | 11–0 | 8.6 | ≥+3.00 | 3.7 | 6% |
| 2017-10-04 | NJISA Fall TEAM 1 | skipper | 2.31 | 2.38 | 4–1 | 4.0 | +0.07 | 0.0 | 73% |
| League | Name | School | Year |
|---|---|---|---|
| ICSA | Cameron Giblin |  Tulane University |
'23 |
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
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