Harvard University '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: 74.69 percentile among ICSA crews with 30+ races. Uncertainty ±0.075 rating points from 340 races with rated skippers.
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 | 2.00 | unranked (fewer than 10 races or not active) | 24 | Fall 2017 |
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 |
|---|---|---|---|
| 1.82 (fleet 2.51) | unranked (fewer than 30 matches as skipper, or not active) | +0.00 about what the fleet rating predicts |
as crew 87–87 (50%) |
| Season | Regattas | Skipper W–L | Crew W–L |
|---|---|---|---|
| Spring 2020 | 2 | — | 13–17 |
| Spring 2019 | 5 | — | 39–41 |
| Spring 2018 | 4 | — | 27–17 |
| Fall 2017 | 1 | — | 2–4 |
| Spring 2017 | 1 | — | 6–8 |
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 13 graded regattas (174 matches) the record is 87–87 against 90.3 wins the pre-event forecasts expected (−3.3). 3 regattas clearly above the rating (P ≤ 20%), 6 clearly below (P ≥ 80%); 19 bits of surprise in all.
| Date | Regatta | Role | Value | Perf. | Record | Exp. wins |
Δ | Surprise (bits) |
P(this good or better) |
|---|---|---|---|---|---|---|---|---|---|
| 2020-03-07 | MIT FJ Team Racing Invite | crew | 2.53 | 1.38 | 8–12 | 12.2 | −1.14 | 3.4 | 99% |
| 2020-02-29 | Hap Moore Trophy | crew | 2.21 | 3.83 | 5–5 | 2.1 | +1.62 | 3.5 | 3% |
| 2019-04-06 | NEISA Team Race Championship | crew | 3.25 | 2.44 | 3–7 | 4.7 | −0.81 | 1.0 | 93% |
| 2019-03-30 | 38th Lynne Marchiando Trophy | crew | 3.19 | 4.35 | 9–5 | 5.4 | +1.17 | 3.0 | 4% |
| 2019-03-23 | Aaron Szambecki Team Race | crew | 3.58 | 3.18 | 10–11 | 11.7 | −0.40 | 0.5 | 86% |
| 2019-03-16 | Graham Hall | crew | 3.20 | 2.12 | 7–9 | 9.8 | −1.08 | 2.1 | 98% |
| 2019-03-02 | Bob Bavier Team Race | crew | 3.14 | 2.88 | 10–9 | 10.8 | −0.25 | 0.2 | 77% |
| 2018-03-24 | BC Team Race | crew | 2.98 | 3.39 | 12–3 | 11.0 | +0.42 | 0.3 | 40% |
| 2018-03-17 | Ike Geiger Team Race Trophy | crew | 3.03 | 3.08 | 2–1 | 2.0 | +0.04 | 0.0 | 73% |
| 2018-03-10 | Wood Trophy | crew | 2.88 | 3.80 | 12–5 | 8.8 | +0.92 | 2.0 | 8% |
| 2018-03-04 | Harvard Women's Team Race | crew | 1.89 | 0.12 | 1–8 | 3.3 | −1.77 | 2.6 | 99% |
| 2017-11-04 | Hap Moore Team Race | crew | 3.14 | 2.38 | 2–4 | 3.0 | −0.76 | 0.5 | 90% |
| 2017-03-25 | Duplin Women's Team Race | crew | 2.59 | 2.83 | 6–8 | 5.4 | +0.24 | 0.1 | 46% |
| League | Name | School | Year |
|---|---|---|---|
| ISSA | Jessica Williams |  Norfolk Academy |
'16 |
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
