University of Pennsylvania '17
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: 24.44 percentile among ICSA crews with 30+ races. Uncertainty ±0.111 rating points from 29 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.
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 |
|---|---|---|---|
| 1.31 (fleet 1.81) | unranked (fewer than 30 matches as skipper, or not active) | −0.00 ± 0.18 about what the fleet rating predicts |
as skipper 3–12 (20%) as crew 2–15 (12%) |
| Season | Regattas | Skipper W–L | Crew W–L |
|---|---|---|---|
| Spring 2017 | 2 | 3–12 | 1–1 |
| Spring 2015 | 1 | — | 1–14 |
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 2 graded regattas (30 matches) the record is 4–26 against 5.8 wins the pre-event forecasts expected (−1.8). 0 regattas clearly above the rating (P ≤ 20%), 1 clearly below (P ≥ 80%); 2 bits of surprise in all.
| Date | Regatta | Role | Value | Perf. | Record | Exp. wins |
Δ | Surprise (bits) |
P(this good or better) |
|---|---|---|---|---|---|---|---|---|---|
| 2017-03-18 | Washington College Team Race | skipper | 1.58 | 0.62 | 3–12 | 5.5 | −0.96 | 1.6 | 96% |
| 2015-03-21 | Graham Hall Team Race | crew | 1.14 | 2.43 | 1–14 | 0.3 | +1.29 | 0.8 | 27% |
| Regatta | Role | Div | Races | Avg | Rating |
|---|---|---|---|---|---|
| Spring 2017 Team page Season | |||||
| Washington College Team Race | Skipper | TR | 15 | 20% | — |
| Sperry Women's Western Semifinal Women's | Crew | B | 2 | 10.0 | — |
| MAISA Team Race Challenge | Crew | TR | 14 | 36% | — |
| Fall 2016 Team page Season | |||||
| Women's Atlantic Coast Championship Women's | Crew | B | 11 | 12.2 | — |
| Kings Point Dinghy Open | Skipper | A | 15 | 13.1 | 1.64 |
| Central Fall Qualifier | Skipper | B | 8 | 6.0 | 1.79 |
| Spring 2016 Team page Season | |||||
| Villanova Spring Open | Skipper | A | 6 | 6.0 | 1.09 |
| Sperry Women's Eastern Semifinal Women's | Skipper | A | 13 | 13.2 | 1.66 |
| MAISA Women’s Championship Women's | Skipper | A | 11 | 8.5 | 1.79 |
| Spring 2015 Team page Season | |||||
| OCC Spring Open | Skipper | B | 9 | 3.3 | 1.37 |
| MAISA Women's Dinghy Championships Women's | Skipper | A | 12 | 11.5 | 1.05 |
| Graham Hall Team Race | Crew | TR | 15 | 7% | — |
| Gill Coed Western Semifinals | Crew | B | 4 | 12.5 | — |
| Fall 2014 Team page Season | |||||
| Navy Fall | Skipper | D | 11 | 18.3 | -0.27 |
| KP Dinghy Open | Crew | A | 12 | 9.5 | — |
| Central Fall Qualifer | Skipper | B | 6 | 5.0 | 1.60 |
| Spring 2014 Team page Season | |||||
| OCC Spring Open | Skipper | A | 10 | 4.8 | 1.31 |
| MAISA Women's Championship Women's | Skipper | A | 14 | 11.9 | 0.34 |
| Fall 2013 Team page Season | |||||
| Maritime Fall Open | Skipper | B | 12 | 5.8 | 2.06 |
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
