University of California at Los Angeles
| Regatta | Type | Finish |
|---|---|---|
| Stoney Burke | Fleet Race | 4 / 16 |
| Stoney Burke JV | Fleet Race | 8 / 14 |
| UCSD Open | Fleet Race | 5 / 13 |
| Frosh-Soph | Fleet Race | 4 / 11 |
| Kiara Arai |
| Max Pearson |
| Selin Posacioglu |
| Alice Tang |
| Colin Cheng |
| Connor Soelburg |
| Elizabeth Li |
| Ella Andrzejek |
| Keira Klein |
| Shai Osorio |
| Weston Otterson |
| Abby Krause |
| Emre Gurdal |
| Eric Zhou |
| Stav Aroeti |
| Thomas Rudowicz |
| Carl Eskilstorp |
| Justine Reynolds |
| Kevin Lu |
| Mary Lucia Howald |
| Rigel Mummers |
| Sam Yu |
| Torkel Johansson |
| Lachlan Gillies |
| # | Skipper | Rating | League percentile |
Team percentile |
Races |
|---|---|---|---|---|---|
| 1 | Thomas Rudowicz | 3.09 | 87.86 | 94.44 | 17 |
| 2 | Carl Eskilstorp | 1.74 | 63.90 | 83.33 | 15 |
| 3 | Rigel Mummers | 1.11 | 50.94 | 72.22 | 10 |
| 4 | Sam Yu | 0.01 | 30.52 | 61.11 | 6 |
| 5 | Kevin Lu | -0.12 | 27.77 | 50.00 | 15 |
| 6 | Shai Osorio | -0.24 | 25.96 | 38.89 | 4 |
| 7 | Colin Cheng | -0.32 | 24.86 | 27.78 | 6 |
| 8 | Weston Otterson | -0.53 | 20.07 | 16.67 | 6 |
| 9 | Emre Gurdal | -0.66 | 17.32 | 5.56 | 7 |
Skippers with at least 4 rated boat-races this season, ranked by their rating after their last race of the season. Percentiles count ties as half.
Weekly rating of every skipper on the roster across their whole career so far, one point per week their rating moved. By class year lines every graduating class up at the start of its freshman year, so each class sits one year further left than the one after it. Hover a line to isolate it.
| # | Crew | Rating | Range The dot is the rating. The shaded band is where it plausibly sits (90% range): a wide band means little evidence, and bands that overlap mean the crews cannot be told apart. The dashed line is the team's skipper average. Ratings are on the skipper scale and crews on one team differ far less than skippers do, so use them to compare crews across teams, not to rank within a team. How crew ratings work → |
League percentile |
Team percentile |
Races |
|---|---|---|---|---|---|---|
| 1 | Mary Lucia Howald | 0.88 | 39.61 | 90.00 | 17 | |
| 2 | Connor Soelburg* | 0.68 | 33.99 | 70.00 | 8 | |
| 3 | Lachlan Gillies | 0.63 | 32.50 | 50.00 | 9 | |
| 4 | Max Pearson* | 0.50 | 30.38 | 30.00 | 12 | |
| 5 | Ella Andrzejek | -0.53 | 12.57 | 10.00 | 11 |
| Crew* | Rating | Range The dot is the rating. The shaded band is where it plausibly sits (90% range): a wide band means little evidence, and bands that overlap mean the crews cannot be told apart. The dashed line is the team's skipper average. Ratings are on the skipper scale and crews on one team differ far less than skippers do, so use them to compare crews across teams, not to rank within a team. How crew ratings work → |
Races this season | Career races |
|---|---|---|---|---|
| Alice Tang* | – | not enough data to rate | 2 | 17 |
| Justine Reynolds* | – | not enough data to rate | 6 | 6 |
| Kiara Arai* | – | not enough data to rate | 5 | 5 |
| Torkel Johansson* | – | not enough data to rate | 6 | 6 |
| Keira Klein* | – | not enough data to rate | 2 | 3 |
| Abby Krause* | – | not enough data to rate | 6 | 6 |
| Eric Zhou* | -0.26 | 5 | 19 | |
| Elizabeth Li* | – | not enough data to rate | 1 | 1 |
Crews are only compared through the skippers they have shared. A skipper's boats do a little better or worse than their rating predicts depending on who is crewing, and the rating is built from those differences. Each big blue dot is a crew on this roster, each small square a skipper they have sailed with, and each line a pairing: blue pushes the crew up, orange pushes them down, thicker means more racing behind it. Click a crew or a skipper.
Loading…
Ranked crews have at least 8 races this season; * means low evidence (under 8 races this season, or under 30 career races with rated skippers). Ratings are on the skipper scale (×18.7 the crew effect). League percentile also reflects how strong the team's skippers are.
Short write-ups of what the ratings and results show, with the numbers and how they were computed.