| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
Lake Forest High School | Scouts | 9–0 |
| 2 |  |
Saint Ignatius College Prep, Chicago, IL | Wolfpack | 8–1 |
| 3 |  |
New Trier HS | Trevian | 6–3 |
| 4 |  |
Grosse Pointe South High School | Blue Devils | 5–4 |
| 5 |  |
Minnetonka High School | Skippers | 5–4 |
| 6 |  |
West Bloomfield High School | Lakers Varsity | 4–5 |
| 7 |  |
Latin School of Chicago | Romans | 3–6 |
| 8 |  |
University of Chicago Laboratory Schools | Maroons | 3–6 |
| 9 |  |
Troy High School | Troy | 1–8 |
| 10 |  |
Sheboygan North High School (WI) | Raiders | 1–8 |
Each side is the sum of its three boats (the skipper's fleet rating times 0.72 plus a team race offset learned from their past matches, plus the crew's offset and a small experience term) plus the school's team race strength and a home-water edge for the host. The win probability is a logistic function of the difference. The forecast was made before the event: the model was refitted on every match sailed before the first day, with fleet ratings as of the week before.
Fitted on the 9,849 team race matches sailed before 2023-05-06, using the line-ups that actually raced. It called 38 of 45 matches (84%) with a log-loss of 0.446 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.35 ± 0.36: a typical event, more orderly than 65% of high school team race events (temperature of the forecast log-odds that best fits the results, relative to the league average; nothing about the field, venue or wind predicts it, see the Weather tab). vs forecast is a team's wins minus the wins the model expected from the matches it sailed: positive means it beat its rating.
For each side, the performance strength is the value that would have made its record least surprising: the strength at which the model's expected wins over exactly these opponents equal the actual wins, with every opponent fixed at its pre-event strength. For a skipper, the same shift is applied only to their boat in the matches they sailed, with team-mates and opponents fixed; team-mates who sailed every match together therefore get the same number. Surprise is in bits: -log2 of the probability of the record at the pre-event strength minus the same at the performance strength. P(this good or better) treats matches as independent coin flips at the model's pre-event probabilities, so it ignores form within the day; read it as a rough guide.
Pre-event strength against the strength that would have made each record least surprising, everything else fixed. Δ is in the model's logit units, the same scale as the boat values above (a side is three boats plus the school term); green is a clear over-performance, red a clear under-performance. Skippers need three or more matches.
| Place | School | Strength | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| 1 | Lake Forest High School | 7.92 | 10.92 | 9–0 | 8.0 | ≥+3.00 | 1.4 | 34% |
| 2 | Saint Ignatius College Prep, Chicago, IL | 5.90 | 8.32 | 8–1 | 5.7 | +2.42 | 2.8 | 7% |
| 3 | New Trier HS | 4.73 | 6.31 | 6–3 | 3.8 | +1.58 | 1.9 | 10% |
| 6 | West Bloomfield High School | 4.65 | 4.87 | 4–5 | 3.7 | +0.22 | 0.0 | 55% |
| 5 | Minnetonka High School | 5.72 | 5.59 | 5–4 | 5.2 | −0.13 | 0.0 | 70% |
| 7 | Latin School of Chicago | 4.42 | 4.28 | 3–6 | 3.2 | −0.14 | 0.0 | 69% |
| 4 | Grosse Pointe South High School | 6.25 | 5.34 | 5–4 | 6.2 | −0.91 | 0.6 | 91% |
| 8 | University of Chicago Laboratory Schools | 5.43 | 4.23 | 3–6 | 4.7 | −1.20 | 1.1 | 95% |
| 10 | Sheboygan North High School (WI) | 3.58 | 2.33 | 1–8 | 2.1 | −1.25 | 0.7 | 92% |
| 9 | Troy High School | 3.79 | 2.27 | 1–8 | 2.4 | −1.52 | 1.1 | 95% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Charlie Gish | Lake Forest High School | 2.80 | 5.80 | 9–0 | 8.0 | ≥+3.00 | 1.4 | 34% |
| Avery Baldwin | Saint Ignatius College Prep, Chicago, IL | 2.18 | 4.60 | 8–1 | 5.7 | +2.42 | 2.8 | 7% |
| Aiala Angueira Salbidegoitia | New Trier HS | 1.50 | 3.08 | 6–3 | 3.8 | +1.58 | 1.9 | 10% |
| Izzy Rietz | New Trier HS | 1.51 | 3.09 | 6–3 | 3.8 | +1.58 | 1.9 | 10% |
| Evy Engebretson | Minnetonka High School | 1.51 | 1.38 | 5–4 | 5.2 | −0.13 | 0.0 | 70% |
| Domenic Sacchetti | Latin School of Chicago | 0.57 | 0.43 | 3–6 | 3.2 | −0.14 | 0.0 | 69% |
| Bryan Pan | University of Chicago Laboratory Schools | 1.33 | 0.13 | 3–6 | 4.7 | −1.20 | 1.1 | 95% |
| David Ren | University of Chicago Laboratory Schools | 1.93 | 0.73 | 3–6 | 4.7 | −1.20 | 1.1 | 95% |
| Frank Ribich | Sheboygan North High School (WI) | 1.40 | 0.15 | 1–8 | 2.1 | −1.25 | 0.7 | 92% |
| Owen Smith | Sheboygan North High School (WI) | 1.14 | -0.11 | 1–8 | 2.1 | −1.25 | 0.7 | 92% |
| Nat Green | Sheboygan North High School (WI) | 0.35 | -0.89 | 1–8 | 2.1 | −1.25 | 0.7 | 92% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Blue Devils | 1-2-5 | def. | |
Maroons | 3-4-6 |
| 2 | |
Scouts | 1-2-3 | def. | |
Troy | 4-5-6 |
| 3 | |
Wolfpack | 1-2-3 | def. | |
Romans | 4-5-6 |
| 4 | |
Skippers | 1-2-6 | def. | |
Raiders | 3-4-5 |
| 5 | |
Trevian | 2-3-4 | def. | |
Lakers Varsity | 1-5-6 |
| 6 | |
Maroons | 1-2-4 | def. | |
Troy | 3-5-6 |
| 7 | |
Wolfpack | 1-2-3 | def. | |
Blue Devils | 4-5-6 |
| 8 | |
Scouts | 1-2-3 | def. | |
Raiders | 4-5-6 |
| 9 | |
Trevian | 1-2-4 | def. | |
Romans | 3-5-6 |
| 10 | |
Lakers Varsity | 2-3-4 | def. | |
Skippers | 1-5-6 |
| 11 | |
Wolfpack | 1-2-5 | def. | |
Troy | 3-4-6 |
| 12 | |
Maroons | 1-2-3 | def. | |
Raiders | 4-5-6 |
| 13 | |
Trevian | 1-3-6 | def. | |
Blue Devils | 2-4-5 |
| 14 | |
Scouts | 2-3-4 | def. | |
Skippers | 1-5-6 |
| 15 | |
Lakers Varsity | 2-3-4 | def. | |
Romans | 1-5-6 |
| 16 | |
Wolfpack | 1-2-3 | def. | |
Raiders | 4-5-6 |
| 17 | |
Trevian | 1-4-5 | def. | |
Troy | 2-3-6 |
| 18 | |
Skippers | 1-2-5 | def. | |
Maroons | 3-4-6 |
| 19 | |
Blue Devils | 1-2-5 | def. | |
Romans | 3-4-6 |
| 20 | |
Scouts | 1-2-3 | def. | |
Lakers Varsity | 4-5-6 |
| 21 | |
Trevian | 1-2-6 | def. | |
Raiders | 3-4-5 |
| 22 | |
Wolfpack | 1-2-3 | def. | |
Skippers | 4-5-6 |
| 23 | |
Romans | 1-2-3 | def. | |
Troy | 4-5-6 |
| 24 | |
Scouts | 1-2-4 | def. | |
Maroons | 3-5-6 |
| 25 | |
Lakers Varsity | 1-3-5 | def. | |
Blue Devils | 2-4-6 |
| 26 | |
Skippers | 1-4-5 | def. | |
Trevian | 2-3-6 |
| 27 | |
Romans | 1-2-3 | def. | |
Raiders | 4-5-6 |
| 28 | |
Scouts | 2-3-4 | def. | |
Wolfpack | 1-5-6 |
| 29 | |
Blue Devils | 1-2-4 | def. | |
Troy | 3-5-6 |
| 30 | |
Maroons | 1-2-4 | def. | |
Lakers Varsity | 3-5-6 |
| 31 | |
Skippers | 1-3-5 | def. | |
Romans | 2-4-6 |
| 32 | |
Scouts | 1-2-4 | def. | |
Trevian | 3-5-6 |
| 33 | |
Blue Devils | 1-2-4 | def. | |
Raiders | 3-5-6 |
| 34 | |
Wolfpack | 1-2-5 | def. | |
Maroons | 3-4-6 |
| 35 | |
Lakers Varsity | 1-2-3 | def. | |
Troy | 4-5-6 |
| 36 | |
Scouts | 1-3-4 | def. | |
Romans | 2-5-6 |
| 37 | |
Blue Devils | 1-2-5 | def. | |
Skippers | 3-4-6 |
| 38 | |
Trevian | 1-2-6 | def. | |
Maroons | 3-4-5 |
| 39 | |
Troy | 1-4-5 | def. | |
Raiders | 2-3-6 |
| 40 | |
Wolfpack | 1-2-6 | def. | |
Lakers Varsity | 3-4-5 |
| 41 | |
Scouts | 1-2-4 | def. | |
Blue Devils | 3-5-6 |
| 42 | |
Romans | 2-3-4 | def. | |
Maroons | 1-5-6 |
| 43 | |
Skippers | 1-2-6 | def. | |
Troy | 3-4-5 |
| 44 | |
Wolfpack | 1-2-5 | def. | |
Trevian | 3-4-6 |
| 45 | |
Raiders | 1-2-6 | def. | |
Lakers Varsity | 3-4-5 |
Orderliness is how tightly a fleet race’s finishing order follows the pre-regatta ratings, relative to a typical event (0): positive is the favourites’ day, negative the underdogs’. A value of ±0.00 means a rating gap counts about 1% more than on a typical day. This event is not a fleet race the rating model scores, so there is no actual value for it: this is what this venue’s fleet racing history says about the breeze on the day, read off the chart at the star. How this is estimated · compare venues.
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
