| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 | University of North Texas | Mean Green | 8–0 | |
| 2 | University of Texas | Longhorns | 5–3 | |
| 3 | Texas A&M University | Aggies | 4–4 | |
| 4 | Texas A&M University at Galveston | Aggies | 3–5 | |
| 5 | University of Central Oklahoma | Bronchos | 0–8 |
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 18,929 team race matches sailed before 2023-02-04, using the line-ups that actually raced. It called 13 of 14 matches (93%) with a log-loss of 0.366 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.33 ± 0.52: a typical event, more orderly than 78% of college 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.
| Place | School | Pred. | Strength | Boats (skipper / crew, boat value) | Pred. win % | Record | vs forecast |
|---|---|---|---|---|---|---|---|
| 1 | University of North Texas Mean Green | 2 | 3.53 school +0.14 | Dutch Byerly / Alana Babilonia 2.32 Taylor Snyder / Alaya Weekley 0.89 Timothy Verriere / Gage Hendrickson | 70% | 8–0 (100%) | +2.4 |
| 2 | University of Texas Longhorns | 1 | 3.49 school +0.06, home +0.37 | John Mason / Leigha Forrest 1.70 Etienne Black / Warren Wegener Thomas Norman / Sireen Kenana 0.93 3–1 Thomas Norman / Delilah D'Souza 0.95 0–2 | 74% | 3–3 (50%) | −1.4 |
| 3 | Texas A&M University Aggies | 3 | 2.34 school −0.11 | Kate Hennig / Katy Heaney Hanna Progelhof / Andrew Pool Ryyan Amsden / Maggie Menefee | 46% | 3–3 (50%) | +0.2 |
| 4 | Texas A&M University at Galveston Aggies | 4 | 3.37 school −0.10 | Jacob Granberry / Brett Pearson Emma Stodghill Joshua Richie | 46% | 0–2 (0%) | −0.9 |
| 5 | University of Central Oklahoma Bronchos | 5 | 0.15 | Catherine Bruce / Branden Mercer Caleb Vanderburg / Jayson Raj Peyton Miller | 5% | 0–6 (0%) | −0.3 |
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 | University of North Texas | 3.53 | 6.53 | 8–0 | 5.6 | ≥+3.00 | 4.3 | 4% |
| 3 | Texas A&M University | 2.34 | 2.57 | 3–3 | 2.8 | +0.23 | 0.0 | 60% |
| 2 | University of Texas | 3.49 | 2.13 | 3–3 | 4.4 | −1.36 | 1.4 | 97% |
| 5 | University of Central Oklahoma | 0.15 | -2.85 | 0–6 | 0.3 | ≤−3.00 | 0.4 | >99% |
| 4 | Texas A&M University at Galveston | 3.37 | 0.37 | 0–2 | 0.9 | ≤−3.00 | 1.7 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Taylor Snyder | University of North Texas | 0.89 | 3.89 | 8–0 | 5.6 | ≥+3.00 | 4.3 | 4% |
| Timothy Verriere | University of North Texas | 0.05 | 3.05 | 8–0 | 5.6 | ≥+3.00 | 4.3 | 4% |
| Hanna Progelhof | Texas A&M University | 0.91 | 1.14 | 3–3 | 2.8 | +0.23 | 0.0 | 60% |
| Ryyan Amsden | Texas A&M University | 0.34 | 0.57 | 3–3 | 2.8 | +0.23 | 0.0 | 60% |
| John Mason | University of Texas | 1.70 | 0.34 | 3–3 | 4.4 | −1.36 | 1.4 | 97% |
| Etienne Black | University of Texas | 0.36 | -1.00 | 3–3 | 4.4 | −1.36 | 1.4 | 97% |
| Thomas Norman | University of Texas | 0.93 | -0.43 | 3–3 | 4.4 | −1.36 | 1.4 | 97% |
| Catherine Bruce | University of Central Oklahoma | -0.61 | -3.61 | 0–6 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Caleb Vanderburg | University of Central Oklahoma | -1.02 | -4.02 | 0–6 | 0.3 | ≤−3.00 | 0.4 | >99% |
| Peyton Miller | University of Central Oklahoma | 1.41 | -1.59 | 0–6 | 0.3 | ≤−3.00 | 0.4 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | Green | Longhorns | Aggies | Aggies | Bronchos | |
|---|---|---|---|---|---|---|---|
| University of North Texas Mean Green | 4–0 | ✕ | W | W | W | W | |
| University of Texas Longhorns | 2–2 | L | ✕ | L | W | W | |
| Texas A&M University Aggies | 3–1 | L | W | ✕ | W | W | |
| Texas A&M University at Galveston Aggies | 1–3 | L | L | L | ✕ | W | |
| University of Central Oklahoma Bronchos | 0–4 | L | L | L | L | ✕ |
| Team | Rec. | Green | Longhorns | Aggies | Aggies | Bronchos | |
|---|---|---|---|---|---|---|---|
| University of North Texas Mean Green | 4–0 | ✕ | W | W | W | W | |
| University of Texas Longhorns | 3–1 | L | ✕ | W | W | W | |
| Texas A&M University Aggies | 1–3 | L | L | ✕ | L | W | |
| Texas A&M University at Galveston Aggies | 2–2 | L | L | W | ✕ | W | |
| University of Central Oklahoma Bronchos | 0–4 | L | L | L | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | Aggies | 1-2-4 | def. | Bronchos | 3-5-6 | ||
| 2 | Mean Green | 1-3-5 | def. | Aggies | 2-4-6 | ||
| 3 | Longhorns | 1-3-4 | def. | Aggies | 2-5-6 | ||
| 4 | Aggies | 1-2-4 | def. | Bronchos | 3-5-6 | ||
| 5 | Mean Green | 1-2-6 | def. | Longhorns | 3-4-5 | ||
| 6 | Aggies | 1-2-5 | def. | Aggies | 3-4-6 | ||
| 7 | Mean Green | 1-2-4 | def. | Bronchos | 3-5-6 | ||
| 8 | Aggies | 1-3-4 | def. | Longhorns | 2-5-6 | ||
| 9 | Mean Green | 1-2-4 | def. | Aggies | 3-5-6 | ||
| 10 | Longhorns | 1-2-4 | def. | Bronchos | 3-5-6 | ||
| 11 | Longhorns | 1-2-3 | def. | Aggies | 4-5-6 | ||
| 12 | Mean Green | 1-2-3 | def. | Aggies | 4-5-6 | ||
| 13 | Aggies | 1-2-3 | def. | Bronchos | 4-5-6 | ||
| 14 | Mean Green | 1-2-3 | def. | Longhorns | 4-5-6 | ||
| 15 | Aggies | 1-2-3 | def. | Bronchos | 4-5-6 | ||
| 16 | Mean Green | 1-2-5 | def. | Aggies | 3-4-6 | ||
| 17 | Longhorns | 2-3-4 | def. | Aggies | 1-5-6 | ||
| 18 | Mean Green | 1-2-3 | def. | Bronchos | 4-5-6 | ||
| 19 | Aggies | 2-3-4 | def. | Aggies | 1-5-6 | ||
| 20 | Longhorns | 1-2-3 | def. | Bronchos | 4-5-6 | ||
| School | Team | Skippers | Crew | |
|---|---|---|---|---|
| University of North Texas | Mean Green | Dutch Byerly '24 Taylor Snyder '24 Timothy Verriere '24 |
Alana Babilonia '25 Alaya Weekley '21 Gage Hendrickson '23 |
|
| University of Texas | Longhorns | Etienne Black '23 John Mason '23 Thomas Norman '23 |
Warren Wegener '23 Leigha Forrest '24 Delilah D'Souza '24 Sireen Kenana '23 |
|
| Texas A&M University | Aggies | Hanna Progelhof '25 Kate Hennig '26 Ryyan Amsden '24 |
Andrew Pool '23 Katy Heaney '23 Maggie Menefee '25 |
|
| Texas A&M University at Galveston | Aggies | Brett Pearson '26 Emma Stodghill '26 Jacob Granberry '26 Joshua Richie '26 |
Joshua Richie '26 Emma Stodghill '26 Brett Pearson '26 |
|
| University of Central Oklahoma | Bronchos | Caleb Vanderburg '24 Catherine Bruce '23 Peyton Miller '24 |
Jayson Raj '25 Branden Mercer '25 |
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 ±0.07 means a rating gap counts about 6% 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.