LaserPerformance Men's Singlehanded Nationals

HostTexas A&M Galveston
Date11/05/2016
TypeNational Championship Finals
BoatLaser
ScoringSinglehanded

#	School	Sailor	TOT
1	Boston College	Scott Rasmussen '20	81
2	College of Charleston	Gerald Williams '19	84
3	Yale University	Nicholas Baird '19	85
4	College of Charleston	Enrique Pacas '17	89
5	College of Charleston	Stefano Peschiera '18	89
6	Tufts University	Alp Rodopman '17	107
7	Yale University	Malcolm Lamphere '18	111
8	Georgetown University	Greg Martinez '18	113
9	U. S. Naval Academy	Gary Prieto '18	117
10	George Washington University	Brendan Shanahan '17	122
11	Stanford University	William Marshall '19	125
12	Texas A&M University at Galveston	John Hanna '19	128
13	Georgetown University	Jack Marshall '18	142
14	Stanford University	Luke Muller '18	160
15	Washington University	James Harvey '17	184
16	Oregon State University	Michael Levy '19	211
17	University of Wisconsin	Charlie Kutschenreuter '19	217
18	University of Wisconsin	Korbin Kierstead '19	231

School	Sailor	R1	R2	R3	R4	R5	R6	R7	R8	R9	R10	R11	R12	R13	R14	TOT
Boston College	Scott Rasmussen '20	12	5	2	5	8	5	6	7	7	1	1	17	4	1	81
College of Charleston	Gerald Williams '19	5	9	13	3	11	11	3	6	1	12	3	1	1	5	84
Yale University	Nicholas Baird '19	6	14	3	8	2	1	4	4	3	7	5	6	8	14	85
College of Charleston	Enrique Pacas '17	2	8	1	14	3	9	9	9	15	6	2	3	6	2	89
College of Charleston	Stefano Peschiera '18	7	1	7	DSQ	1	3	OCS	1	6	4	4	7	7	3	89
Tufts University	Alp Rodopman '17	9	7	4	7	5	4	5	14	4	5	12	8	12	11	107
Yale University	Malcolm Lamphere '18	1	11	10	12	14	12	1	3	5	13	8	2	9	10	111
Georgetown University	Greg Martinez '18	3	2	14	2	9	2	13	11	9	3	10	9	18	8	113
U. S. Naval Academy	Gary Prieto '18	13	3	6	1	6	8	2	5	8	10	7	13	17	18	117
George Washington University	Brendan Shanahan '17	10	10	9	9	4	10	12	12	11	8	14	4	3	6	122
Stanford University	William Marshall '19	8	16	5	13	10	7	7	8	13	11	6	12	5	4	125
Texas A&M University at Galveston	John Hanna '19	4	13	11	6	12	6	10	15	2	2	17	10	11	9	128
Georgetown University	Jack Marshall '18	14	4	8	4	16	14	8	2	12	9	15	14	10	12	142
Stanford University	Luke Muller '18	18	6	17	11	13	17	11	10	18	16	9	5	2	7	160
Washington University	James Harvey '17	16	17	12	10	7	13	15	13	10	18	11	11	16	15	184
Oregon State University	Michael Levy '19	11	12	15	16	15	16	16	16	17	17	13	16	14	17	211
University of Wisconsin	Charlie Kutschenreuter '19	15	18	16	17	17	15	14	18	16	14	16	15	13	13	217
University of Wisconsin	Korbin Kierstead '19	17	15	18	15	18	18	17	17	14	15	18	18	15	16	231

Performance rating asks, for each skipper: holding every other boat fixed, which rating makes my actual race-by-race finishes least surprising? Boats are valued with the singlehanded rating rather than the fleet rating: 0.79 × the skipper's fleet rating from the week before the event (unrated skippers start at 1.11); the skipper's own singlehanded offset. Strength differences are scaled by 0.80 before they become probabilities, the value that calibrates the model on seasons it had not seen. Non-finishes (OCS, DNF and similar) are left out of the fitting, as in the rating model.

Percentile places a rating among the 309 ICSA sailors with a singlehanded rating who raced the discipline in the last three seasons. Surprise is how many bits more surprising the finishes were at the pre-event rating than at the performance rating. P(this good or better) simulates the event 3,000 times at the pre-event ratings, with the same regatta-form model as the fleet analysis pages, and reports how often the skipper would score this many points or fewer in the races they sailed.

The singlehanded offsets are the current ones (the discipline files keep no weekly history), so a skipper's own offset has already seen this event; offsets are shrunk hard, so the effect is a few hundredths at most. Only skippers are rated.

^u no fleet rating — the model's level for unrated skippers is the baseline.

Division A 18 boats · 14 races

Fin	Skipper	School	Races	Rating before	Perf. rating	Δ	Percentile before → perf.	Surprise (bits)	P(this good or better)	Avg finish actual / exp.
1	Scott Rasmussen '20	Boston College	14/14	2.88	3.78	+0.90	78th → 94th	3.3	4%	5.8 / 9.3
2	Gerald Williams '19	College of Charleston Cougars 3	14/14	3.29	3.85	+0.56	87th → 94th	1.5	16%	6.0 / 8.1
3	Nicholas Baird '19	Yale University Bulldogs 1	14/14	3.48	3.82	+0.34	90th → 94th	0.6	24%	6.1 / 7.6
4	Enrique Pacas '17	College of Charleston Cougars 2	14/14	1.33^u	3.65	+2.32	31st → 93rd	18.4	1%	6.4 / 13.1
4	Stefano Peschiera '18	College of Charleston Cougars 1	14/14	3.91	4.72	+0.81	94th → 99th	2.5	50%	6.4 / 6.5
6	Alp Rodopman '17	Tufts University	14/14	3.20	3.51	+0.31	85th → 90th	0.5	41%	7.6 / 8.4
7	Malcolm Lamphere '18	Yale University Bulldogs 2	14/14	3.10	3.28	+0.18	84th → 86th	0.2	38%	7.9 / 8.6
8	Greg Martinez '18	Georgetown University Hoyas 2	14/14	3.56	3.03	−0.53	92nd → 83rd	1.6	65%	8.1 / 7.4
9	Gary Prieto '18	U. S. Naval Academy	14/14	3.30	2.89	−0.41	87th → 78th	0.9	58%	8.4 / 8.1
10	Brendan Shanahan '17	George Washington University	14/14	3.45	3.18	−0.27	89th → 85th	0.4	71%	8.7 / 7.7
11	William Marshall '19	Stanford University Cardinal 1	14/14	2.78	3.05	+0.27	75th → 83rd	0.4	41%	8.9 / 9.6
12	John Hanna '19	Texas A&M University at Galveston	14/14	2.86	2.94	+0.08	78th → 81st	0.0	47%	9.1 / 9.3
13	Jack Marshall '18	Georgetown University Hoyas 1	14/14	3.03	2.71	−0.32	83rd → 72nd	0.6	75%	10.1 / 8.8
14	Luke Muller '18	Stanford University Cardinal 2	14/14	2.60	1.78	−0.82	68th → 43rd	3.4	75%	11.4 / 10.0
15	James Harvey '17	Washington University	14/14	2.00	2.01	+0.02	52nd → 52nd	0.0	72%	13.1 / 11.5
16	Michael Levy '19	Oregon State University	14/14	1.49	1.63	+0.15	37th → 40th	0.1	89%	15.1 / 12.8
17	Charlie Kutschenreuter '19	University of Wisconsin Badgers 2	14/14	1.85	1.22	−0.64	47th → 29th	2.0	95%	15.5 / 11.9
18	Korbin Kierstead '19	University of Wisconsin Badgers 1	14/14	1.69	0.60	−1.10	42nd → 15th	5.2	98%	16.5 / 12.2

Conditions — 11/05/2016 (8am–6pm)

🌤️Mainly clear

Humidity 62% · Pressure 1021.9 hPa

Temperature

76°F

↑ 77°F ↓ 72°F

Feels like 76°F

Wind

● from ▲ toward

6.6 kn

avg · max 8.1 kn

Gusts to 15.7 kn

From ENE (75°)

Sky & Precipitation

Cloud cover52% Sunshine10.0 hrs Humidity62% Pressure1021.9 hPa

What this breeze does at Texas A&M Galveston — from fleet racing

Breeze: E about 9 kn (weather reanalysis in the scorer’s units)

In fleet races at Texas A&M Galveston in this breeze: a favourites’ day (+0.08)

Favourites’ conditions: in fleet racing here the results follow the ratings more closely than usual, and the top seeds hold their places.

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 ±0.08 means a rating gap counts about 7% 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.

Orderliness beyond the fleet at Texas A&M Galveston by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (29 labelled fleet-race days at Texas A&M Galveston).

From the notes

Short write-ups of what the ratings and results show, with the numbers and how they were computed.

What a rating point is worthA one-point edge is a 73% chance to beat another boat in a race; two points is 88%.
Should the best sailor sail A?Add your two skippers’ ratings and compare with the field; above it the better skipper belongs in A.
Which venues get orderly in a breeze?Some venues get orderly when it blows, a few get messier; the fleet comes first.

All notes →

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