The Wood Trophy

HostHarvard
Date03/09/2024
TypeCross Regional
BoatFJ/Z420
ScoringTeam

#	School	Team	Rec.
1	Harvard University	Crimson	16–1
2	Brown University	Bears	14–3
3	Roger Williams University	Hawks	9–8
4	Massachusetts Institute of Technology	Engineers	9–8
5	Georgetown University	Hoyas	9–8
6	University of Rhode Island	Rams	7–10
7	Tufts University	Jumbos	4–13
8	Fordham University	Rams	0–17

Pre-event forecast

Fitted on the 22,415 team race matches sailed before 2024-03-09, using the line-ups that actually raced. It called 60 of 68 matches (88%) with a log-loss of 0.281 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness +0.35 ± 0.22: an orderly event, more orderly than 80% 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	Harvard University Crimson	1	12.30 school +0.24, home +0.39	Mitchell Callahan / Alexandra Dorofeev 3.84 Lachlain Mcgranahan / Marbella Marlo 4.12 12–1 Justin Callahan / Kennedy Leehealey 4.03 12–1 Robby Meek / Jj Drummond 3.33 8–0	93%	16–1 (94%)	+0.2
2	Brown University Bears	2	10.97 school +0.27	Guthrie Braun / Emily Mueller 3.58 12–3 Liam O'Keefe / Caroline Keeffe-Jones 3.66 12–3 Connor Nelson / Vera Allen 3.61 12–3 Leyton Borcherding / Menasha Leport 3.13 6–0	74%	14–3 (82%)	+1.5
3	Roger Williams University Hawks	6	9.63 school +0.25	Kyle Pfrang / Julia O'Connor 3.54 Mathieu Dale / Addyson Fisher 3.09 Drew Mastovsky / Maren Matthews 2.83 5–5 Jack Roman / Carter Sheehan 2.47 4–3	49%	9–8 (53%)	+0.8
4	Massachusetts Institute of Technology Engineers	4	9.79 school +0.05	Maks Groom / Wendy Wu 3.25 Sam Bruce / Jemma Schroder 3.52 Julius Heitkoetter / Yitian Zhu 2.94	50%	9–8 (53%)	+0.4
5	Georgetown University Hoyas	3	9.37 school +0.23	Jeffrey Petersen / Anna Brzezinski 2.68 Enzo Menditto / Spencer Kriegstein 3.25 Peter Barnard / Audrey Fung 8–1 Piper Holthus / Audrey Fung 3.10 1–7	54%	9–8 (53%)	−0.2
6	University of Rhode Island Rams	5	9.20 school −0.07	Kerem Erkmen / Abbie Chipps 3.50 Henry Lee / Eric Pohl 2.78 Tyler Nash / Sadie Thomas 2.97	50%	7–10 (41%)	−1.6
7	Tufts University Jumbos	7	7.75 school +0.15	Connor Rosow / Amelia Carlson 2.61 Adrien Bellanger / Reddin Kehrli 2.26 4–11 Jack Flores / Matthew Caplan 2.45 3–7 Kurt Stuebe / Matthew Caplan 2.85 1–6 Jack Flores / Reddin Kehrli 2.47 0–2	26%	4–13 (24%)	−0.4
8	Fordham University Rams	8	5.80 school +0.09	Elizabeth Cutler / Rebecca Keller 2.17 Lucas Thress / Caroline Newton 1.89 Lizzie Cochran / Leah Spadaro 1.51 0–13 Lizzie Cochran / Isa Arrigo 1.53 0–4	4%	0–17 (0%)	−0.7

Surprisal: who beat their rating

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)
2	Brown University	10.97	11.77	14–3	12.5	+0.80	0.8	26%
3	Roger Williams University	9.63	9.91	9–8	8.3	+0.29	0.2	44%
4	Massachusetts Institute of Technology	9.79	9.97	9–8	8.6	+0.18	0.1	51%
1	Harvard University	12.30	12.47	16–1	15.8	+0.17	0.0	67%
5	Georgetown University	9.37	9.30	9–8	9.2	−0.07	0.0	66%
7	Tufts University	7.75	7.54	4–13	4.4	−0.20	0.1	73%
6	University of Rhode Island	9.20	8.61	7–10	8.6	−0.59	0.7	90%
8	Fordham University	5.80	2.80	0–17	0.7	≤−3.00	1.1	>99%

By skipper

Skipper	School	Value	Perf.	Record	Exp. wins	Δ	Surprise (bits)	P(this good or better)
Lachlain Mcgranahan	Harvard University	4.12	4.40	9–8	8.3	+0.29	0.2	44%
Drew Mastovsky	Roger Williams University	2.83	3.03	5–5	4.6	+0.21	0.1	51%
Adrien Bellanger	Tufts University	2.26	2.07	4–11	4.3	−0.18	0.0	72%
Connor Rosow	Tufts University	2.61	2.40	4–13	4.4	−0.20	0.1	73%
Kerem Erkmen	University of Rhode Island	3.50	2.90	7–10	8.6	−0.59	0.7	90%
Lucas Thress	Fordham University	1.89	-1.11	0–17	0.7	≤−3.00	1.1	>99%

Match by match

Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).

Rd	#	Winner	Loser	P(winner)
1	1	Harvard University	Massachusetts Institute of Technology	95%
1	2	Georgetown University	Roger Williams University	39%	upset
1	3	Tufts University	Fordham University	86%
1	4	Brown University	University of Rhode Island	81%
1	5	Harvard University	Georgetown University	93%
1	6	Massachusetts Institute of Technology	Fordham University	98%
1	7	University of Rhode Island	Roger Williams University	37%	upset
1	8	Brown University	Tufts University	96%
1	9	Georgetown University	Fordham University	97%
1	10	Harvard University	University of Rhode Island	94%
1	11	Massachusetts Institute of Technology	Tufts University	91%
1	12	Brown University	Roger Williams University	80%
1	13	University of Rhode Island	Fordham University	97%
1	14	Georgetown University	Tufts University	85%
1	15	Harvard University	Roger Williams University	96%
1	16	Brown University	Massachusetts Institute of Technology	79%
1	17	University of Rhode Island	Tufts University	78%
1	18	Roger Williams University	Fordham University	97%
1	19	Massachusetts Institute of Technology	Georgetown University	60%
1	20	Brown University	Harvard University	18%	upset
1	21	Roger Williams University	Tufts University	82%
1	22	Massachusetts Institute of Technology	University of Rhode Island	64%
1	23	Harvard University	Fordham University	100%
1	24	Brown University	Georgetown University	85%
1	25	Massachusetts Institute of Technology	Roger Williams University	51%
1	26	Harvard University	Tufts University	98%
1	27	Georgetown University	University of Rhode Island	53%
1	28	Brown University	Fordham University	99%
2	29	Massachusetts Institute of Technology	University of Rhode Island	64%
2	30	Roger Williams University	Georgetown University	59%
2	31	Harvard University	Tufts University	98%
2	32	Brown University	Fordham University	99%
2	33	Georgetown University	University of Rhode Island	54%
2	34	Harvard University	Massachusetts Institute of Technology	94%
2	35	Roger Williams University	Fordham University	97%
2	36	Brown University	Tufts University	95%
2	37	Harvard University	Georgetown University	92%
2	38	University of Rhode Island	Fordham University	97%
2	39	Massachusetts Institute of Technology	Tufts University	90%
2	40	Roger Williams University	Brown University	20%	upset
2	41	Harvard University	Fordham University	100%
2	42	Georgetown University	Tufts University	86%
2	43	Roger Williams University	University of Rhode Island	64%
2	44	Brown University	Massachusetts Institute of Technology	79%
2	45	Tufts University	Fordham University	85%
2	46	Harvard University	Roger Williams University	96%
2	47	Massachusetts Institute of Technology	Georgetown University	59%
2	48	Brown University	University of Rhode Island	81%
2	49	Roger Williams University	Tufts University	82%
2	50	Massachusetts Institute of Technology	Fordham University	98%
2	51	Harvard University	University of Rhode Island	94%
2	52	Brown University	Georgetown University	84%
2	53	Roger Williams University	Massachusetts Institute of Technology	50%	upset
2	54	Tufts University	University of Rhode Island	23%	upset
2	55	Georgetown University	Fordham University	97%
2	56	Harvard University	Brown University	82%
3	57	Brown University	Massachusetts Institute of Technology	79%
3	58	Harvard University	Roger Williams University	96%
3	59	Brown University	Roger Williams University	80%
3	60	Harvard University	Massachusetts Institute of Technology	94%
3	61	Roger Williams University	Massachusetts Institute of Technology	50%	upset
3	62	Harvard University	Brown University	81%
4	63	University of Rhode Island	Tufts University	77%
4	64	Georgetown University	Fordham University	97%
4	65	University of Rhode Island	Fordham University	97%
4	66	Georgetown University	Tufts University	86%
4	67	Tufts University	Fordham University	85%
4	68	University of Rhode Island	Georgetown University	45%	upset

Round 1

Team	Rec.	Crimson	Bears	Hawks	Engineers	Hoyas	Rams	Jumbos	Rams
Harvard University Crimson	6–1	✕	L	W	W	W	W	W	W
Brown University Bears	7–0	W	✕	W	W	W	W	W	W
Roger Williams University Hawks	2–5	L	L	✕	L	L	L	W	W
Massachusetts Institute of Technology Engineers	5–2	L	L	W	✕	W	W	W	W
Georgetown University Hoyas	4–3	L	L	W	L	✕	W	W	W
University of Rhode Island Rams	3–4	L	L	W	L	L	✕	W	W
Tufts University Jumbos	1–6	L	L	L	L	L	L	✕	W
Fordham University Rams	0–7	L	L	L	L	L	L	L	✕

Round 2

Team	Rec.	Crimson	Bears	Hawks	Engineers	Hoyas	Rams	Jumbos	Rams
Harvard University Crimson	7–0	✕	W	W	W	W	W	W	W
Brown University Bears	5–2	L	✕	L	W	W	W	W	W
Roger Williams University Hawks	6–1	L	W	✕	W	W	W	W	W
Massachusetts Institute of Technology Engineers	4–3	L	L	L	✕	W	W	W	W
Georgetown University Hoyas	3–4	L	L	L	L	✕	W	W	W
University of Rhode Island Rams	1–6	L	L	L	L	L	✕	L	W
Tufts University Jumbos	2–5	L	L	L	L	L	W	✕	W
Fordham University Rams	0–7	L	L	L	L	L	L	L	✕

Round 3

Team	Rec.	Crimson	Bears	Hawks	Engineers
Harvard University Crimson	3–0	✕	W	W	W
Brown University Bears	2–1	L	✕	W	W
Roger Williams University Hawks	1–2	L	L	✕	W
Massachusetts Institute of Technology Engineers	0–3	L	L	L	✕

Round 4

Team	Rec.	Hoyas	Rams	Jumbos	Rams
Georgetown University Hoyas	2–1	✕	L	W	W
University of Rhode Island Rams	3–0	W	✕	W	W
Tufts University Jumbos	1–2	L	L	✕	W
Fordham University Rams	0–3	L	L	L	✕

Filter by team:

#					Pos.
1	Crimson	1-2-3	def.	Engineers	4-5-6
2	Hoyas	1-2-5	def.	Hawks	3-4-6
3	Jumbos	1-2-4	def.	Rams	3-5-6
4	Bears	1-2-4	def.	Rams	3-5-6
5	Crimson	1-2-4	def.	Hoyas	3-5-6
6	Engineers	1-2-5	def.	Rams	3-4-6
7	Rams	1-2-6	def.	Hawks	3-4-5
8	Bears	1-2-6	def.	Jumbos	3-4-5
9	Hoyas	1-2-5	def.	Rams	3-4-6
10	Crimson	1-2-6	def.	Rams	3-4-5
11	Engineers	1-2-3	def.	Jumbos	4-5-6
12	Bears	1-2-4	def.	Hawks	3-5-6
13	Rams	1-2-3	def.	Rams	4-5-6
14	Hoyas	1-2-3	def.	Jumbos	4-5-6
15	Crimson	1-2-3	def.	Hawks	4-5-6
16	Bears	1-2-5	def.	Engineers	3-4-6
17	Rams	2-3-4	def.	Jumbos	1-5-6
18	Hawks	1-2-3	def.	Rams	4-5-6
19	Engineers	1-2-5	def.	Hoyas	3-4-6
20	Bears	2-3-5	def.	Crimson	1-4-6
21	Hawks	2-3-4	def.	Jumbos	1-5-6
22	Engineers	1-3-4	def.	Rams	2-5-6
23	Crimson	1-2-5	def.	Rams	3-4-6
24	Bears	1-2-5	def.	Hoyas	3-4-6
25	Engineers	1-2-6	def.	Hawks	3-4-5
26	Crimson	2-3-5	def.	Jumbos	1-4-6
27	Hoyas	2-3-5	def.	Rams	1-4-6 DSQ
28	Bears	1-2-4	def.	Rams	3-5-6
29	Engineers	1-3-6	def.	Rams	2-4-5
30	Hawks	1-2-6	def.	Hoyas	3-4-5
31	Crimson	2-3-4	def.	Jumbos	1-5-6
32	Bears	1-2-3	def.	Rams	4-5-6
33	Hoyas	1-2-6	def.	Rams	3-4-5
34	Crimson	1-2-5	def.	Engineers	3-4-6
35	Hawks	1-2-5	def.	Rams	3-4-6
36	Bears	1-2-3	def.	Jumbos	4-5-6
37	Crimson	1-2-5	def.	Hoyas	3-4-6
38	Rams	1-2-4	def.	Rams	3-5-6
39	Engineers	1-2-3	def.	Jumbos	4-5-6
40	Hawks	1-2-6	def.	Bears	3-4-5
41	Crimson	1-2-3	def.	Rams	4-5-6
42	Hoyas	1-2-5	def.	Jumbos	3-4-6
43	Hawks	1-2-6	def.	Rams	3-4-5
44	Bears	1-2-4	def.	Engineers	3-5-6
45	Jumbos	1-2-6	def.	Rams	3-4-5
46	Crimson	1-2-4	def.	Hawks	3-5-6
47	Engineers	1-2-3	def.	Hoyas	4-5-6
48	Bears	1-2-4	def.	Rams	3-5-6
49	Hawks	1-2-4	def.	Jumbos	3-5-6
50	Engineers	1-2-4	def.	Rams	3-5-6
51	Crimson	1-3-4	def.	Rams	2-5-6
52	Bears	1-4-5	def.	Hoyas	2-3-6
53	Hawks	1-2-6	def.	Engineers	3-4-5
54	Jumbos	1-2-6	def.	Rams	3-4-5
55	Hoyas	1-2-3	def.	Rams	4-5-6
56	Crimson	1-2-5	def.	Bears	3-4-6
57	Bears	1-2-4	def.	Engineers	3-5-6
58	Crimson	2-3-4	def.	Hawks	1-5-6
59	Bears	1-2-6	def.	Hawks	3-4-5
60	Crimson	2-3-4	def.	Engineers	1-5-6
61	Hawks	1-2-6	def.	Engineers	3-4-5
62	Crimson	1-2-3	def.	Bears	4-5-6
63	Rams	1-2-5	def.	Jumbos	3-4-6
64	Hoyas	1-2-4	def.	Rams	3-5-6
65	Rams	2-3-4	def.	Rams	1-5-6
66	Hoyas	2-3-4	def.	Jumbos	1-5-6
67	Jumbos	1-2-5	def.	Rams	3-4-6
68	Rams	1-4-5	def.	Hoyas	2-3-6

School	Team	Skippers	Crew
Harvard University	Crimson	Justin Callahan '26 Lachlain Mcgranahan '24 Mitchell Callahan '26 Robby Meek '27	Kennedy Leehealey '26 Marbella Marlo '24 Alexandra Dorofeev '25 Jj Drummond '27
Brown University	Bears	Connor Nelson '24 Guthrie Braun '26 Leyton Borcherding '25 Liam O'Keefe '26	Vera Allen '27 Emily Mueller '25 Menasha Leport '25 Caroline Keeffe-Jones '26
Roger Williams University	Hawks	Drew Mastovsky '26 Jack Roman '26 Kyle Pfrang '26 Mathieu Dale '25	Maren Matthews '26 Carter Sheehan '27 Julia O'Connor '24 Addyson Fisher '27
Massachusetts Institute of Technology	Engineers	Julius Heitkoetter '25 Maks Groom '24 Sam Bruce '24	Yitian Zhu '25 Wendy Wu '23 Jemma Schroder '24
Georgetown University	Hoyas	Enzo Menditto '26 Jeffrey Petersen '25 Peter Barnard '27 Piper Holthus '25	Spencer Kriegstein '25 Anna Brzezinski '27 Audrey Fung '24
University of Rhode Island	Rams	Henry Lee '24 Kerem Erkmen '25 Tyler Nash '26	Eric Pohl '28 Abbie Chipps '25 Sadie Thomas '25
Tufts University	Jumbos	Adrien Bellanger '25 Connor Rosow '24 Jack Flores '25 Kurt Stuebe '27	Reddin Kehrli '27 Amelia Carlson '24 Matthew Caplan '25
Fordham University	Rams	Elizabeth Cutler '24 Lizzie Cochran '27 Lucas Thress '26	Rebecca Keller '25 Isa Arrigo '27 Leah Spadaro '25 Caroline Newton '27

Conditions — 03/09/2024 (8am–6pm)

☁️Overcast

Humidity 76% · Pressure 1023.0 hPa

Temperature

39°F

↑ 42°F ↓ 34°F

Feels like 32°F

Wind

● from ▲ toward

7.8 kn

avg · max 9.9 kn

Gusts to 18.5 kn

From SE (134°)

Sky & Precipitation

Cloud cover100% Sunshine0.0 hrs Humidity76% Pressure1023.0 hPa

What this breeze does at Harvard — from fleet racing

Breeze: SE about 10 kn (weather reanalysis in the scorer’s units)

In fleet races at Harvard 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 Harvard by wind direction (angle) and speed (rings), fitted surface; dots are labelled regatta-days, ★ this regatta (59 labelled fleet-race days at Harvard).

From the notes

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

How team race forecasts workThree boats’ ratings, a school term and a home edge; 78.8% of held-out matches called.
Play 1, Play 2, Play 4: how team races are wonHow often each play happens, how that shifts with breeze and level, and whether a star wins differently.
Which team races go to form?Orderliness is a real property of a team race regatta and nothing known in advance predicts it.

All notes →

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