I submitted my March Madness Machine Learning Mania today. My two entries consist of picks made using the actual spread for first round games and then a simple Bradley-Terry model for the games past that. In my second bracket, which I called the “aggressive” one, I picks UConn in the men’s bracket and South Carolina in the women’s bracket to win each round (and thus the tournament) with probability 1. So is UConn and South Carolina win, maybe I have a shot at winning. I also manually adjusted two teams on the women’s side (South Carolina and USC). The problem with South Carolina is that they haven’t lost any games and Bradley-Terry basically can’t handle that. I adjusted their regression coefficients to match the market price that they win the tournament. I also adjusted USC on the women’s side because they were way off their market price too. I didn’t make any adjustments to the men’s side because the futures prices were generally in the ball park with what I was estimating (i.e. there are three truly top teams in the men’s bracket (Purdue, UConn, Houston), then a sizable gap down to the next team (which I think is Iowa State. North Carolina got a gift of a 1 seed.)

I’m really excited about the new scoring system for Kaggle this year. And I think they got the scoring system right. A few weeks ago I believe I read that the scoring system was going to be average bracket score with traditional bracket scoring (1-2-4-8-16-32). My first thought when I saw this was that the best strategy is to just enter one bracket and hope. I think other people figured this out and they change it to a Brier score metric. But what they really got right this year is that that don’t take the average over all the GAMES, they take the average over the 6 ROUNDS. This weights the game in the finals much more heavily than a game in the first round, much closer to traditional bracket games.

Anyway, here are some probabilities below are based on my 10000 brackets that I submitted:

To win the championship:

UConn – 29.3%

Houston – 20.9%

Purdue – 19.4%

Iowa St – 5.19%

North Carolina – 4.96%

Tennessee – 3.39%

Marquette – 2.49%

Auburn – 1.94%

Illinois – 1.51%

Baylor – 1.43%

Everyone else < 1%

To make the finals:

UConn – 45.5%

Houston – 34.8%

Purdue – 32.4%

North Carolina – 12.6%

Iowa St – 11.4%

Tennessee – 7..92%

Marquette – 6.51%

Auburn – 5.8%

Illinois – 4.54%

Baylor – 4.34%

Arizona – 3.16%

Alabama – 2.68%

South Carolina – 2.46%

Kansas – 2.31%

Kentucky – 2.13%

Creighton 2.03%

Everyone else < 2%

And finally, here are my pre-tournament rankings 1 through UMass:

Rank	TeamName
1	Connecticut
2	Houston
3	Purdue
4	Iowa St
5	North Carolina
6	Tennessee
7	Auburn
8	Marquette
9	Illinois
10	South Carolina
11	Baylor
12	Kansas
13	Utah St
14	Creighton
15	Arizona
16	Duke
17	Nevada
18	Kentucky
19	Alabama
20	San Diego St
21	BYU
22	Florida
23	Texas Tech
24	New Mexico
25	Wisconsin
26	Gonzaga
27	Nebraska
28	Colorado St
29	Dayton
30	Clemson
31	Virginia
32	Mississippi St
33	Boise St
34	Texas
35	St Mary’s CA
36	TCU
37	Drake
38	Oklahoma
39	Grand Canyon
40	Northwestern
41	Colorado
42	Texas A&M
43	Washington St
44	Indiana St
45	Pittsburgh
46	NC State
47	FL Atlantic
48	Syracuse
49	Providence
50	Michigan St
51	Oregon
52	St John’s
53	James Madison
54	Seton Hall
55	Mississippi
56	Kansas St
57	Ohio St
58	Indiana
59	Princeton
60	Wake Forest
61	Cincinnati
62	Iowa
63	Butler
64	Virginia Tech
65	Villanova
66	Samford
67	Richmond
68	Duquesne
69	McNeese St
70	Utah
71	Memphis
72	Loyola-Chicago
73	South Florida
74	UNLV
75	Florida St
76	Boston College
77	Xavier
78	UCF
79	LSU
80	Georgia
81	VCU
82	Minnesota
83	UAB
84	Washington
85	Bradley
86	San Francisco
87	Appalachian St
88	Arkansas
89	Rutgers
90	Cornell
91	Vermont
92	Miami FL
93	Col Charleston
94	Maryland
95	Penn St
96	Georgia Tech
97	St Joseph’s PA
98	Yale
99	USC
100	UC Irvine
101	St Bonaventure
102	Santa Clara
103	George Mason
104	Massachusetts