Rockaway, NJ - Rockaway, NJ, USA
Explore the pool victory probability density for each fencer, with their actual victories highlighted in a box. Learn more.
# | Name | Number of victories | ||||||
---|---|---|---|---|---|---|---|---|
0 | 1 | 2 | 3 | 4 | 5 | 6 | ||
1 | CHOU Stephen C. | - | - | 6% | 31% | 44% | 18% | |
2 | SHI Andrew | - | - | 4% | 19% | 43% | 33% | |
3 | YEN Darren | - | - | 1% | 5% | 20% | 41% | 32% |
3 | QIU Le | 2% | 13% | 31% | 34% | 17% | 3% | |
5 | PEDERSEN Leif | - | - | 4% | 16% | 33% | 34% | 13% |
6 | RAI Avin | - | 1% | 5% | 19% | 36% | 31% | 9% |
7 | KUSHKOV Simon O. | - | - | - | 5% | 21% | 42% | 32% |
8 | MAHONEY Colin M. | - | 3% | 16% | 32% | 32% | 14% | 2% |
9 | WOOD Elden S. | - | 1% | 7% | 24% | 38% | 25% | 5% |
10 | BASALYGA Jeffrey | - | 2% | 9% | 25% | 35% | 23% | 5% |
11 | FRISHMAN Ethan J. | - | - | 4% | 20% | 43% | 33% | |
12 | LIN John A. | - | - | 3% | 23% | 46% | 27% | |
13 | GINIS Nathan | - | 4% | 17% | 32% | 31% | 14% | 2% |
14 | MOSKOWITZ Mason C. | - | 4% | 15% | 31% | 32% | 15% | 3% |
15 | TRAVAGLIONE Conor D. | - | - | 1% | 6% | 23% | 42% | 29% |
16 | LUKASHENKO Darii | - | 1% | 10% | 36% | 40% | 14% | |
17 | WILLIAMS Nolan E. | - | - | 1% | 7% | 25% | 41% | 26% |
17 | ZU Kevin | - | - | 1% | 8% | 26% | 41% | 24% |
19 | MIKA Casper | - | - | - | 3% | 20% | 47% | 31% |
20 | BARNETT Adam | - | 1% | 8% | 27% | 41% | 23% | |
21 | MOSZCZYNSKI Adam | - | 1% | 7% | 21% | 35% | 28% | 9% |
22 | CHO Brandon | - | 1% | 10% | 36% | 40% | 13% | |
23 | CZAHA Balint | - | 1% | 7% | 24% | 36% | 25% | 7% |
24 | GANTA Vijay | 10% | 30% | 34% | 19% | 5% | 1% | - |
25 | LILOV Neil | - | - | - | 3% | 22% | 47% | 28% |
26 | MORRIS Samuel A. | - | 1% | 7% | 23% | 35% | 26% | 7% |
27 | CHAN Matthew | - | - | 3% | 21% | 45% | 31% | |
28 | LAU Jeremy Y. | - | 4% | 18% | 36% | 32% | 10% | |
29 | WIND Nicky E. | - | 1% | 8% | 26% | 36% | 23% | 5% |
30 | SO Hananiah | - | 1% | 9% | 35% | 41% | 14% | |
31 | LIU kelly | - | 4% | 26% | 43% | 23% | 4% | |
32 | HONG Marshall Q. | - | - | 3% | 15% | 33% | 35% | 14% |
33 | TRAVERS Samir T. | - | 3% | 15% | 36% | 35% | 11% | |
34 | SZEWCZYK Thomas D. | - | 4% | 22% | 38% | 27% | 8% | 1% |
35 | WU Nicholas R. | 1% | 9% | 26% | 34% | 23% | 7% | 1% |
36 | VACCARI Braden | 1% | 5% | 19% | 32% | 29% | 13% | 2% |
37 | WOLIN Zachary A. | - | 1% | 6% | 24% | 38% | 26% | 6% |
38 | LASORSA Matthew | 1% | 8% | 24% | 34% | 24% | 9% | 1% |
39 | MURTHY mukund | - | 2% | 16% | 34% | 32% | 13% | 2% |
40 | JUN Ryan | 7% | 27% | 36% | 22% | 7% | 1% | - |
41 | HARRIS Alex K. | - | 1% | 6% | 24% | 42% | 23% | 4% |
42 | BARTOLO Domenic V. | - | 1% | 7% | 23% | 36% | 26% | 7% |
43 | HONG Vincent Q. | 7% | 26% | 37% | 23% | 7% | 1% | - |
44 | METTKE Nathaniel | 2% | 13% | 30% | 32% | 17% | 4% | - |
45 | GHOSH Tuhin | 4% | 20% | 35% | 28% | 11% | 2% | |
46 | YEN Preston | 1% | 9% | 31% | 38% | 18% | 3% | |
47 | WYCHE Scott H. | 7% | 31% | 44% | 16% | 2% | - | |
48 | WUN William | 1% | 8% | 28% | 38% | 21% | 4% | |
48 | STEINMETZ John | 17% | 38% | 31% | 12% | 2% | - | |
50 | KIM Avery J. | - | 3% | 14% | 32% | 35% | 15% | |
50 | ATEFI Daniel | 6% | 24% | 36% | 25% | 8% | 1% | |
52 | PATTON Colin T. | 1% | 17% | 47% | 28% | 6% | - | |
53 | HUSSAIN Faaris | - | 1% | 6% | 20% | 34% | 29% | 10% |
54 | XU Michael | 10% | 30% | 35% | 20% | 5% | 1% | - |
55 | GILLIGAN Wolff | - | 2% | 11% | 28% | 35% | 20% | 4% |
56 | TANG Albert | 1% | 8% | 23% | 33% | 24% | 9% | 1% |
57 | DEWEY Charles J. | 26% | 51% | 20% | 3% | - | - | - |
58 | KEEFE Duncan | 3% | 16% | 34% | 33% | 13% | 2% | |
59 | YUAN Kevin | 5% | 22% | 37% | 27% | 9% | 1% | |
60 | PARKHURST Jr Michael | 2% | 16% | 38% | 32% | 11% | 1% | |
61 | MORREALE John | - | 5% | 20% | 36% | 30% | 9% | |
62 | LEE Jude H. | 13% | 34% | 33% | 16% | 4% | - | - |
63 | QIN Alexander | 10% | 30% | 35% | 20% | 5% | 1% | - |
64 | JIANG Kevin | 31% | 46% | 20% | 3% | - | - | |
65 | EPSTEIN Henry N. | 9% | 33% | 36% | 17% | 4% | - | - |
66 | LEVIN Mark A. | 1% | 5% | 20% | 36% | 29% | 9% | |
67 | YOU Jaden | 16% | 36% | 31% | 13% | 3% | - | - |
68 | CHAN Daniel | 2% | 14% | 35% | 35% | 12% | 1% | - |
69 | CLAWSON Amzie | - | 2% | 10% | 25% | 34% | 23% | 6% |
70 | MENSAH Kennedy C | 1% | 7% | 22% | 35% | 26% | 9% | 1% |
71 | MARTINEZ Justin | 12% | 37% | 36% | 13% | 2% | - | - |
72 | HUDDY Brandon J. | 1% | 5% | 19% | 32% | 29% | 13% | 2% |
73 | ALKEMPER Tristan H. | 1% | 10% | 27% | 33% | 21% | 7% | 1% |
73 | ANGELILLO Nicholas | 18% | 49% | 26% | 6% | 1% | - | - |
75 | RYAN Edward T. | 2% | 11% | 28% | 33% | 20% | 6% | 1% |
76 | BUCCINO George | 10% | 52% | 31% | 6% | - | - | |
77 | WEHLE Paul | 25% | 41% | 26% | 8% | 1% | - | |
78 | FAN ANDREW | 15% | 46% | 30% | 8% | 1% | - | |
79 | NEVILLE James | 30% | 49% | 18% | 2% | - | - | |
79 | GROTH Christian | 20% | 41% | 29% | 9% | 1% | - | |
81 | TEVEBAUGH Andrew | 17% | 37% | 31% | 13% | 3% | - | |
82 | BOURGHOL Matthew | 6% | 26% | 39% | 23% | 5% | - | - |
83 | CZYZEWSKI Konrad R. | - | 2% | 13% | 32% | 34% | 17% | 3% |
84 | CHAN Alexander S. | 6% | 23% | 34% | 26% | 10% | 2% | - |
85 | PEARSON James G. | 28% | 43% | 23% | 5% | - | - | - |
86 | ZHANG Jeffrey | - | 4% | 23% | 38% | 26% | 8% | 1% |
87 | KREGER Evan | 13% | 33% | 33% | 17% | 4% | - | - |
88 | MOLINARO Lawrence | 26% | 42% | 25% | 7% | 1% | - | - |
89 | CHAN Austin | 47% | 43% | 9% | 1% | - | - | - |
90 | FISK Ethan | 52% | 36% | 10% | 1% | - | - | - |
91 | SHAO Peter | 6% | 22% | 34% | 26% | 10% | 2% | - |
92 | YANG Richard | < 1% | 2% | 11% | 28% | 35% | 19% | 4% |
93 | CHERNAEV Aleksandar | 10% | 34% | 36% | 16% | 3% | - | |
94 | HO Kaden M. | 8% | 28% | 35% | 21% | 7% | 1% | - |
95 | ZHOU Miles | 7% | 28% | 37% | 21% | 6% | 1% | - |
96 | DEFORD Kevin W. | 76% | 23% | 1% | - | - | - | |
96 | BELEV Nicholas | 26% | 49% | 22% | 3% | - | - | |
98 | HUANG Ethan F. | < 1% | 5% | 18% | 33% | 29% | 13% | 2% |
99 | CAMPO Alexander P. | 54% | 39% | 7% | 1% | - | - | - |
The heatmap in this table provides a visual representation of the victory probability distribution for each fencer in their respective pools:
This heatmap visualization offers an immediate understanding of each fencer's expected performance compared to their actual results.