Secaucus, NJ - Secaucus, 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 | SILBERZWEIG Jordan H. | - | - | - | - | 2% | 28% | 70% |
2 | TONG ZACHARY | - | 1% | 8% | 30% | 42% | 19% | |
3 | GRASS James D. | - | 2% | 12% | 30% | 34% | 18% | 3% |
3 | MORRILL Justin | - | - | - | 3% | 17% | 42% | 38% |
5 | NG Jonathan H. | - | - | - | 4% | 19% | 43% | 34% |
6 | DENNER Maximilian P. | - | 1% | 7% | 22% | 35% | 27% | 8% |
7 | NOBLE Colin | - | 4% | 15% | 31% | 32% | 16% | 2% |
8 | WU Mengke | - | 1% | 8% | 28% | 42% | 21% | |
9 | GINIS Nathan | - | - | 2% | 10% | 28% | 38% | 21% |
10 | TANG Albert | - | - | 3% | 13% | 31% | 37% | 17% |
11 | LASORSA Matthew | - | - | 2% | 11% | 30% | 38% | 18% |
12 | ETIN Ari | - | 8% | 31% | 39% | 18% | 3% | |
13 | ZHOU Miles | - | 3% | 16% | 34% | 34% | 13% | |
14 | LO Alexander | 1% | 14% | 39% | 32% | 11% | 2% | - |
15 | GHAYALOD ansh | - | 3% | 14% | 31% | 32% | 17% | 3% |
16 | WONG Ryan | 1% | 11% | 27% | 33% | 21% | 6% | 1% |
17 | KIM-COGAN Ryan | - | 1% | 6% | 24% | 41% | 27% | |
18 | COLE Alexander | - | 1% | 10% | 30% | 36% | 19% | 4% |
19 | YUAN Kevin | - | 1% | 8% | 26% | 37% | 23% | 5% |
20 | BERMAN Luca | - | - | 4% | 18% | 37% | 32% | 9% |
21 | YEN Preston | - | - | - | 4% | 18% | 41% | 37% |
22 | MENSAH Kennedy C | - | - | 4% | 21% | 45% | 30% | |
23 | FENG Leo | - | 4% | 17% | 35% | 33% | 12% | |
24 | WANG Andy | 12% | 32% | 34% | 18% | 5% | 1% | - |
25 | ZHENG Edward L. | - | 4% | 15% | 30% | 32% | 16% | 3% |
26 | ZHANG Jeffrey | - | 1% | 7% | 21% | 35% | 28% | 8% |
27 | MORRILL William | - | - | 3% | 16% | 35% | 34% | 12% |
28 | HONG Steven | 3% | 17% | 34% | 31% | 13% | 2% | |
29 | NOURELDIN Gabriel | - | 3% | 20% | 41% | 29% | 7% | |
30 | SHOMAN Zachary | - | - | 3% | 16% | 35% | 33% | 11% |
31 | LEDERER Justin W. | 7% | 26% | 34% | 23% | 8% | 1% | - |
32 | WOLFE-MCGUIRE George T. | - | - | 3% | 14% | 31% | 36% | 16% |
33 | FIELDS Matthew S. | - | 1% | 10% | 31% | 40% | 18% | |
34 | SHIRPAL Oleksandr | - | - | 1% | 7% | 29% | 51% | 13% |
35 | STONE Esmond A. | - | 2% | 12% | 32% | 35% | 16% | 2% |
36 | DENG Andrew | 1% | 10% | 27% | 34% | 21% | 6% | 1% |
37 | RAUSCHER Ryan | 2% | 13% | 31% | 33% | 17% | 3% | |
38 | GOLD Jackson | 5% | 23% | 36% | 26% | 9% | 1% | |
39 | CLYMER Lucas Y. | - | 4% | 15% | 30% | 32% | 16% | 3% |
39 | HO Kaden M. | - | 4% | 16% | 31% | 30% | 15% | 3% |
41 | WU Wilmund | - | - | 3% | 16% | 36% | 35% | 10% |
42 | CHENG Kyle | - | 4% | 18% | 32% | 30% | 13% | 2% |
43 | HUANG Tyler T. | 1% | 7% | 22% | 34% | 26% | 9% | 1% |
44 | BOURGHOL Matthew | - | 7% | 27% | 39% | 23% | 5% | |
45 | WEBER Mattias A. | 1% | 14% | 38% | 34% | 12% | 1% | |
46 | LU Caleb Q. | - | 4% | 23% | 39% | 27% | 7% | |
47 | KIM Shaun M. | - | 1% | 8% | 30% | 42% | 19% | |
48 | LUTHRA Arjun | 1% | 6% | 21% | 36% | 28% | 9% | |
49 | HONG Justin | 8% | 46% | 35% | 10% | 1% | - | |
50 | KIM Matthew | 1% | 10% | 27% | 34% | 21% | 7% | 1% |
51 | ZHOU Brian | 1% | 8% | 23% | 33% | 25% | 9% | 1% |
51 | CHAUDHURI Eeshaan A. | 4% | 19% | 35% | 30% | 11% | 1% | - |
53 | SHAO Peter | - | 5% | 22% | 37% | 27% | 8% | 1% |
54 | FISK Ethan | 1% | 10% | 29% | 36% | 20% | 3% | - |
55 | OVERDECK Andrew | 15% | 37% | 32% | 13% | 2% | - | |
56 | BUCHMANN Finn D. | 1% | 7% | 24% | 36% | 25% | 7% | |
57 | SHTEYN Mark | 1% | 6% | 21% | 33% | 27% | 10% | 2% |
58 | TRUDNOS Allen | - | - | 3% | 17% | 37% | 33% | 10% |
59 | REN Richard | 8% | 29% | 37% | 20% | 5% | 1% | - |
60 | KAPLAN Liam | - | 5% | 25% | 37% | 24% | 7% | 1% |
61 | MELIS Gabriele Nathan | 20% | 39% | 28% | 10% | 2% | - | - |
62 | EPSTEIN Oliver D. | 3% | 17% | 34% | 31% | 13% | 2% | - |
63 | HUANG Ethan F. | - | 1% | 6% | 22% | 38% | 27% | 6% |
64 | MOLINARO Lawrence | 17% | 37% | 30% | 12% | 3% | - | - |
65 | TSIGAL Edwin | 6% | 23% | 35% | 26% | 9% | 1% | |
66 | HAQ Kamran R. | 7% | 26% | 37% | 24% | 6% | 1% | - |
67 | QIN Alexander | - | 2% | 14% | 35% | 36% | 13% | |
68 | BUCCINO George | 6% | 41% | 38% | 14% | 2% | - | |
69 | MCCARTHY Gabriel | 1% | 11% | 36% | 37% | 14% | 2% | |
70 | PANDEY Neil | 13% | 35% | 34% | 15% | 3% | - | |
71 | LIU Mingyang Ryan | 33% | 41% | 21% | 5% | 1% | - | |
72 | LEE Justin | 1% | 10% | 28% | 36% | 21% | 4% | |
73 | OWENS Harrison J. | 6% | 26% | 38% | 24% | 6% | 1% | |
74 | ZHUANG Rayken | 8% | 27% | 35% | 22% | 7% | 1% | - |
75 | GEORGE Daniel | 1% | 13% | 34% | 34% | 15% | 3% | - |
76 | YU Thomas | 6% | 25% | 36% | 25% | 7% | 1% | - |
76 | GRYCIUK Koby | 21% | 40% | 28% | 9% | 1% | - | - |
78 | HAN Daniel Y. | 8% | 26% | 35% | 22% | 7% | 1% | - |
79 | COSGROVE Connor R. | 5% | 23% | 37% | 26% | 8% | 1% | - |
80 | EDELMAN Seth A. | 1% | 9% | 26% | 34% | 22% | 7% | 1% |
81 | DA GRACA Aidan | 2% | 13% | 31% | 34% | 17% | 3% | |
82 | DEPEW Spencer | 6% | 35% | 39% | 16% | 3% | - | |
83 | VAROQUA Tolby | 11% | 33% | 35% | 17% | 4% | - | |
84 | LEMPERT Levy A. | 1% | 8% | 26% | 36% | 23% | 6% | |
85 | RUDNET Noah | 42% | 43% | 13% | 2% | - | - | - |
86 | DESHETLER Scott | 22% | 48% | 24% | 5% | - | - | - |
87 | LEUNG Andrew K. | 14% | 41% | 32% | 11% | 2% | - | - |
88 | SUSSMAN Jamie | 48% | 43% | 9% | 1% | - | - | - |
89 | XUE ALEXANDER | 1% | 7% | 24% | 37% | 25% | 6% | |
90 | LAMHAOUAR Ryan | 13% | 35% | 34% | 15% | 3% | - | - |
91 | ZHENG Joshua | 73% | 25% | 2% | - | - | - | |
92 | HUANG Alexander C. | 1% | 10% | 26% | 33% | 22% | 7% | 1% |
92 | TISHININ Alexander D. | 2% | 13% | 30% | 32% | 17% | 4% | - |
94 | YURT Vehbi | 70% | 27% | 3% | - | - | - | |
95 | PIWOWAR Alex | 4% | 19% | 33% | 28% | 12% | 2% | - |
96 | GILBERT Spencer E. | 76% | 22% | 2% | - | - | - | |
97 | LIN Hadrian | 39% | 43% | 15% | 3% | - | - | - |
98 | MACDERMOTT Rowan | 11% | 34% | 36% | 16% | 3% | - | - |
99 | ZHANG Yankun | 43% | 40% | 15% | 3% | - | - | - |
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.