Boston, MA - Boston, MA, 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 | KIM Nicholas W. | - | - | - | 1% | 8% | 36% | 55% |
2 | ONIK Elijah T. | - | - | 2% | 15% | 35% | 35% | 13% |
3 | FU Samuel Y. | - | - | - | 5% | 23% | 44% | 28% |
3 | BAE Kevin | - | - | 1% | 8% | 29% | 44% | 18% |
5 | CHENG Jonathan | - | - | - | 2% | 13% | 41% | 45% |
6 | AZUELA Maximo | - | 3% | 14% | 30% | 33% | 17% | 3% |
7 | COSTELLO Chaissen F. | - | 1% | 8% | 22% | 34% | 27% | 9% |
8 | BING Charles | - | - | - | 2% | 15% | 43% | 40% |
9 | HUTH Mitchell | - | - | - | 5% | 25% | 46% | 24% |
10 | KAO Castor T. | - | 1% | 9% | 31% | 41% | 17% | |
11 | DAI Jonathan T. | - | - | 4% | 21% | 46% | 30% | |
12 | LIANG Lixi (Henry) | - | - | - | 1% | 10% | 36% | 53% |
13 | LI Richard | - | - | - | 4% | 20% | 43% | 32% |
14 | ZELTSER Lawrence M. | - | 1% | 5% | 19% | 35% | 30% | 10% |
15 | SINGH Dayaal | - | 1% | 7% | 28% | 44% | 21% | |
16 | RUSADZE Nickolas | - | - | 3% | 15% | 34% | 35% | 13% |
17 | HOOSHI Dylan M. | - | - | - | 2% | 15% | 42% | 40% |
18 | KEE Andrew L. | - | - | 3% | 17% | 39% | 33% | 7% |
19 | KIM Yonjae | - | - | 5% | 24% | 45% | 27% | |
20 | NAGER Noah | - | - | 4% | 16% | 34% | 34% | 12% |
21 | KIM Tei D. | - | - | - | 4% | 23% | 45% | 28% |
22 | GRAHAM Roy J. | - | - | - | - | 6% | 36% | 57% |
23 | DU Samuel R. | - | - | 2% | 13% | 34% | 38% | 13% |
24 | AHN Jun | - | 6% | 27% | 43% | 21% | 3% | |
25 | LEE Joshua | - | - | - | 4% | 25% | 53% | 18% |
26 | HOOSHI Jayden C. | - | - | 2% | 11% | 30% | 38% | 18% |
27 | GEOGHEGAN Ronan | - | 2% | 10% | 30% | 37% | 18% | 3% |
28 | TSAI Max W. | - | 2% | 14% | 34% | 35% | 13% | 2% |
29 | LI Owen | - | - | 1% | 12% | 35% | 39% | 12% |
30 | PAN Eric | 1% | 8% | 23% | 34% | 25% | 8% | 1% |
31 | ZHANG Evan | - | 1% | 10% | 30% | 38% | 18% | 3% |
32 | MARX Jackson L. | - | - | 7% | 27% | 40% | 22% | 4% |
33 | KWON Ethan | - | - | 3% | 15% | 37% | 36% | 9% |
34 | SYOMICHEV Gleb A. | 4% | 19% | 34% | 28% | 12% | 2% | - |
35 | SICHITIU Alexander | - | 3% | 13% | 28% | 33% | 19% | 4% |
36 | WANG Jonathan | - | 2% | 16% | 39% | 32% | 10% | 1% |
37 | XU Jia Bao (Bowen) | - | - | 1% | 11% | 34% | 40% | 14% |
38 | LEE Aidan | - | - | 7% | 26% | 38% | 23% | 5% |
39 | WU Alexander | - | 1% | 7% | 27% | 41% | 22% | 3% |
40 | ANTON Nathaniel | - | 1% | 11% | 35% | 40% | 12% | 1% |
41 | WANG Alex L. | 2% | 25% | 45% | 23% | 4% | - | - |
42 | YU Jason | - | 5% | 24% | 41% | 24% | 5% | - |
43 | CATINO Brennen | - | 6% | 31% | 40% | 19% | 4% | - |
44 | ORVANANOS Jorge | 1% | 15% | 40% | 33% | 10% | 1% | |
45 | MARX Oscar L. | - | - | 4% | 22% | 45% | 29% | |
46 | PAE Jonathan L. | - | - | 4% | 22% | 47% | 27% | |
47 | MCLEAN Miles K. | 1% | 8% | 30% | 39% | 19% | 3% | |
48 | PAE Brian L. | - | 2% | 10% | 27% | 36% | 21% | 3% |
49 | DAVIDSON Elliot | 16% | 39% | 32% | 12% | 2% | - | - |
50 | GAO Anthony | - | 10% | 32% | 36% | 17% | 3% | - |
51 | MIALL Steven A. | - | - | 9% | 30% | 37% | 19% | 4% |
52 | XIANG Derrick | 2% | 19% | 42% | 29% | 7% | 1% | - |
53 | ZHEN Ethan | - | 3% | 22% | 41% | 26% | 6% | - |
54 | GUO Sean | 2% | 33% | 43% | 19% | 3% | - | |
55 | SHIN Joshua J. | 1% | 12% | 35% | 36% | 14% | 2% | |
56 | QI Steve | 13% | 40% | 35% | 11% | 1% | - | |
57 | FORTUNE Alexander J. | 27% | 46% | 23% | 4% | - | - | |
58 | CHEN Kyle P. | 1% | 11% | 27% | 33% | 21% | 6% | 1% |
59 | TSIMIKLIS Yanni | 2% | 14% | 32% | 32% | 16% | 4% | - |
60 | LOU Darren | 7% | 25% | 35% | 24% | 8% | 1% | - |
61 | ALIMI Yacine A. | - | 3% | 21% | 45% | 26% | 4% | - |
62 | LI Eric | - | - | 5% | 24% | 42% | 25% | 5% |
63 | JIANG Owen | - | 6% | 28% | 41% | 21% | 4% | |
64 | LEE Jacob J | 9% | 29% | 35% | 20% | 6% | 1% | - |
65 | GU Andrew | - | 1% | 21% | 39% | 28% | 9% | 1% |
66 | XU Xinhao ( Sonny) | 9% | 31% | 37% | 19% | 4% | - | - |
67 | MENG Zhaoyi | 1% | 8% | 25% | 35% | 23% | 7% | 1% |
68 | GONG Benjamin | - | - | 3% | 19% | 40% | 30% | 8% |
69 | LIN James G. | - | 2% | 19% | 40% | 30% | 8% | 1% |
70 | LI Matthew | 2% | 17% | 34% | 31% | 13% | 3% | - |
71 | SONG Austin | 6% | 25% | 37% | 24% | 7% | 1% | - |
72 | LI Chenglang Ryan | 8% | 38% | 38% | 13% | 2% | - | - |
73 | TANG August L. | 1% | 6% | 22% | 37% | 26% | 8% | 1% |
73 | TORRES Treston | 13% | 34% | 33% | 15% | 4% | - | - |
75 | WECHSLER Jacob | 1% | 10% | 29% | 37% | 19% | 4% | - |
76 | SVERDLOV Seth | 8% | 32% | 39% | 18% | 3% | - | - |
77 | MITRA Debarghya | 15% | 44% | 34% | 6% | - | - | - |
78 | LI Jinghua E. | 1% | 13% | 38% | 34% | 12% | 2% | - |
79 | ACHILOV Sayid | 2% | 13% | 30% | 33% | 17% | 4% | - |
80 | XU Ethan | 7% | 30% | 41% | 19% | 3% | - | |
81 | LIN Michael | - | 7% | 28% | 39% | 21% | 5% | - |
82 | WANG Mason | 18% | 47% | 29% | 6% | - | - | - |
83 | ZHANG Zixuan "Mark" | 40% | 46% | 13% | 1% | - | - | - |
84 | PROMRAT Pete | 2% | 31% | 42% | 21% | 4% | - | - |
85 | LIU Charles | 39% | 48% | 12% | 1% | - | - | - |
86 | HUA Aiden | 27% | 49% | 21% | 3% | - | - | - |
87 | GUO Justin | 7% | 29% | 38% | 21% | 5% | - | - |
88 | JIA Jing Yu | 60% | 37% | 3% | - | - | - | - |
89 | SHAO Eric | 29% | 43% | 22% | 5% | - | - | - |
90 | TANG Albert | 17% | 39% | 31% | 11% | 2% | - | - |
91 | LEWIS Nikhil I. | 87% | 13% | 1% | - | - | - | - |
92 | LIGOS Alex M. | 39% | 51% | 9% | 1% | - | - | - |
93 | LEWIS Akhil | 29% | 45% | 21% | 4% | - | - | |
93 | BAUMANN Gunnar | 36% | 43% | 17% | 3% | - | - | |
95 | LI Yao (Liam) | 3% | 15% | 32% | 31% | 15% | 3% | - |
96 | WANG Julang | 88% | 12% | 1% | - | - | - | |
97 | HUANG Eythan | 36% | 44% | 17% | 2% | - | - | - |
97 | XU Feng | 15% | 43% | 34% | 8% | 1% | - | - |
99 | ZHUANG Chuanxuan | 46% | 42% | 11% | 1% | - | - | - |
100 | LU Xiao | 30% | 62% | 8% | - | - | - | - |
101 | TING Clement | 67% | 30% | 3% | - | - | - | - |
102 | LOU Felix | 22% | 39% | 27% | 9% | 2% | - | - |
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.