Main Hall Dallas Market Center - Dallas, TX, 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 | YANG Gary | - | - | - | - | 3% | 23% | 74% |
2 | MEHROTRA Neel | - | - | - | 3% | 15% | 41% | 41% |
3 | SINGLETON Aman | - | - | - | 1% | 10% | 37% | 51% |
3 | KIM Henry | - | - | - | - | 1% | 17% | 81% |
5 | ZHAI Junqi | - | - | 1% | 5% | 23% | 45% | 27% |
6 | MIKHAIL Lucas | - | - | 2% | 10% | 28% | 39% | 21% |
7 | CHEN Tianjun | - | - | 2% | 13% | 32% | 37% | 16% |
8 | LIU Austin | - | 3% | 17% | 36% | 33% | 11% | |
9 | YILMAZ Tarik | - | - | 1% | 6% | 24% | 42% | 27% |
10 | ZHANG Albert | - | - | - | 2% | 19% | 47% | 32% |
11 | CHANEY Charles | - | 1% | 5% | 18% | 36% | 32% | 9% |
12 | KIM Julian | - | 1% | 7% | 22% | 35% | 28% | 8% |
13 | KIM Gene | - | - | - | - | 3% | 25% | 72% |
14 | PARKS-GOOD Tyler | - | 1% | 9% | 30% | 42% | 19% | |
15 | TANG Michael | - | - | 1% | 11% | 44% | 36% | 8% |
16 | ZHANG Chaoyi(Joey) | - | - | 5% | 19% | 36% | 31% | 9% |
17 | CHO Alex | - | - | 1% | 5% | 21% | 42% | 31% |
18 | KIM Leejay | - | 4% | 18% | 35% | 32% | 11% | 1% |
19 | SHIM Jae | - | 1% | 7% | 28% | 42% | 21% | |
20 | ZHENG Jason | 1% | 6% | 19% | 32% | 28% | 12% | 2% |
21 | MOORE Alexander | - | - | 3% | 15% | 34% | 35% | 13% |
22 | BRESLAV Asher | 1% | 7% | 24% | 36% | 25% | 7% | - |
23 | TSIEN Richard | - | 2% | 12% | 30% | 35% | 18% | 3% |
24 | VAN RIET Stefan | - | 2% | 14% | 34% | 36% | 14% | |
25 | KHAVKIN Alexander | 4% | 18% | 33% | 29% | 13% | 3% | - |
26 | CORTRIGHT Edmund | - | - | - | 3% | 22% | 48% | 27% |
27 | KIM Doyun | - | 1% | 6% | 23% | 39% | 27% | 4% |
28 | TUBALTSEV Evan | - | 1% | 5% | 19% | 36% | 31% | 9% |
29 | YAO Tristan | - | 5% | 20% | 34% | 29% | 11% | 1% |
30 | WU MiEr | - | 6% | 23% | 37% | 27% | 7% | |
31 | YAO Ryan | - | 4% | 18% | 39% | 31% | 8% | |
32 | FREEMAN Jake Matthew | 4% | 21% | 36% | 27% | 10% | 2% | - |
33 | WONG Kyle | 1% | 9% | 26% | 36% | 22% | 5% | - |
34 | KROPP Wesley | - | - | 1% | 8% | 29% | 42% | 20% |
35 | ZHANG Aiden | 1% | 10% | 28% | 35% | 20% | 5% | - |
36 | GEVA Reuben | - | 1% | 6% | 21% | 37% | 28% | 8% |
37 | QU RuiTing | - | 2% | 10% | 26% | 35% | 22% | 5% |
38 | CHIANG William | 1% | 8% | 24% | 34% | 24% | 8% | 1% |
39 | CHO Joshua | 8% | 35% | 37% | 16% | 3% | - | - |
40 | FEELY Benjamin | 9% | 28% | 34% | 21% | 7% | 1% | - |
41 | CHEN Aiden | - | 3% | 14% | 33% | 33% | 15% | 2% |
42 | YANG Junhu | 3% | 22% | 42% | 28% | 4% | - | - |
43 | CAFASSO Alexander | - | 3% | 16% | 34% | 33% | 13% | 1% |
43 | YAO Aiden | 2% | 13% | 30% | 32% | 17% | 4% | - |
45 | THOMAS Andrew | - | 3% | 14% | 30% | 33% | 17% | 3% |
46 | LI Andy | 1% | 11% | 28% | 35% | 20% | 5% | - |
47 | CHO Adrian | - | 2% | 11% | 26% | 34% | 21% | 5% |
48 | VEERAVALLI Pranav | - | 4% | 17% | 35% | 32% | 12% | 1% |
49 | HUA Nolan | 4% | 22% | 39% | 26% | 8% | 1% | - |
50 | LEE Leo | 4% | 18% | 33% | 29% | 13% | 2% | - |
51 | TUMULA Arihaan | - | 1% | 8% | 25% | 38% | 23% | 5% |
52 | KIM Louie | 2% | 14% | 32% | 33% | 15% | 3% | - |
53 | YUE Bryan | 5% | 21% | 35% | 27% | 10% | 2% | - |
54 | LEE Harrison | - | 4% | 18% | 35% | 32% | 11% | - |
55 | CHANG Matthew | - | 1% | 6% | 20% | 35% | 29% | 8% |
56 | SHIM Jaeyoo | - | 2% | 13% | 32% | 35% | 16% | 1% |
57 | LAU Caleb | 9% | 29% | 35% | 20% | 6% | 1% | - |
58 | DING Max | 3% | 18% | 36% | 31% | 11% | 1% | - |
59 | GARIKIPATI Tharan | 2% | 12% | 28% | 33% | 19% | 5% | - |
60 | TOY Tanner | - | 1% | 9% | 26% | 36% | 23% | 5% |
61 | ROBERTS Arthur | 1% | 11% | 29% | 34% | 20% | 5% | - |
62 | MEDISETTI Arjun | - | 2% | 10% | 29% | 38% | 20% | 1% |
63 | TREVINO Lucas | 4% | 20% | 35% | 29% | 11% | 2% | - |
64 | WU Jiachen | 2% | 13% | 30% | 32% | 17% | 5% | 1% |
65 | ZHANG Eric | 15% | 36% | 32% | 14% | 3% | - | - |
66 | CHEN Hayden | 8% | 34% | 38% | 17% | 3% | - | - |
67 | LIN Bryan | 1% | 8% | 24% | 33% | 24% | 9% | 1% |
68 | TANG Daniel | 1% | 7% | 23% | 35% | 25% | 8% | 1% |
69 | ZHU Brady | 4% | 20% | 36% | 28% | 10% | 2% | - |
70 | RODRIGUEZ Emiliano | 8% | 26% | 35% | 23% | 8% | 1% | - |
71 | HOLDEN Harrison | 8% | 31% | 39% | 19% | 4% | - | |
72 | KUYKENDALL Lucas | 53% | 37% | 9% | 1% | - | - | |
73 | CASTILLO ASHER | - | - | 9% | 31% | 38% | 18% | 3% |
74 | KESELMAN Ron | 13% | 37% | 34% | 14% | 3% | - | - |
75 | YAKUB Noah | 41% | 40% | 16% | 3% | - | - | - |
76 | WU James | 12% | 34% | 34% | 16% | 3% | - | - |
77 | DESAI Adithya | 9% | 30% | 36% | 19% | 5% | 1% | - |
78 | FEELY Samuel | 3% | 22% | 42% | 28% | 5% | - | - |
79 | CHEN Daniel | 4% | 18% | 33% | 29% | 13% | 2% | - |
80 | JERKINS Gianni | 12% | 33% | 33% | 16% | 4% | 1% | - |
81 | KNYSH IURII | 4% | 19% | 34% | 29% | 12% | 3% | - |
82 | MAXWELL Taiga | 25% | 43% | 25% | 6% | 1% | - | |
83 | MANU Aadhav | 5% | 28% | 38% | 22% | 6% | 1% | |
84 | PARK Ethan | 1% | 12% | 32% | 35% | 17% | 3% | |
85 | KUYKENDALL Logan | 45% | 39% | 13% | 2% | - | - | - |
86 | JIMENEZ PARRA Dorian D | 29% | 44% | 22% | 4% | - | - | - |
86 | PARKER Bowen | 1% | 10% | 30% | 37% | 19% | 3% | - |
88 | JENKINS James | 12% | 37% | 37% | 13% | 1% | - | - |
89 | ZHAN ETHAN | 6% | 23% | 35% | 26% | 9% | 2% | - |
89 | RAO Vibhav | - | 4% | 18% | 33% | 29% | 13% | 2% |
91 | DE LOS REYES Noah | 17% | 37% | 31% | 12% | 2% | - | - |
92 | TAN Samuel | 31% | 43% | 21% | 4% | - | - | - |
93 | LIN Edison | 13% | 37% | 34% | 14% | 3% | - | - |
94 | EFIMOV Georgii | - | 8% | 30% | 37% | 20% | 4% | - |
95 | LEE Taeryum | 5% | 23% | 38% | 25% | 8% | 1% | - |
96 | CHEN Linus | 16% | 40% | 32% | 10% | 1% | - | |
97 | FRENCH Drake | 3% | 16% | 34% | 32% | 14% | 2% | - |
97 | DISPENZA Jayan | 22% | 39% | 27% | 9% | 2% | - | - |
99 | PLUMMER Kellan | 13% | 34% | 34% | 16% | 4% | - | - |
100 | SALAKO Caleb | 35% | 42% | 19% | 4% | - | - | - |
101 | HODE Callen | 1% | 11% | 33% | 36% | 16% | 3% | - |
102 | HUANG EVAN | 39% | 43% | 16% | 2% | - | - | - |
103 | ANDRY Matthew | 2% | 12% | 27% | 32% | 20% | 6% | 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.