Santa Clara Convention Center - Santa Clara, CA, 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 | LI Howard | - | - | - | 1% | 6% | 33% | 60% |
2 | JOO Jeein | - | - | - | - | 4% | 29% | 66% |
3 | GREMILLION Obadiah | - | 2% | 10% | 26% | 34% | 22% | 5% |
3 | HWANG Jayden | - | - | - | 1% | 6% | 31% | 62% |
5 | ANDRES Michael | - | - | - | 4% | 20% | 49% | 27% |
6 | CHON Collin | - | - | - | 2% | 12% | 39% | 47% |
7 | KIM ELIJAH | - | - | - | - | 4% | 28% | 67% |
8 | YAP Kah Kai (Cayden) | - | - | - | 2% | 12% | 40% | 46% |
9 | LI AYDEN | - | - | - | 4% | 20% | 43% | 32% |
10 | TSE Aiden J | - | - | 1% | 5% | 21% | 41% | 32% |
11 | LI linze | - | 2% | 17% | 45% | 30% | 6% | |
12 | KITSON Chase | - | 1% | 10% | 32% | 41% | 17% | |
13 | WONG Lucas | - | 5% | 23% | 39% | 26% | 6% | - |
14 | KANG Jeremy | - | - | 2% | 12% | 32% | 38% | 16% |
15 | HOLZ Lucas | - | 1% | 4% | 16% | 33% | 33% | 13% |
16 | HO Anson | - | 1% | 8% | 25% | 38% | 24% | 3% |
17 | GAY Jono | - | - | 2% | 9% | 26% | 39% | 24% |
18 | YU Casey | - | 4% | 16% | 31% | 31% | 15% | 3% |
19 | VUONG Kyle Ka-Him | - | 1% | 8% | 27% | 39% | 22% | 3% |
20 | KOVALEV Daniil N. | - | - | 1% | 8% | 38% | 53% | |
21 | CHAN Henry | - | 1% | 6% | 24% | 39% | 25% | 5% |
22 | CAO Donald | - | 1% | 5% | 21% | 38% | 29% | 7% |
23 | WANG Tiger | - | - | 2% | 11% | 32% | 39% | 15% |
24 | SUNG Julian | - | 2% | 11% | 30% | 37% | 18% | 2% |
25 | CRICOL Damian | - | 5% | 21% | 36% | 27% | 9% | 1% |
26 | SHA Walter | 2% | 15% | 31% | 32% | 16% | 4% | - |
27 | GREENSTEIN Viktor | - | - | 4% | 20% | 40% | 30% | 4% |
28 | RONG Jasper | - | 2% | 12% | 29% | 34% | 19% | 3% |
29 | NGUYEN Lomani | 2% | 16% | 37% | 32% | 12% | 2% | - |
30 | KOZLOFF Wyatt | 1% | 6% | 24% | 37% | 25% | 7% | - |
31 | NIKOLOV Ruben | 2% | 16% | 34% | 31% | 14% | 3% | - |
32 | SANCHEZ Jacob | - | 1% | 6% | 22% | 40% | 27% | 4% |
33 | VO Landon | - | 4% | 18% | 35% | 30% | 11% | 1% |
34 | TANI Tino | - | - | 1% | 5% | 23% | 42% | 29% |
35 | YANG Phillip | - | - | 2% | 12% | 31% | 38% | 17% |
36 | WONG Hawken | - | 1% | 7% | 26% | 38% | 23% | 5% |
37 | SANGSTER Arden | - | 4% | 18% | 34% | 30% | 12% | 2% |
38 | LUC Cedric | 4% | 25% | 41% | 24% | 5% | - | |
39 | IM Tyler | 1% | 10% | 27% | 34% | 22% | 6% | - |
40 | TANG Morgan | - | 1% | 10% | 30% | 39% | 18% | 2% |
41 | HE Zhikai (kyle) | 7% | 24% | 34% | 24% | 9% | 2% | - |
42 | KROON Landon | - | 1% | 8% | 26% | 39% | 22% | 4% |
43 | WINTERSET Mason | 5% | 26% | 41% | 23% | 4% | - | |
44 | CHI Everett | - | 6% | 26% | 41% | 23% | 4% | |
45 | WANG Edward | 1% | 9% | 29% | 38% | 20% | 4% | - |
46 | CHEN Cooper | 1% | 8% | 23% | 33% | 24% | 9% | 1% |
47 | ZHANG KAIQI | 1% | 7% | 23% | 35% | 25% | 8% | 1% |
48 | GU Andrew | - | 3% | 17% | 36% | 31% | 11% | 1% |
49 | LI Yidong A. | - | - | 4% | 18% | 37% | 32% | 8% |
50 | IYER Neil | 1% | 7% | 26% | 37% | 23% | 6% | - |
51 | LEE Nathan Uju | - | 2% | 13% | 33% | 35% | 15% | 1% |
51 | SLIGAR Jackson | - | 2% | 15% | 33% | 33% | 15% | 2% |
51 | SU Kingston | 11% | 34% | 35% | 16% | 3% | - | - |
54 | BEKDJANOV Arthur | - | 1% | 9% | 28% | 38% | 21% | 3% |
55 | ZHAO Aidan | 4% | 19% | 33% | 28% | 13% | 3% | - |
56 | KANG Matthew | - | - | 3% | 19% | 44% | 33% | |
57 | ANUMULA Aryan | 4% | 18% | 33% | 29% | 13% | 3% | - |
58 | LUC Linkin | 2% | 12% | 28% | 32% | 20% | 6% | 1% |
59 | MINASIAN Mason | 2% | 14% | 31% | 32% | 17% | 4% | - |
60 | HAO Johnny | - | 6% | 25% | 36% | 24% | 7% | 1% |
61 | LI Ryan | 1% | 17% | 39% | 31% | 11% | 2% | - |
62 | YOUNG Navin | 23% | 43% | 26% | 7% | 1% | - | - |
63 | ROSALES Vincent | 4% | 28% | 40% | 22% | 5% | 1% | - |
64 | LIU Daniel | 2% | 11% | 27% | 34% | 20% | 6% | 1% |
65 | EKAMBARAM Nikhil | 13% | 34% | 34% | 16% | 4% | - | - |
66 | SRIVATSAV Ishaan | 3% | 17% | 33% | 31% | 14% | 3% | - |
67 | LIU Daniel | 2% | 27% | 41% | 24% | 6% | 1% | - |
68 | ROH Jaden | 24% | 45% | 25% | 5% | - | - | |
69 | WONG David | 9% | 32% | 37% | 17% | 4% | - | - |
70 | NAIR Sujit | 3% | 18% | 35% | 31% | 12% | 2% | - |
71 | XIAO haoyu | 8% | 29% | 36% | 21% | 6% | 1% | - |
72 | WANG Yongen | 2% | 28% | 41% | 23% | 6% | 1% | - |
73 | GRIGORIEV Roman | 1% | 6% | 20% | 34% | 28% | 10% | 1% |
73 | MA Oliver | 1% | 5% | 18% | 32% | 29% | 13% | 2% |
75 | NGUYEN Dylan | 14% | 38% | 33% | 12% | 2% | - | - |
76 | HWANG Hagan | - | 1% | 6% | 20% | 35% | 29% | 9% |
76 | GU Kevin | 18% | 37% | 30% | 12% | 2% | - | - |
78 | SEELMAN Cole | 21% | 40% | 28% | 9% | 1% | - | - |
79 | VENKATRAMAN Sudhir | - | 2% | 12% | 31% | 35% | 17% | 3% |
79 | LI Coby | - | 4% | 15% | 29% | 31% | 17% | 4% |
81 | YUEN Caleb | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
82 | LIANG Preston | 14% | 35% | 33% | 14% | 3% | - | - |
83 | SRIVATSAV Anay | 23% | 40% | 27% | 9% | 1% | - | - |
84 | BAGGA Shray | 4% | 24% | 41% | 25% | 5% | - | |
85 | BURDE Braylen | 9% | 34% | 38% | 17% | 3% | - | |
86 | JOUFFLINEAU Yohann | 2% | 16% | 38% | 32% | 11% | 1% | - |
87 | QI Jeremy | 1% | 9% | 28% | 36% | 21% | 5% | - |
88 | GRAEHL Ian | 3% | 18% | 35% | 30% | 11% | 2% | - |
89 | LIU Yijin | 2% | 13% | 31% | 33% | 17% | 4% | - |
90 | LEE Bill King | 23% | 42% | 27% | 7% | 1% | - | - |
91 | HAN Kyle | 24% | 40% | 26% | 8% | 1% | - | - |
92 | VENKATRAMAN Sushil | 6% | 27% | 37% | 23% | 6% | 1% | - |
92 | VAN ROY Ray | 17% | 43% | 30% | 9% | 1% | - | - |
94 | BRADIC Andreja | 38% | 41% | 17% | 3% | - | - | - |
95 | SLOAN Ethan | 37% | 44% | 17% | 3% | - | - | - |
96 | LIU Ryan | 46% | 41% | 12% | 1% | - | - | |
97 | PARK Emerson | 15% | 34% | 32% | 15% | 4% | - | - |
98 | HONG Arick | 27% | 44% | 23% | 5% | 1% | - | - |
98 | YU Albert | 89% | 10% | - | - | - | - | - |
100 | BAERENWALD Tybalt Wolfram | 1% | 8% | 25% | 35% | 23% | 6% | - |
101 | MUTYALA Kavin | 62% | 32% | 6% | - | - | - | - |
102 | ROATH Tristan | 4% | 20% | 37% | 30% | 10% | 1% | |
103 | COOK Ridgely | 84% | 15% | 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.