Ontario Convention Center - Ontario, 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 | SANCHEZ Jacob | - | - | - | 1% | 15% | 46% | 38% |
2 | KOVALEV Daniil N. | - | - | - | 3% | 26% | 72% | |
3 | TANI Tino | - | - | - | 3% | 17% | 43% | 36% |
3 | IYER Neil | - | - | 4% | 17% | 34% | 33% | 12% |
5 | WONG David | - | - | - | 5% | 34% | 45% | 16% |
6 | BRIMMER Robert (Trey) | - | - | 2% | 10% | 29% | 39% | 20% |
7 | KOVACHEV Martin | - | - | 3% | 15% | 36% | 35% | 11% |
8 | LUC Cedric | - | - | 5% | 25% | 45% | 25% | |
9 | LI AYDEN | - | - | - | 2% | 12% | 41% | 45% |
10 | KANG Matthew | - | - | - | - | 4% | 30% | 65% |
11 | YANG Phillip | - | - | - | 3% | 17% | 44% | 36% |
12 | ZHANG Kaixuan | - | - | - | 4% | 19% | 42% | 35% |
13 | ZHANG KAIQI | - | - | 2% | 12% | 34% | 40% | 13% |
14 | GRIGORIEV Roman | - | 1% | 7% | 30% | 43% | 19% | |
15 | ANUMULA Aryan | - | 3% | 18% | 40% | 32% | 8% | |
16 | IM Tyler | - | - | - | 4% | 20% | 44% | 31% |
17 | LI Yidong A. | - | - | - | 3% | 15% | 40% | 41% |
18 | LEE Brian | - | - | - | 3% | 19% | 45% | 32% |
18 | WANG Matthew | - | - | 3% | 16% | 35% | 34% | 12% |
20 | TAN Rui | - | - | 1% | 10% | 31% | 41% | 17% |
21 | BROWN Andrew | - | 1% | 9% | 27% | 37% | 21% | 4% |
22 | CRICOL Damian | - | - | 1% | 11% | 33% | 40% | 14% |
23 | CHEN Cooper | - | 1% | 6% | 22% | 39% | 27% | 5% |
24 | LEE Nathan Uju | - | 1% | 8% | 39% | 45% | 8% | |
25 | LUC Linkin | - | - | - | 5% | 26% | 48% | 20% |
26 | WANG Tiger | - | - | 2% | 12% | 33% | 38% | 15% |
27 | LIU Daniel | 2% | 13% | 31% | 32% | 17% | 4% | - |
28 | LEE Brady | - | - | - | 1% | 10% | 42% | 47% |
29 | GREENSTEIN Viktor | - | - | 1% | 9% | 29% | 41% | 20% |
30 | VO Blake | - | 1% | 10% | 28% | 38% | 20% | 3% |
31 | CHAN Henry | - | - | - | 6% | 36% | 44% | 14% |
32 | SUN Andy | - | 3% | 16% | 36% | 32% | 11% | 1% |
33 | KIM Suin | - | 5% | 22% | 38% | 27% | 7% | 1% |
34 | TANG Morgan | - | - | 3% | 15% | 36% | 35% | 11% |
35 | SOULES-ONO Makoa | - | 2% | 15% | 48% | 32% | 3% | |
36 | WINTERSET Mason | - | - | 3% | 16% | 35% | 34% | 12% |
37 | WONG Hawken | - | 1% | 6% | 25% | 40% | 24% | 4% |
38 | KANG Jeremy | - | - | 1% | 5% | 24% | 46% | 24% |
39 | LIU Yijin | - | - | 2% | 13% | 36% | 40% | 8% |
40 | CHI Everett | - | - | 4% | 18% | 36% | 32% | 10% |
41 | DOOLEY Atticus | - | 1% | 11% | 31% | 36% | 18% | 3% |
42 | QI Jeremy | - | 3% | 14% | 34% | 36% | 13% | 1% |
43 | BRUM Charles E. | - | 1% | 8% | 31% | 42% | 17% | 2% |
44 | TENG Lucas | 2% | 14% | 34% | 33% | 14% | 2% | - |
45 | FISCHER Noel | 2% | 14% | 34% | 33% | 14% | 2% | - |
46 | YUEN Caleb | - | 7% | 25% | 37% | 24% | 7% | 1% |
46 | SUN Eon | 3% | 21% | 40% | 28% | 8% | 1% | - |
48 | LIN Ethan | 2% | 14% | 39% | 38% | 7% | - | - |
50 | LI Ryan | - | 5% | 22% | 36% | 26% | 9% | 1% |
51 | WESTMORELAND-BROWN Cole | 2% | 11% | 28% | 34% | 19% | 5% | - |
52 | TALLARICO Leonardo | - | 1% | 9% | 28% | 36% | 21% | 4% |
53 | WANG James | 1% | 9% | 26% | 34% | 22% | 7% | 1% |
54 | FUGATE Logan | 30% | 48% | 19% | 3% | - | - | |
55 | HAO Johnny | - | 1% | 8% | 25% | 36% | 24% | 5% |
55 | IRVINE Patrick | 1% | 6% | 23% | 37% | 26% | 7% | 1% |
57 | HRISTOV Nickolas | 1% | 10% | 27% | 34% | 21% | 6% | 1% |
58 | YUE Ivan | 8% | 36% | 38% | 16% | 3% | - | - |
59 | DUFF Michael | 2% | 13% | 33% | 35% | 15% | 2% | - |
60 | MOORE Greyson | 3% | 21% | 40% | 27% | 8% | 1% | - |
61 | OU Rigel | - | 3% | 15% | 31% | 32% | 16% | 3% |
62 | LIU Paul | 14% | 44% | 35% | 6% | - | - | |
63 | SU Eric | 4% | 19% | 37% | 29% | 10% | 1% | - |
64 | LEE Brendan | 2% | 17% | 42% | 30% | 8% | 1% | |
65 | GATTO Enzo P. | 1% | 9% | 26% | 34% | 23% | 7% | 1% |
66 | YANG Jake | 7% | 29% | 38% | 21% | 5% | - | - |
67 | HAN Kyle | 16% | 40% | 32% | 11% | 2% | - | - |
68 | SHEN Hudson | 3% | 18% | 36% | 31% | 11% | 2% | - |
69 | YOUNG Navin | 1% | 8% | 32% | 40% | 17% | 2% | - |
70 | 曾 ZIMO | - | 6% | 22% | 37% | 27% | 8% | 1% |
71 | KIM Leo | 37% | 42% | 18% | 3% | - | - | - |
72 | LIU Clarence | 1% | 10% | 36% | 38% | 14% | 2% | - |
73 | LOPEZ Mateo | 5% | 23% | 38% | 26% | 7% | 1% | - |
74 | CHOI LIAM | 11% | 32% | 34% | 17% | 4% | 1% | - |
75 | WANG Ryan | 4% | 20% | 35% | 28% | 11% | 2% | - |
76 | XIE Justin | 14% | 41% | 35% | 10% | 1% | - | - |
77 | CHEN Aaron | 3% | 19% | 36% | 30% | 11% | 2% | - |
78 | VENKATRAMAN Sushil | 7% | 27% | 38% | 22% | 6% | 1% | - |
79 | WANG David | 1% | 11% | 31% | 36% | 18% | 4% | - |
80 | WU Garrick | 12% | 40% | 37% | 10% | 1% | - | |
81 | WU Allen | 36% | 47% | 15% | 2% | - | - | - |
82 | LO Elroy | 14% | 38% | 34% | 12% | 2% | - | - |
83 | AN Chris | 34% | 46% | 17% | 2% | - | - | |
84 | GUO Jonathan | 19% | 38% | 29% | 11% | 2% | - | - |
85 | ORLINO Sam | 16% | 39% | 32% | 11% | 2% | - | - |
86 | WU Dustin | 29% | 48% | 20% | 3% | - | - | - |
87 | BRADIC Andreja | 5% | 24% | 39% | 25% | 7% | 1% | - |
88 | HERRERA Stefano | 22% | 41% | 28% | 8% | 1% | - | - |
89 | EKAMBARAM Rithik | 10% | 33% | 36% | 17% | 3% | - | - |
90 | LI Sky | 80% | 19% | 2% | - | - | - | - |
91 | YPHANTIDES Alexander | - | 7% | 27% | 40% | 22% | 5% | - |
92 | WEATHERBEE Liam | 56% | 35% | 8% | 1% | - | - | - |
93 | DING Orlando | 6% | 30% | 43% | 19% | 2% | - | - |
94 | KIM Derek | 29% | 41% | 23% | 6% | 1% | - | - |
95 | FERRING Theo | 20% | 40% | 29% | 9% | 1% | - | - |
96 | WARD Carter | 28% | 43% | 23% | 5% | - | - | - |
97 | LIANG Preston | 5% | 24% | 38% | 25% | 7% | 1% | - |
97 | RAMBHIA Smit | 3% | 29% | 40% | 22% | 6% | 1% | - |
97 | ZHOU Ruibo | 8% | 39% | 38% | 13% | 2% | - | - |
100 | GRIFFIN Sid | 39% | 45% | 15% | 1% | - | - | |
101 | NAZIF Laith | 32% | 44% | 20% | 4% | - | - | - |
102 | RHODES Bryce | 31% | 42% | 21% | 5% | - | - | - |
103 | KIM Enoch | 52% | 38% | 9% | 1% | - | - | - |
104 | SINGH Swaran | 38% | 44% | 16% | 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.