Meadowlands Expo Center - 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 | BOUDREAUX James | - | - | - | - | 4% | 29% | 68% |
2 | VYSOTSKIY Evan | - | - | 1% | 6% | 24% | 42% | 27% |
3 | SINGLETON Aman | - | - | 1% | 5% | 21% | 42% | 31% |
3 | LIU Adam | - | - | - | 2% | 12% | 40% | 45% |
5 | LI Ryan | 2% | 11% | 29% | 34% | 19% | 5% | 1% |
6 | MIDYANY Evan | - | - | - | 4% | 27% | 69% | |
7 | AHMED Mohsen | - | - | - | 3% | 16% | 40% | 40% |
8 | KIM Gene | - | - | - | 4% | 19% | 42% | 34% |
9 | YI Nathan | - | - | - | 4% | 19% | 42% | 34% |
10 | YANG Gary | - | - | - | 1% | 8% | 35% | 56% |
11 | GUMEDELLI Mohnish | - | 1% | 5% | 20% | 37% | 30% | 8% |
12 | MOSTOVOY philip | - | 1% | 8% | 30% | 43% | 19% | |
13 | CRESPO Nathaniel Justus | - | - | 3% | 15% | 36% | 35% | 11% |
14 | KABA Elias | - | 1% | 5% | 19% | 36% | 30% | 9% |
15 | LYCHKO Maksym | - | - | 3% | 13% | 34% | 36% | 14% |
16 | NORMILE Nicholas | - | - | - | - | 3% | 24% | 73% |
17 | TSE Maxwell | - | - | - | 1% | 8% | 34% | 58% |
18 | SHCHUR Grayson | - | - | 1% | 9% | 37% | 45% | 9% |
19 | YAMAGUCHI Yuzuki | - | - | 1% | 8% | 25% | 40% | 25% |
20 | KIM Henry | - | - | - | 1% | 8% | 38% | 53% |
21 | CHEN Edward | - | 1% | 7% | 23% | 37% | 26% | 6% |
22 | LEE Anton | - | - | 1% | 9% | 32% | 45% | 14% |
23 | SOLARZ Arthur | - | - | 4% | 18% | 36% | 32% | 10% |
24 | TRAN Spencer | - | - | - | 2% | 13% | 39% | 45% |
25 | TANG Michael | - | 1% | 9% | 27% | 38% | 21% | 3% |
26 | LUO Alexander | - | 1% | 5% | 17% | 34% | 33% | 10% |
27 | DODIN Daniel M. | - | - | 1% | 8% | 26% | 40% | 25% |
28 | MIDYANY Ryan | - | - | 2% | 11% | 31% | 39% | 18% |
29 | TESFAYE Elias | - | - | 2% | 10% | 29% | 39% | 20% |
29 | OCONNOR Paul | 4% | 20% | 34% | 28% | 11% | 2% | - |
31 | LI Jade | - | - | 2% | 14% | 35% | 38% | 11% |
32 | MEDISETTI Arjun | 4% | 21% | 37% | 27% | 9% | 1% | - |
33 | LEE Aiden | - | - | 1% | 5% | 20% | 42% | 32% |
34 | DANG William | - | 4% | 16% | 32% | 32% | 14% | 1% |
35 | SONG Aidan | - | 1% | 8% | 25% | 36% | 24% | 6% |
36 | ZHANG jonathan | - | 4% | 17% | 32% | 31% | 14% | 2% |
37 | CHANEY Charles | 2% | 10% | 27% | 34% | 21% | 5% | 1% |
38 | LIN ZIJIE | 3% | 15% | 31% | 31% | 16% | 4% | - |
39 | WANG-SONG Evan | - | 1% | 7% | 24% | 37% | 25% | 5% |
40 | KIM Remington | - | - | 4% | 23% | 46% | 24% | 3% |
41 | O'LONGAIGH Sunkhar | - | 1% | 4% | 17% | 35% | 34% | 10% |
41 | ZHANG Austin | - | 3% | 14% | 31% | 34% | 16% | 2% |
43 | KHERSONSKY Robert | - | 5% | 22% | 37% | 27% | 8% | 1% |
44 | ARMSTRONG Payson | 1% | 7% | 23% | 36% | 25% | 8% | 1% |
45 | YU David | 2% | 15% | 34% | 33% | 14% | 2% | - |
46 | HELMY Richard | - | 5% | 22% | 41% | 26% | 5% | |
47 | CHEN Jayden | - | - | 5% | 23% | 44% | 27% | |
48 | AU Joshua | 9% | 33% | 37% | 17% | 3% | - | |
49 | HENNESSY Levon | - | 4% | 15% | 31% | 33% | 15% | 2% |
50 | KIM Julian | - | 1% | 8% | 25% | 37% | 24% | 5% |
51 | WU Matthew | 2% | 13% | 29% | 33% | 18% | 5% | - |
52 | NG Nico | 1% | 8% | 23% | 34% | 25% | 8% | 1% |
53 | KENDLER Micah | 2% | 16% | 36% | 31% | 12% | 2% | - |
54 | WANG Marcus | - | 3% | 14% | 31% | 33% | 17% | 3% |
55 | ZHENG Jason | 7% | 25% | 34% | 24% | 8% | 1% | - |
56 | KROPP Wesley | - | - | 4% | 16% | 34% | 34% | 12% |
57 | YAO Tristan | - | 2% | 14% | 37% | 36% | 11% | 1% |
58 | MA Nolan | 1% | 6% | 25% | 40% | 25% | 3% | |
59 | CHANG Matthew | - | 4% | 15% | 31% | 32% | 16% | 3% |
60 | ZHANG Marcus | 4% | 18% | 32% | 29% | 14% | 3% | - |
61 | LEE DoWon | - | - | < 1% | 5% | 21% | 43% | 31% |
61 | CHEN Isaac Zhi | - | 1% | 7% | 24% | 39% | 25% | 4% |
63 | HAN Keyi | 2% | 10% | 26% | 33% | 22% | 7% | 1% |
64 | GU Eric | 5% | 20% | 34% | 28% | 11% | 2% | - |
65 | DYCKMAN Benjamin | - | 5% | 20% | 36% | 28% | 9% | 1% |
66 | WANG Jason | - | 2% | 11% | 29% | 36% | 20% | 4% |
67 | CAFASSO Alexander | - | 1% | 10% | 29% | 37% | 19% | 3% |
68 | THOMAS Ethan | - | 5% | 18% | 33% | 29% | 12% | 2% |
69 | TOPRANI Valmik | 4% | 17% | 32% | 30% | 14% | 3% | - |
70 | LEE Daniel | - | 4% | 17% | 33% | 31% | 13% | 2% |
71 | ZHU Yiming | - | 3% | 14% | 29% | 32% | 18% | 4% |
72 | ZHANG Chaoyi(Joey) | - | 3% | 16% | 38% | 33% | 10% | 1% |
73 | CUELLAR Markus | 3% | 22% | 42% | 27% | 7% | 1% | |
74 | TANG Luke | 4% | 24% | 40% | 26% | 6% | - | |
75 | ZHANG Jonathan | - | 5% | 23% | 37% | 26% | 7% | 1% |
76 | KATS Brandon | 1% | 9% | 26% | 34% | 22% | 7% | 1% |
77 | PENG Ethan | 1% | 11% | 31% | 36% | 18% | 4% | - |
78 | TSIEN Richard | 1% | 10% | 26% | 34% | 22% | 6% | 1% |
79 | FOGEL Jake | 7% | 25% | 35% | 24% | 8% | 1% | - |
80 | GOVOROV Alexander | 6% | 25% | 36% | 24% | 7% | 1% | - |
81 | YUE Bryan | 7% | 26% | 35% | 23% | 8% | 1% | - |
82 | SI Anderson | 8% | 26% | 35% | 23% | 7% | 1% | - |
83 | ZHOU Zhi Matthew | 1% | 11% | 30% | 34% | 19% | 5% | - |
84 | NOOL Alexander | - | 3% | 14% | 31% | 33% | 16% | 3% |
85 | FENG Xinmin | 10% | 30% | 34% | 19% | 5% | 1% | - |
86 | KURUGANTI Vivaan | 13% | 35% | 34% | 15% | 3% | - | - |
87 | ADDYSON Aidan | 1% | 8% | 29% | 40% | 20% | 2% | |
88 | DAI Jason | 4% | 19% | 35% | 29% | 11% | 2% | - |
88 | CHEN Evan | 1% | 8% | 23% | 35% | 26% | 8% | - |
90 | CAMP William | 1% | 8% | 30% | 42% | 17% | 2% | - |
91 | CHIANG William | 2% | 17% | 35% | 31% | 13% | 2% | - |
92 | YAKHNIS Seth | 2% | 13% | 33% | 34% | 15% | 3% | - |
93 | ZHANG Shuhao | 27% | 41% | 24% | 7% | 1% | - | - |
93 | CHEN Cameron | 5% | 25% | 41% | 23% | 5% | - | - |
95 | BHANDARE Veer | 8% | 26% | 35% | 23% | 7% | 1% | - |
96 | YAO Ryan | 1% | 8% | 23% | 35% | 25% | 8% | 1% |
96 | CHO Adrian | 5% | 27% | 37% | 23% | 7% | 1% | - |
98 | NAM Nathaniel | 1% | 10% | 26% | 33% | 22% | 7% | 1% |
98 | LEE Ryan | 28% | 45% | 23% | 4% | - | - | - |
100 | MA Joseph | 12% | 39% | 35% | 13% | 2% | - | - |
101 | WANG Marcus | 15% | 35% | 32% | 15% | 3% | - | - |
102 | WEISELBERG Mark | 2% | 12% | 29% | 33% | 19% | 5% | - |
102 | BENNETT Nathaniel | 3% | 15% | 32% | 31% | 15% | 3% | - |
104 | YOON Jonathan | 6% | 30% | 42% | 19% | 3% | - | - |
105 | KIM Doyun | 6% | 28% | 38% | 22% | 6% | 1% | - |
106 | LAI Jayden | 8% | 30% | 36% | 20% | 6% | 1% | - |
107 | ZHENG Jasper | 33% | 41% | 20% | 5% | 1% | - | - |
108 | MOSLEY Wally | - | 5% | 21% | 35% | 28% | 10% | 1% |
109 | CHEN Daniel | 10% | 39% | 37% | 13% | 2% | - | |
110 | DING Max | 4% | 19% | 33% | 29% | 12% | 2% | - |
111 | MASKIN Mikhail | 4% | 19% | 35% | 29% | 11% | 2% | - |
112 | FRIZZELL Kai | 8% | 27% | 34% | 22% | 7% | 1% | - |
112 | LIU Andrew | - | 5% | 19% | 33% | 29% | 12% | 2% |
114 | OH Ted | 17% | 38% | 31% | 12% | 2% | - | - |
115 | LANE Sawyer | 7% | 36% | 40% | 15% | 2% | - | - |
116 | BANG Dylan | 8% | 27% | 34% | 22% | 7% | 1% | - |
117 | SHI Evan | 41% | 41% | 15% | 3% | - | - | - |
118 | BO Genero | 2% | 11% | 27% | 34% | 21% | 6% | 1% |
118 | ZHOU Luke | 5% | 21% | 36% | 27% | 10% | 1% | - |
120 | SHAO Mason | 21% | 40% | 29% | 10% | 2% | - | - |
121 | YAO Aiden | 2% | 12% | 29% | 34% | 19% | 5% | - |
122 | LEE Joshua | 11% | 34% | 35% | 16% | 4% | - | - |
122 | WELCH Sebastian | 58% | 34% | 7% | 1% | - | - | - |
124 | MADRIGAL SALVAT Guillermo | 4% | 19% | 34% | 29% | 12% | 2% | - |
125 | HONG Ethen | 7% | 31% | 37% | 20% | 5% | 1% | - |
126 | SHAPIRO Samuel | 8% | 27% | 35% | 22% | 7% | 1% | - |
127 | NOOL Aaron | 6% | 31% | 39% | 20% | 5% | - | - |
128 | MCGANN Grant | 41% | 41% | 15% | 3% | - | - | - |
129 | ZINCHUK Yuri | 3% | 18% | 35% | 30% | 12% | 2% | - |
130 | JAISING Aaditya | 51% | 38% | 10% | 1% | - | - | - |
131 | KIM Louie | 53% | 38% | 9% | 1% | - | - | |
132 | SMITH Theo | 27% | 42% | 24% | 6% | 1% | - | - |
133 | SHI Peyton | 35% | 43% | 19% | 3% | - | - | |
134 | CARCELLER Jeremias | 8% | 27% | 36% | 22% | 7% | 1% | - |
135 | ROBINSON Blake | 55% | 36% | 9% | 1% | - | - | - |
136 | NABI Mikhail | 23% | 45% | 26% | 6% | - | - | - |
137 | WU Jiachen | 11% | 31% | 34% | 18% | 5% | 1% | - |
138 | PREVOST Landon | 41% | 42% | 14% | 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.