Gaylord National Resort and Convention Center - National Harbor, MD, 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 | FISHMAN Rahm | - | - | - | 1% | 7% | 39% | 53% |
| 2 | CHEN Zhengyang (Allen) | - | - | - | 2% | 15% | 41% | 41% |
| 3 | MITEV Alexander | - | - | 1% | 7% | 31% | 50% | 12% |
| 3 | LAM Alan | - | - | - | - | 7% | 38% | 54% |
| 5 | HEADRICK Jack | - | 1% | 5% | 20% | 39% | 31% | 5% |
| 6 | BOUDREAUX James | - | - | - | 1% | 6% | 33% | 60% |
| 7 | KIM Henry | - | - | - | 4% | 19% | 42% | 34% |
| 8 | YANG Gary | - | 1% | 9% | 27% | 36% | 22% | 5% |
| 9 | WOLFE Alex | - | - | - | - | 6% | 32% | 62% |
| 10 | DOUBOV Andrew | - | - | 1% | 11% | 33% | 40% | 15% |
| 11 | PENG Yue | - | 2% | 11% | 29% | 37% | 19% | 3% |
| 12 | LEE Anton | - | 1% | 5% | 20% | 38% | 30% | 5% |
| 13 | MIDYANY Evan | - | - | 3% | 16% | 39% | 36% | 6% |
| 14 | TIKHONOV Daniel | - | - | - | 4% | 21% | 44% | 31% |
| 15 | ZIEGLER John | - | - | 1% | 8% | 25% | 40% | 25% |
| 16 | CHEN Brian | - | - | - | 1% | 6% | 32% | 61% |
| 17 | TIKHONOV Ilia | - | - | - | 1% | 7% | 36% | 57% |
| 18 | SINGLETON Aman | - | - | 1% | 5% | 25% | 50% | 19% |
| 18 | CHEN Leonardo | - | - | - | 2% | 13% | 40% | 45% |
| 20 | LE BORGNE Matthieu | - | - | - | - | 4% | 29% | 67% |
| 21 | ALI Farhan | - | 1% | 6% | 26% | 45% | 21% | |
| 22 | NORMILE Nicholas | - | - | 4% | 19% | 38% | 31% | 8% |
| 23 | CHUNG Andrew | - | - | 3% | 16% | 36% | 34% | 11% |
| 24 | TRAN Spencer | - | - | 4% | 19% | 39% | 32% | 6% |
| 25 | PETROW Zoryan | - | - | 2% | 14% | 35% | 36% | 13% |
| 26 | ZOGRAFOS Nicholas | - | - | 3% | 14% | 32% | 35% | 15% |
| 27 | BORISENKO Samuel | - | - | - | 3% | 16% | 42% | 39% |
| 27 | EVANS George | - | 4% | 16% | 34% | 33% | 12% | 1% |
| 29 | LI Tristan | - | 1% | 5% | 18% | 36% | 32% | 9% |
| 29 | VYSOTSKIY Evan | - | 1% | 8% | 29% | 40% | 20% | 2% |
| 31 | KIM Joshua | - | 1% | 9% | 28% | 38% | 21% | 3% |
| 32 | CHA Patrick | - | 6% | 24% | 37% | 25% | 8% | 1% |
| 33 | GINZBURG Adam | - | - | - | - | 5% | 31% | 63% |
| 34 | YU Austin | - | - | 1% | 8% | 27% | 41% | 21% |
| 35 | CHEN Ryan | - | - | 3% | 15% | 35% | 36% | 11% |
| 36 | KABA Elias | - | 7% | 26% | 37% | 23% | 6% | 1% |
| 37 | MAO Benjamin | - | - | - | - | 5% | 30% | 65% |
| 38 | TIKHOMIROV Theodore | - | - | 1% | 7% | 25% | 42% | 25% |
| 39 | SHOUSHA Hamza | - | - | - | 5% | 27% | 50% | 18% |
| 39 | LIU Adam | - | - | 1% | 8% | 28% | 41% | 22% |
| 41 | YI Nathan | - | - | 4% | 20% | 41% | 29% | 6% |
| 42 | VAN JAARSVELD Leo | 1% | 11% | 29% | 35% | 19% | 5% | - |
| 43 | TSE Kirby Zhiheng | - | - | - | 2% | 15% | 41% | 41% |
| 44 | JIANG Harry | 7% | 26% | 35% | 23% | 8% | 1% | - |
| 45 | LEE Aiden | - | - | 3% | 17% | 44% | 35% | |
| 46 | LEE DoWon | - | 1% | 10% | 31% | 40% | 18% | |
| 47 | SAUNIER Cameron | - | - | 1% | 10% | 31% | 41% | 16% |
| 48 | RIGGINS Joshua | - | - | - | - | 3% | 24% | 72% |
| 49 | RIM Eugene | - | - | 3% | 15% | 36% | 36% | 10% |
| 50 | CHEN Bowen | - | - | 4% | 17% | 38% | 35% | 7% |
| 51 | MEHROTRA Neel | - | 2% | 12% | 30% | 35% | 17% | 3% |
| 52 | GUMEDELLI Mohnish | - | 4% | 21% | 38% | 28% | 9% | 1% |
| 53 | BRADSHAW Carter | - | 3% | 15% | 34% | 33% | 13% | 2% |
| 54 | CRESPO Nathaniel Justus | - | 9% | 30% | 36% | 20% | 5% | - |
| 55 | YAMAGUCHI Yuzuki | - | 2% | 11% | 28% | 34% | 20% | 4% |
| 56 | ZHANG Jonathan | 1% | 8% | 24% | 35% | 25% | 7% | - |
| 57 | CHEN Isaac Zhi | 1% | 8% | 28% | 37% | 21% | 5% | - |
| 58 | RVACHEV Michael | 1% | 6% | 24% | 39% | 25% | 6% | |
| 59 | LEE Aiden | - | 1% | 9% | 29% | 41% | 20% | |
| 60 | SINGH Ravin | - | - | 1% | 9% | 29% | 41% | 20% |
| 61 | ZHU Yiming | 1% | 10% | 34% | 38% | 15% | 2% | - |
| 62 | GANTSOUDES Isaac | - | 2% | 12% | 32% | 37% | 16% | 2% |
| 63 | BAGDONAS Olivier | 6% | 25% | 36% | 24% | 7% | 1% | - |
| 64 | GRIGORENKO Gleb E. | 11% | 32% | 34% | 18% | 4% | - | - |
| 65 | HSU Joshua | - | 2% | 12% | 28% | 34% | 19% | 4% |
| 66 | CHANEY Charles | 3% | 16% | 33% | 31% | 14% | 3% | - |
| 67 | AHMED Mohsen | - | - | 1% | 8% | 31% | 46% | 14% |
| 68 | KROPP Wesley | 2% | 12% | 31% | 34% | 17% | 4% | - |
| 69 | HERNDON Liam | - | 1% | 8% | 26% | 39% | 23% | 2% |
| 70 | WANG Jiacheng | - | 4% | 25% | 41% | 24% | 6% | - |
| 71 | LUO Alexander | 1% | 8% | 26% | 37% | 22% | 5% | - |
| 71 | HE Yurui | 1% | 7% | 23% | 37% | 25% | 7% | - |
| 71 | DONG Haiyi | - | - | 5% | 22% | 38% | 27% | 7% |
| 74 | MALHAM Andrew | 1% | 10% | 28% | 35% | 20% | 5% | - |
| 75 | BAI Brian | - | 4% | 24% | 40% | 26% | 6% | - |
| 76 | ZHANG Albert | - | 3% | 18% | 37% | 31% | 9% | 1% |
| 77 | KIM Gene | - | - | 4% | 21% | 42% | 30% | 4% |
| 78 | ARMSTRONG TyLee | 1% | 9% | 30% | 37% | 19% | 4% | - |
| 79 | HENNESSY Levon | 1% | 6% | 22% | 35% | 27% | 9% | 1% |
| 80 | CUMMINGS Owen | - | 7% | 32% | 39% | 18% | 3% | - |
| 81 | TSIEN Richard | 2% | 16% | 36% | 32% | 12% | 2% | - |
| 82 | LIN Haley | 1% | 8% | 27% | 38% | 22% | 4% | - |
| 83 | NOOL Alexander | 1% | 10% | 28% | 37% | 20% | 4% | - |
| 84 | CZEPLA Andrew | 2% | 13% | 31% | 34% | 16% | 3% | - |
| 85 | ARMSTRONG Payson | 2% | 14% | 38% | 34% | 11% | 1% | - |
| 86 | ROSADO Balthazar Francisco | - | 2% | 11% | 29% | 38% | 19% | 2% |
| 87 | YU David | 11% | 32% | 35% | 18% | 4% | - | - |
| 88 | WANG Aiden | - | 4% | 16% | 34% | 33% | 12% | 1% |
| 89 | ZHANG Austin | 4% | 18% | 33% | 29% | 13% | 3% | - |
| 90 | LIDSKY Phineas | - | 1% | 6% | 21% | 38% | 28% | 6% |
| 91 | KE Sebastian | - | 3% | 17% | 37% | 32% | 10% | 1% |
| 92 | TOWNSHEND Connor | 2% | 14% | 32% | 34% | 16% | 3% | - |
| 93 | RAMEY Daylon | 18% | 38% | 31% | 12% | 2% | - | - |
| 94 | ROBERTS Phoenix | 2% | 12% | 28% | 33% | 19% | 6% | 1% |
| 94 | MOU Jaydon | 4% | 21% | 36% | 28% | 10% | 1% | - |
| 96 | LEE Benjamin | 2% | 18% | 39% | 30% | 10% | 1% | - |
| 97 | DELONG Joshua | 3% | 16% | 34% | 32% | 14% | 2% | - |
| 98 | KONG Brandon | - | 3% | 15% | 32% | 33% | 14% | 2% |
| 99 | OZBAY Alp | 10% | 31% | 36% | 19% | 5% | - | - |
| 100 | SOLOMON Aryeh | 13% | 34% | 33% | 16% | 3% | - | - |
| 100 | SZIEDE Kieran | 1% | 13% | 35% | 34% | 15% | 3% | - |
| 102 | DAVIS Andrew | 24% | 42% | 26% | 7% | 1% | - | |
| 103 | NG Nico | 9% | 32% | 38% | 18% | 3% | - | |
| 104 | CHEN Tianjun | 16% | 38% | 33% | 11% | 2% | - | |
| 105 | ADDYSON Aidan | 6% | 34% | 39% | 17% | 3% | - | - |
| 106 | CHEN Jayden | - | 1% | 6% | 20% | 34% | 29% | 9% |
| 107 | LEECH Braedan | 1% | 11% | 34% | 36% | 16% | 3% | - |
| 108 | WANG Marcus | 1% | 10% | 26% | 34% | 22% | 7% | 1% |
| 109 | CHO Alex | - | 3% | 13% | 29% | 33% | 17% | 3% |
| 110 | TUMULA Arihaan | 7% | 25% | 36% | 24% | 8% | 1% | - |
| 111 | DONNELLY Enzo | - | 1% | 8% | 31% | 43% | 16% | 1% |
| 111 | FOGEL Jake | 23% | 43% | 26% | 7% | 1% | - | - |
| 113 | LEE Henry | 8% | 26% | 35% | 22% | 7% | 1% | - |
| 114 | GAO Victor | 1% | 11% | 33% | 36% | 16% | 2% | - |
| 115 | HALE Bradley | 25% | 46% | 24% | 5% | - | - | - |
| 116 | SATISHKUMAR Pranav | 11% | 33% | 36% | 16% | 3% | - | |
| 117 | BENNETT Pierce | 15% | 38% | 33% | 12% | 2% | - | |
| 118 | CHAWLA Aarav | 2% | 15% | 35% | 34% | 12% | 1% | |
| 119 | HERDMAN Julian | 1% | 10% | 36% | 37% | 14% | 2% | - |
| 120 | LORENZ Nathan | 24% | 47% | 24% | 5% | - | - | - |
| 121 | CAFASSO Alexander | 3% | 16% | 33% | 31% | 14% | 3% | - |
| 122 | SUNKARA Vishnu | 13% | 33% | 33% | 16% | 4% | 1% | - |
| 122 | BAYUS Oliver | 5% | 22% | 34% | 26% | 11% | 2% | - |
| 124 | LI Ryan | 8% | 28% | 37% | 21% | 5% | 1% | - |
| 125 | MARKOWITZ Sam | 2% | 34% | 41% | 18% | 4% | - | - |
| 126 | HANNA Alexander | 10% | 31% | 35% | 18% | 4% | - | - |
| 127 | GOODMAN Liam | 14% | 36% | 34% | 14% | 3% | - | - |
| 128 | JARRATT Isaac | 6% | 24% | 35% | 25% | 8% | 1% | - |
| 129 | MARIN Ayan N. | 3% | 15% | 32% | 32% | 16% | 3% | - |
| 130 | TSEN Mason | 4% | 20% | 37% | 28% | 9% | 1% | - |
| 131 | OLSON Joseph | 9% | 31% | 37% | 19% | 4% | - | |
| 132 | SHAFFER Tyler | 1% | 9% | 27% | 38% | 22% | 4% | - |
| 133 | KIM Remington | - | 4% | 19% | 38% | 31% | 8% | 1% |
| 134 | ROBERTS Arthur | 15% | 36% | 33% | 13% | 2% | - | - |
| 135 | LIN ZIJIE | 12% | 32% | 34% | 17% | 4% | 1% | - |
| 136 | VENZON Gavin | 23% | 42% | 27% | 8% | 1% | - | - |
| 137 | SONG Ryan | 10% | 32% | 36% | 18% | 4% | - | - |
| 138 | BO Genero | 13% | 36% | 34% | 14% | 3% | - | - |
| 139 | MAXWELL Sheito | 22% | 43% | 27% | 7% | 1% | - | - |
| 140 | HURLEY Michael | 29% | 50% | 18% | 2% | - | - | - |
| 141 | PERI Mourya | 14% | 37% | 34% | 14% | 2% | - | - |
| 142 | BEREKNYEI Lukas | - | 1% | 9% | 28% | 37% | 20% | 3% |
| 143 | DANG William | 3% | 17% | 37% | 32% | 11% | 1% | - |
| 144 | GRIGGS Kaiden | 27% | 43% | 24% | 6% | 1% | - | - |
| 145 | LEE Carson | 2% | 14% | 32% | 33% | 16% | 3% | - |
| 146 | PENG Ethan | 28% | 42% | 23% | 6% | 1% | - | - |
| 147 | GATEWOOD Michael | 11% | 31% | 35% | 18% | 5% | 1% | - |
| 148 | SMOTHERS Nathan | 27% | 43% | 23% | 5% | 1% | - | - |
| 149 | ZHENG Jason | 18% | 42% | 30% | 9% | 1% | - | - |
| 150 | LEE Harrison | 14% | 35% | 33% | 15% | 3% | - | - |
| 151 | YAO Tristan | 10% | 31% | 36% | 18% | 4% | - | - |
| 152 | TSANG Aiden | 18% | 39% | 30% | 11% | 2% | - | - |
| 152 | CHEN Jayden | 47% | 42% | 10% | 1% | - | - | - |
| 154 | KARLEKAR Veer | 9% | 49% | 33% | 8% | 1% | - | - |
| 155 | BROSNAN Solomon | 18% | 40% | 30% | 10% | 2% | - | - |
| 156 | YAZDANFAR Marius | 12% | 35% | 35% | 15% | 3% | - | - |
| 157 | SLAVIN Tamir | 34% | 47% | 17% | 2% | - | - | - |
| 157 | GRANT Aidan | 75% | 23% | 2% | - | - | - | - |
| 157 | REKHI Krish | 6% | 26% | 38% | 24% | 6% | 1% | - |
| 160 | HUANG Max | 19% | 39% | 30% | 10% | 2% | - | - |
| 161 | KIM Zac | 21% | 43% | 28% | 8% | 1% | - | - |
| 162 | WELCH Sebastian | 85% | 14% | 1% | - | - | - | - |
| 163 | FENG Xinmin | 39% | 45% | 14% | 2% | - | - | - |
| 164 | QI Bryan | 43% | 46% | 11% | 1% | - | - | - |
| 164 | JUSTA Rivan | 3% | 19% | 35% | 29% | 11% | 2% | - |
| 166 | MACTOUGH Ben | 60% | 33% | 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.