Reno-Sparks Convention Center - Reno, NV, 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 | LATIF IMRAN ZAKARIYYA | - | - | 1% | 7% | 35% | 57% | |
| 2 | MANN Jake R. | - | - | - | 1% | 9% | 35% | 55% |
| 3 | DAVOODIAN Christopher | - | - | - | 1% | 11% | 38% | 50% |
| 3 | NORMILE Nicholas | - | 6% | 22% | 37% | 28% | 7% | |
| 5 | ROMANOV Ethan | - | - | 1% | 6% | 24% | 42% | 27% |
| 6 | LEE Stewart S. | - | - | - | 4% | 20% | 43% | 33% |
| 7 | LOISEAU Eliott | - | 1% | 6% | 21% | 36% | 29% | 9% |
| 8 | SOBESHKEVYCH ROMAN | - | 2% | 12% | 31% | 35% | 17% | 3% |
| 9 | KIM Jayden | - | 2% | 11% | 29% | 35% | 19% | 4% |
| 10 | ROBINSON Samuel | - | 5% | 22% | 37% | 28% | 8% | |
| 11 | KUGLER Luke | - | 1% | 9% | 29% | 40% | 20% | |
| 12 | WU Jonathan | - | - | - | 3% | 16% | 41% | 40% |
| 13 | SAVORETTI Francesco | - | - | 3% | 15% | 35% | 36% | 11% |
| 14 | LIU Yueri | - | - | 3% | 15% | 34% | 36% | 12% |
| 15 | CHEN Leonardo | - | 1% | 8% | 26% | 40% | 24% | |
| 16 | LAI Boden | - | 1% | 9% | 29% | 41% | 20% | |
| 17 | SEEFELDT William Henry C. | 1% | 9% | 28% | 37% | 21% | 4% | |
| 18 | WONG Baron | - | 3% | 17% | 36% | 33% | 10% | |
| 19 | LIU Adam | - | 2% | 12% | 30% | 34% | 18% | 3% |
| 20 | PARKER Isaiah | - | 2% | 11% | 30% | 36% | 18% | 3% |
| 21 | JAIN Samyak | 1% | 9% | 30% | 37% | 19% | 4% | |
| 22 | HUANG Kenneth | - | 3% | 18% | 37% | 31% | 11% | 1% |
| 23 | KIM Sullivan | - | - | - | 1% | 9% | 35% | 55% |
| 24 | SAVORETTI Pietro | 2% | 13% | 31% | 33% | 17% | 4% | - |
| 25 | HAMZA Tudor | - | 2% | 12% | 33% | 38% | 15% | |
| 26 | CHEN Zhengyang (Allen) | 1% | 7% | 26% | 39% | 23% | 5% | |
| 27 | DOUBOV Andrew | - | 2% | 13% | 31% | 34% | 17% | 3% |
| 28 | CHOI Kaiden I. | - | 2% | 13% | 32% | 37% | 16% | |
| 29 | LEE JoonWon | - | - | 4% | 16% | 35% | 33% | 11% |
| 30 | XIA Dashan | - | - | 2% | 12% | 32% | 38% | 16% |
| 31 | MIZRAHI Michael | - | 3% | 18% | 34% | 30% | 12% | 2% |
| 32 | TANG William | - | 2% | 10% | 28% | 37% | 21% | 3% |
| 33 | FU Leon | - | - | 2% | 14% | 41% | 43% | |
| 34 | GUMEDELLI Mohnish | 1% | 12% | 31% | 33% | 17% | 5% | < 1% |
| 35 | CARRIER Gabriel A. | - | - | - | 1% | 7% | 33% | 59% |
| 36 | ERLIKHMAN Adrian | - | 1% | 7% | 24% | 37% | 25% | 6% |
| 37 | CHEN Brian | - | - | 2% | 12% | 31% | 38% | 17% |
| 38 | LO Jake | - | - | - | 4% | 18% | 42% | 36% |
| 39 | GINZBURG Adam | - | 1% | 5% | 19% | 36% | 31% | 9% |
| 40 | PAK Elliot | - | 3% | 17% | 37% | 34% | 9% | |
| 41 | CHOI Zachary | - | 1% | 9% | 30% | 41% | 19% | |
| 42 | SONG Troy | - | 1% | 6% | 22% | 37% | 28% | 8% |
| 43 | TSE Maxwell | - | 1% | 6% | 21% | 37% | 29% | 7% |
| 44 | TRAN Spencer | - | 2% | 13% | 32% | 35% | 16% | 2% |
| 45 | CHEN YiHeng | 1% | 7% | 24% | 35% | 25% | 8% | 1% |
| 46 | DANIELS Jonah | - | 3% | 14% | 32% | 34% | 16% | 2% |
| 47 | KIM Gene | 1% | 9% | 26% | 35% | 22% | 6% | - |
| 48 | ZHU Eric | 1% | 7% | 24% | 35% | 25% | 8% | 1% |
| 49 | YAO Geoffrey B. | - | 1% | 9% | 29% | 40% | 20% | |
| 50 | LI Yunji (Rain) | 2% | 17% | 37% | 31% | 11% | 1% | |
| 51 | MUENKE Magnus | 3% | 16% | 33% | 32% | 14% | 2% | |
| 52 | LEE Aiden | 1% | 8% | 25% | 36% | 24% | 7% | 1% |
| 53 | YU Austin | - | 2% | 12% | 31% | 36% | 17% | 2% |
| 54 | LU Jacob | - | 2% | 16% | 36% | 32% | 12% | 1% |
| 55 | LI Tristan | 2% | 16% | 34% | 31% | 14% | 3% | - |
| 56 | HE Zhiheng | - | 1% | 7% | 23% | 36% | 26% | 7% |
| 56 | ALI Farhan | - | 5% | 18% | 34% | 30% | 11% | 1% |
| 58 | TIEN Jabin | - | - | 4% | 17% | 34% | 33% | 12% |
| 59 | MEHROTRA Neel | 1% | 6% | 22% | 36% | 26% | 8% | 1% |
| 60 | MCDOWELL Will | - | 2% | 11% | 30% | 36% | 18% | 3% |
| 61 | MCLAREN Mason | 10% | 44% | 34% | 11% | 2% | - | - |
| 62 | WANG Jason | 12% | 34% | 35% | 16% | 3% | - | - |
| 63 | WU Alistair | - | 3% | 14% | 31% | 33% | 17% | 3% |
| 64 | KIM Alexander | 25% | 42% | 26% | 7% | 1% | - | |
| 65 | LIU Yikun | - | 1% | 7% | 23% | 36% | 26% | 7% |
| 66 | WANG justin | - | - | 4% | 18% | 36% | 32% | 9% |
| 67 | WANG Joey | - | 1% | 8% | 23% | 35% | 26% | 7% |
| 68 | TIKHOMIROV Theodore | - | 2% | 14% | 36% | 39% | 9% | |
| 69 | LI Timothy | 8% | 29% | 37% | 20% | 5% | 1% | - |
| 70 | KHANNA Nikhil | - | - | 1% | 6% | 22% | 41% | 30% |
| 71 | LEE Aiden | - | 4% | 19% | 34% | 29% | 12% | 2% |
| 72 | LOUIE Joseph | 7% | 28% | 39% | 21% | 4% | - | |
| 73 | LEE Royce | 5% | 22% | 36% | 27% | 10% | 1% | |
| 74 | XIE Brandon | 1% | 10% | 28% | 35% | 21% | 4% | |
| 75 | SANTOS Antonio K. | - | 2% | 11% | 28% | 36% | 20% | 3% |
| 76 | BORISENKO Samuel | - | 2% | 13% | 31% | 33% | 17% | 3% |
| 77 | HU Robert J. | - | 2% | 10% | 28% | 37% | 21% | 3% |
| 78 | CHANG Andrew | 2% | 13% | 32% | 33% | 16% | 3% | - |
| 79 | SIM Ian | - | 8% | 26% | 35% | 23% | 7% | 1% |
| 80 | WONG King-Yee | - | 5% | 19% | 34% | 29% | 11% | 2% |
| 82 | SIEDOW William | 2% | 15% | 32% | 32% | 16% | 3% | - |
| 83 | LI Ray | 19% | 40% | 29% | 10% | 2% | - | - |
| 84 | LI Grayson | 17% | 37% | 31% | 12% | 2% | - | - |
| 85 | AGGELER Donovan | 1% | 11% | 29% | 35% | 19% | 5% | - |
| 86 | WANG Devin | 16% | 37% | 32% | 12% | 2% | - | - |
| 87 | WU Steven | 2% | 15% | 32% | 33% | 15% | 3% | |
| 88 | GLOGOWSKI Konrad | 2% | 14% | 34% | 35% | 14% | 2% | |
| 89 | WU Johnny y. | 3% | 18% | 37% | 30% | 10% | 1% | |
| 90 | SEBASTIAN Alexander P. | 1% | 12% | 31% | 35% | 18% | 3% | |
| 91 | LI Ethan R. | 7% | 28% | 37% | 21% | 5% | 1% | |
| 92 | YAMAGUCHI Yuzuki | 4% | 23% | 39% | 27% | 7% | - | |
| 93 | LEE Jayden J. | 1% | 9% | 27% | 35% | 21% | 6% | 1% |
| 94 | EMMERT JP | 6% | 25% | 37% | 24% | 7% | 1% | - |
| 95 | HE Bronto | 23% | 40% | 27% | 9% | 1% | - | - |
| 96 | KIM Remington | 28% | 43% | 23% | 6% | 1% | - | - |
| 97 | PARK Sangwook | - | 4% | 16% | 33% | 32% | 13% | 1% |
| 98 | SUH Aiden | 14% | 38% | 33% | 13% | 2% | - | - |
| 99 | ZHANG Luqi | 38% | 41% | 17% | 3% | - | - | - |
| 100 | SU Samuel | 17% | 38% | 31% | 12% | 2% | - | - |
| 101 | DEVINENI Avyang | 14% | 37% | 33% | 13% | 2% | - | - |
| 102 | MIAO Quentin | - | 8% | 28% | 38% | 22% | 4% | |
| 103 | PARKE Nathaniel | 38% | 42% | 17% | 3% | - | - | |
| 104 | PAN Anthony | 13% | 37% | 34% | 14% | 2% | - | |
| 104 | DACHELET Sawyer | 26% | 43% | 24% | 6% | 1% | - | |
| 106 | PIVOVAROV Lucas | 11% | 37% | 35% | 14% | 2% | - | |
| 107 | SANTOS Francisco M. | 7% | 28% | 37% | 22% | 6% | 1% | |
| 108 | LEE DoWon | 8% | 32% | 37% | 19% | 4% | - | |
| 109 | LIN Andrew | 34% | 43% | 19% | 4% | - | - | |
| 110 | LOISEAU Oscar | 1% | 8% | 25% | 35% | 24% | 7% | 1% |
| 111 | LIN Jason | 40% | 47% | 12% | 1% | - | - | - |
| 112 | AHMED Mohsen | 1% | 8% | 24% | 36% | 24% | 7% | 1% |
| 113 | LESCURE Dimitri | - | 3% | 20% | 38% | 29% | 9% | 1% |
| 114 | HOWARD Jackson | 2% | 13% | 31% | 34% | 17% | 3% | - |
| 115 | KE Sebastian | 7% | 27% | 36% | 23% | 7% | 1% | - |
| 115 | HERDMAN Julian | 6% | 26% | 38% | 23% | 7% | 1% | - |
| 117 | MOLLINIER Angel | 12% | 43% | 33% | 11% | 2% | - | - |
| 117 | ZHANG Austin | 20% | 40% | 29% | 9% | 1% | - | - |
| 119 | GUO Woody | 15% | 36% | 32% | 13% | 3% | - | - |
| 120 | VOO Lucas | 19% | 40% | 29% | 10% | 2% | - | - |
| 121 | LEE Jake (JiYuen) | 3% | 26% | 40% | 24% | 6% | 1% | |
| 122 | HERNDON Liam | 1% | 9% | 31% | 36% | 19% | 5% | - |
| 122 | GUO Luke | 32% | 49% | 16% | 2% | - | - | - |
| 124 | LIU Max | 54% | 37% | 8% | 1% | - | - | - |
| 125 | LEE Anton | 14% | 36% | 34% | 14% | 3% | - | - |
| 126 | WANG-SONG Evan | 17% | 39% | 30% | 11% | 2% | - | - |
| 127 | CHAKRABORTY Zorian | 5% | 24% | 37% | 25% | 8% | 1% | - |
| 128 | GANESH Maxen | 21% | 39% | 28% | 10% | 2% | - | |
| 129 | DAO Alexander | 3% | 20% | 39% | 29% | 8% | 1% | |
| 130 | GADHVI Darius | 42% | 42% | 14% | 2% | - | - | |
| 131 | KOU Mason | 68% | 29% | 3% | - | - | - | - |
| 132 | SONG Jonathan | 84% | 15% | 1% | - | - | - | - |
| 133 | LIGHT Luke | 24% | 42% | 26% | 7% | 1% | - | - |
| 134 | OLIVAS Joseph | 70% | 26% | 4% | - | - | - | |
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.