Golisano Training Center at Nazareth University - Rochester, NY, 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 | MIDYANY Evan | - | - | - | 2% | 16% | 48% | 34% |
| 2 | HUANG Kenneth | - | - | - | 2% | 15% | 42% | 41% |
| 3 | KIM Henry | - | - | - | 1% | 10% | 37% | 52% |
| 3 | LEE DoWon | - | - | 1% | 8% | 26% | 41% | 24% |
| 5 | LIU Adam | - | - | - | - | 7% | 39% | 54% |
| 6 | AHMED Mohsen | - | - | - | 3% | 15% | 41% | 41% |
| 7 | KIM Gene | - | - | - | 2% | 15% | 48% | 35% |
| 8 | YI Nathan | - | - | - | 4% | 21% | 44% | 31% |
| 9 | CAO Gavin | - | 2% | 11% | 29% | 38% | 19% | 2% |
| 10 | MEHROTRA Neel | - | - | - | 4% | 19% | 43% | 33% |
| 11 | SINGLETON Aman | - | - | - | 4% | 18% | 43% | 35% |
| 12 | TESFAYE Elias | - | - | 3% | 15% | 33% | 35% | 13% |
| 13 | BOUDREAUX James | - | - | - | - | 3% | 22% | 75% |
| 14 | ARMSTRONG TyLee | - | - | 1% | 6% | 26% | 43% | 24% |
| 15 | LUO Alexander | - | 1% | 8% | 25% | 37% | 24% | 5% |
| 16 | NG Nico | 1% | 6% | 20% | 33% | 28% | 11% | 1% |
| 17 | TARCHICHI Robby | - | - | - | - | 6% | 38% | 56% |
| 18 | YAMAGUCHI Yuzuki | - | - | 1% | 6% | 23% | 42% | 28% |
| 19 | DODIN Daniel M. | - | - | - | 4% | 23% | 52% | 21% |
| 20 | DURKIN Hudson | - | 1% | 4% | 17% | 34% | 33% | 11% |
| 21 | LEE Anton | - | - | 2% | 12% | 33% | 39% | 13% |
| 21 | LI Jade | - | - | - | 4% | 26% | 50% | 18% |
| 23 | DANG William | - | 5% | 19% | 34% | 29% | 11% | 2% |
| 24 | SHCHUR Grayson | - | - | 2% | 12% | 32% | 39% | 15% |
| 25 | HE Bronto | - | 5% | 17% | 33% | 30% | 13% | 2% |
| 26 | KABA Elias | - | - | 2% | 13% | 34% | 38% | 13% |
| 27 | ZHANG Jonathan | - | 1% | 6% | 26% | 46% | 19% | 2% |
| 27 | CRESPO Nathaniel Justus | - | - | 3% | 14% | 35% | 36% | 12% |
| 29 | MIDYANY Ryan | - | - | 3% | 16% | 37% | 34% | 10% |
| 30 | MA YIXING (Tiger) | - | - | 1% | 8% | 27% | 41% | 23% |
| 31 | CHEN Tianjun | 3% | 23% | 39% | 26% | 8% | 1% | - |
| 32 | HELMY Richard | - | 1% | 5% | 18% | 35% | 32% | 10% |
| 33 | DANILOV Artur | - | 4% | 23% | 39% | 26% | 7% | 1% |
| 34 | LEE Harrison | - | 4% | 17% | 34% | 32% | 12% | 1% |
| 34 | TOWNSHEND Connor | 1% | 6% | 21% | 35% | 27% | 9% | 1% |
| 36 | TSIEN Richard | 3% | 15% | 31% | 31% | 16% | 4% | - |
| 37 | ZHANG Marcus | 2% | 14% | 32% | 32% | 16% | 3% | - |
| 38 | GU Eric | 1% | 9% | 28% | 35% | 21% | 5% | - |
| 39 | CHEN Isaac Zhi | - | 1% | 7% | 26% | 39% | 23% | 4% |
| 40 | ZHU Yiming | 1% | 7% | 25% | 35% | 24% | 7% | 1% |
| 41 | NOOL Aaron | 1% | 7% | 26% | 39% | 23% | 4% | - |
| 42 | LIN ZIJIE | 1% | 7% | 22% | 34% | 26% | 9% | 1% |
| 43 | NOOL Alexander | - | 4% | 19% | 35% | 30% | 11% | 1% |
| 44 | FONG Kobe | 1% | 6% | 20% | 33% | 28% | 11% | 1% |
| 45 | WHITE Jackson | 4% | 20% | 33% | 28% | 12% | 2% | - |
| 46 | MASKIN Mikhail | - | 4% | 17% | 34% | 32% | 12% | 1% |
| 47 | CAFASSO Alexander | - | 1% | 5% | 21% | 38% | 29% | 7% |
| 48 | SOLOMON Aryeh | - | 4% | 19% | 39% | 31% | 7% | - |
| 49 | LEE Leo | 3% | 18% | 34% | 30% | 13% | 2% | - |
| 50 | MA Owen | 5% | 24% | 38% | 26% | 6% | 1% | - |
| 51 | FRIZZELL Kai | 2% | 15% | 35% | 33% | 13% | 2% | - |
| 52 | FOGEL Jake | 7% | 25% | 35% | 24% | 8% | 1% | - |
| 53 | MA Joseph | 10% | 31% | 35% | 18% | 5% | - | - |
| 54 | BOBORIS Dimitrios | 9% | 33% | 38% | 17% | 3% | - | - |
| 55 | WU Jiachen | 18% | 39% | 31% | 11% | 2% | - | - |
| 56 | QU RuiTing | 1% | 7% | 23% | 35% | 26% | 8% | 1% |
| 57 | CUELLAR Markus | 4% | 19% | 35% | 29% | 11% | 2% | - |
| 58 | WANG Eason | 4% | 20% | 34% | 28% | 12% | 2% | - |
| 59 | HANNA Alexander | 10% | 31% | 36% | 18% | 4% | - | - |
| 60 | GRIGORENKO Gleb E. | - | 8% | 33% | 38% | 17% | 3% | - |
| 61 | STRAFFORD Andrew | 13% | 37% | 35% | 13% | 2% | - | - |
| 62 | FENG Xinmin | 11% | 30% | 34% | 19% | 5% | 1% | - |
| 63 | GAO Ryan | 62% | 31% | 6% | 1% | - | - | - |
| 64 | KIM Louie | 26% | 43% | 25% | 6% | - | - | - |
| 65 | HUANG Max | 6% | 30% | 39% | 20% | 4% | - | - |
| 66 | SHAPIRO Samuel | 4% | 19% | 34% | 29% | 11% | 2% | - |
| 67 | SONG Aidan | - | 1% | 6% | 21% | 37% | 28% | 7% |
| 68 | ZHAI Junqi | - | 2% | 10% | 28% | 36% | 20% | 3% |
| 69 | LIU-XUE Shuliang | 11% | 33% | 35% | 17% | 4% | - | - |
| 70 | ZHOU Zhi Matthew | 2% | 15% | 34% | 32% | 15% | 3% | - |
| 71 | MAZEL Antonin | 15% | 38% | 33% | 12% | 2% | - | - |
| 72 | CHIANG William | 2% | 15% | 33% | 33% | 15% | 3% | - |
| 73 | PUTHOFF Henry | 1% | 10% | 31% | 38% | 18% | 2% | - |
| 74 | VANDERMEER Joshua | 8% | 27% | 35% | 22% | 7% | 1% | - |
| 75 | ZHANG Shuhao | 7% | 48% | 34% | 9% | 1% | - | - |
| 76 | SHAO Mason | 5% | 22% | 36% | 27% | 9% | 1% | - |
| 77 | ARMSTRONG Payson | - | 3% | 17% | 38% | 33% | 8% | 1% |
| 77 | MEDISETTI Arjun | 1% | 14% | 34% | 32% | 15% | 3% | - |
| 79 | ZINCHUK Yuri | 3% | 20% | 36% | 29% | 11% | 2% | - |
| 80 | SI Anderson | 3% | 21% | 37% | 27% | 10% | 2% | - |
| 81 | WANG Marcus | 4% | 22% | 37% | 27% | 9% | 1% | - |
| 82 | PENG Ethan | 2% | 19% | 39% | 29% | 9% | 1% | - |
| 83 | ZHENG Jasper | 10% | 31% | 35% | 19% | 5% | 1% | - |
| 84 | CHEN Daniel | 12% | 32% | 34% | 17% | 4% | 1% | - |
| 84 | ZHENG Jason | 3% | 20% | 39% | 29% | 9% | 1% | - |
| 86 | WU Matthew | 7% | 26% | 35% | 23% | 8% | 1% | - |
| 87 | ZHAO Brandon | 5% | 25% | 40% | 25% | 5% | - | - |
| 88 | LEE Ryan | 41% | 40% | 15% | 3% | - | - | - |
| 89 | MADRIGAL SALVAT Guillermo | 1% | 8% | 26% | 35% | 23% | 7% | 1% |
| 90 | CHAN Ian | 54% | 36% | 9% | 1% | - | - | - |
| 91 | WELCH Sebastian | 57% | 35% | 8% | 1% | - | - | - |
| 92 | CHEN Jayden A | 19% | 39% | 30% | 10% | 2% | - | - |
| 93 | DAI Jason | 9% | 30% | 36% | 20% | 5% | 1% | - |
| 94 | ROBERTS Arthur | 1% | 12% | 31% | 35% | 18% | 4% | - |
| 95 | YOON Jonathan | 12% | 34% | 34% | 16% | 3% | - | - |
| 96 | MUELLER Travis | 51% | 38% | 10% | 1% | - | - | - |
| 97 | MALLAKIS Efstathios | 13% | 37% | 35% | 13% | 2% | - | - |
| 97 | DALY Liam | 75% | 23% | 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.