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 | KUGLER Luke | - | - | - | 1% | 8% | 35% | 56% |
| 2 | LI Jade | - | 1% | 9% | 32% | 42% | 17% | |
| 3 | BOUDREAUX James | - | - | - | 1% | 9% | 38% | 52% |
| 3 | AHMED Mohsen | - | 1% | 6% | 26% | 44% | 23% | |
| 5 | LEE Aiden | - | - | 1% | 8% | 36% | 56% | |
| 6 | SINGLETON Aman | - | - | 4% | 21% | 44% | 30% | |
| 7 | LEE DoWon | - | - | 3% | 12% | 30% | 37% | 18% |
| 8 | LEE Anton | - | 3% | 13% | 30% | 33% | 17% | 3% |
| 9 | HU Anton | - | 1% | 9% | 32% | 41% | 16% | |
| 10 | MA YIXING (Tiger) | - | - | 2% | 13% | 36% | 39% | 10% |
| 11 | ROSIELLO Francesco | 4% | 24% | 40% | 25% | 6% | 1% | - |
| 12 | HUANG Kenneth | - | - | 2% | 14% | 36% | 37% | 10% |
| 13 | KABA Elias | - | 3% | 13% | 29% | 33% | 18% | 4% |
| 14 | YAMAGUCHI Yuzuki | - | 1% | 6% | 21% | 35% | 28% | 8% |
| 15 | KIM Gene | - | - | 4% | 22% | 45% | 28% | |
| 16 | TOWNSHEND Connor | 1% | 11% | 30% | 35% | 19% | 4% | - |
| 17 | LIU Adam | - | - | 4% | 20% | 43% | 32% | |
| 18 | ARMSTRONG TyLee | - | 1% | 5% | 19% | 38% | 32% | 6% |
| 19 | RIM Eugene | - | 1% | 10% | 32% | 41% | 16% | |
| 20 | CRESPO Nathaniel Justus | 3% | 22% | 40% | 27% | 7% | 1% | |
| 21 | TESFAYE Elias | - | 1% | 14% | 38% | 36% | 11% | |
| 22 | GLUSHKOV David | - | 2% | 12% | 29% | 34% | 18% | 4% |
| 23 | CAFASSO Alexander | 1% | 6% | 22% | 36% | 27% | 8% | 1% |
| 24 | MARIN Ayan N. | 9% | 29% | 35% | 20% | 6% | 1% | - |
| 25 | BAI Brian | 4% | 21% | 38% | 28% | 9% | 1% | |
| 26 | CHEN Isaac Zhi | 1% | 7% | 26% | 39% | 22% | 4% | |
| 27 | DURKIN Hudson | - | 3% | 18% | 40% | 31% | 8% | |
| 28 | HE Bronto | 2% | 17% | 40% | 31% | 9% | 1% | |
| 29 | ZHU Yiming | 1% | 14% | 42% | 33% | 10% | 1% | |
| 30 | MEHROTRA Neel | - | - | 6% | 27% | 44% | 23% | |
| 31 | CAO Gavin | 7% | 28% | 38% | 22% | 5% | - | |
| 32 | PATHAK Arush | 28% | 43% | 23% | 5% | 1% | - | |
| 33 | MIDYANY Evan | - | - | 5% | 25% | 44% | 26% | |
| 34 | LIU Jeremiah W. | - | 1% | 11% | 32% | 41% | 15% | |
| 35 | SHCHUR Grayson | - | 2% | 14% | 36% | 38% | 9% | |
| 36 | WANG Eason | 8% | 28% | 36% | 21% | 6% | 1% | - |
| 37 | ZHANG Jonathan | 4% | 23% | 41% | 25% | 6% | - | |
| 38 | GU Eric | 7% | 28% | 39% | 21% | 4% | - | |
| 39 | ROBERTS Arthur | 11% | 34% | 36% | 16% | 3% | - | |
| 40 | CUELLAR Markus | 29% | 43% | 22% | 5% | - | - | |
| 41 | FOGEL Jake | 20% | 41% | 29% | 9% | 1% | - | |
| 42 | HELMY Richard | - | 1% | 9% | 28% | 40% | 20% | 3% |
| 43 | LEE Harrison | 1% | 9% | 30% | 38% | 18% | 3% | - |
| 44 | TSIEN Richard | 2% | 13% | 31% | 34% | 17% | 3% | - |
| 45 | NOOL Alexander | 5% | 20% | 33% | 28% | 12% | 3% | - |
| 46 | KIM Zac | 4% | 19% | 34% | 29% | 12% | 2% | - |
| 47 | PENG Ethan | - | 2% | 9% | 24% | 34% | 24% | 7% |
| 48 | NG Nico | 3% | 18% | 37% | 32% | 9% | 1% | |
| 49 | CHAN Ian | 68% | 29% | 3% | - | - | - | |
| 50 | HUANG Max | 12% | 50% | 31% | 7% | 1% | - | |
| 51 | ZHAI Junqi | 2% | 13% | 33% | 36% | 15% | 2% | |
| 52 | LIN ZIJIE | 11% | 35% | 36% | 15% | 3% | - | |
| 52 | MAXWELL Sheito | 17% | 41% | 31% | 9% | 1% | - | |
| 54 | FENG Xinmin | 34% | 46% | 17% | 3% | - | - | |
| 55 | SOLOMON Aryeh | 10% | 30% | 34% | 19% | 6% | 1% | - |
| 56 | ZHANG Marcus | 1% | 10% | 30% | 36% | 18% | 4% | - |
| 57 | VANDERMEER Joshua | 21% | 41% | 28% | 9% | 1% | - | - |
| 58 | GRIGORENKO Gleb E. | 8% | 30% | 37% | 20% | 5% | 1% | - |
| 58 | SI Anderson | 6% | 30% | 39% | 20% | 4% | - | - |
| 60 | ZHANG Shuhao | 45% | 40% | 13% | 2% | - | - | - |
| 61 | MA Owen | 4% | 27% | 45% | 21% | 3% | - | |
| 62 | HANNA Alexander | 26% | 47% | 22% | 4% | - | - | |
| 63 | SHI Yeyu | 21% | 41% | 29% | 9% | 1% | - | |
| 64 | LIU-XUE Shuliang | 28% | 42% | 23% | 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.