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 | KIM Gene | - | - | - | - | 3% | 25% | 72% |
| 2 | WU Matthew | 1% | 7% | 22% | 34% | 26% | 10% | 1% |
| 3 | DODIN Daniel M. | - | - | - | 3% | 16% | 40% | 40% |
| 3 | FONG Kobe | - | - | 4% | 15% | 32% | 34% | 14% |
| 5 | VASILEV Victor | - | 4% | 15% | 31% | 32% | 15% | 3% |
| 6 | LUO Alexander | - | - | 1% | 5% | 20% | 41% | 34% |
| 7 | WHITE Jackson | 1% | 8% | 24% | 34% | 24% | 8% | 1% |
| 8 | MEDISETTI Arjun | 5% | 20% | 34% | 27% | 11% | 2% | - |
| 9 | KHERSONSKY Robert | 1% | 6% | 19% | 31% | 28% | 13% | 2% |
| 10 | ARMSTRONG Payson | - | - | 4% | 15% | 31% | 34% | 16% |
| 11 | LAI Jayden | - | 2% | 9% | 25% | 35% | 24% | 6% |
| 12 | FRIZZELL Kai | 1% | 5% | 20% | 34% | 28% | 11% | 1% |
| 13 | MADRIGAL SALVAT Guillermo | - | 2% | 11% | 27% | 34% | 21% | 5% |
| 14 | ZHOU Zhi Matthew | - | 3% | 18% | 36% | 32% | 10% | |
| 15 | CHEN Tianjun | 1% | 8% | 25% | 35% | 23% | 7% | 1% |
| 16 | DAI Jason | 1% | 7% | 21% | 32% | 27% | 11% | 2% |
| 17 | TANG Colin | - | 2% | 12% | 30% | 35% | 18% | 3% |
| 18 | DANILOV Artur | - | 5% | 22% | 37% | 28% | 8% | |
| 19 | MIDYANY Ryan | - | - | 1% | 5% | 19% | 41% | 34% |
| 20 | DANG William | - | 2% | 9% | 24% | 34% | 24% | 7% |
| 21 | MASKIN Mikhail | - | - | 5% | 24% | 43% | 25% | 3% |
| 22 | WU Jiachen | 3% | 16% | 31% | 30% | 15% | 4% | - |
| 23 | KIM Louie | 12% | 32% | 33% | 17% | 4% | 1% | - |
| 24 | ROBERTS Arthur | - | - | 3% | 14% | 32% | 36% | 15% |
| 25 | QU RuiTing | - | 3% | 13% | 29% | 33% | 18% | 3% |
| 26 | ZHENG Jason | - | 1% | 7% | 21% | 35% | 28% | 8% |
| 27 | ZHOU Luke | - | 6% | 24% | 37% | 26% | 7% | |
| 28 | PUTHOFF Henry | - | 3% | 13% | 30% | 34% | 18% | 3% |
| 29 | CHAU Ivan | 1% | 8% | 23% | 32% | 25% | 10% | 1% |
| 30 | SONG Aidan | - | 1% | 4% | 16% | 32% | 33% | 14% |
| 31 | CHEN Daniel | - | 4% | 16% | 32% | 32% | 14% | 2% |
| 32 | NOOL Aaron | 2% | 11% | 27% | 32% | 21% | 7% | 1% |
| 33 | HU Charles | - | 5% | 23% | 40% | 26% | 6% | - |
| 34 | ZINCHUK Yuri | 1% | 6% | 22% | 35% | 27% | 9% | 1% |
| 35 | LEE Harrison | - | - | 4% | 21% | 42% | 29% | 3% |
| 36 | BUTLER Xavier | 1% | 7% | 21% | 32% | 26% | 11% | 2% |
| 37 | SHAPIRO Samuel | - | 7% | 25% | 37% | 24% | 6% | |
| 38 | SHAO Mason | 1% | 8% | 23% | 33% | 24% | 9% | 1% |
| 39 | ZHOU Silvan | 4% | 19% | 33% | 29% | 13% | 3% | - |
| 39 | MA Joseph | 9% | 29% | 35% | 20% | 6% | 1% | - |
| 41 | SHI Peyton | 3% | 21% | 43% | 26% | 6% | 1% | - |
| 42 | HOO Bezalel | 1% | 14% | 33% | 33% | 16% | 3% | - |
| 43 | STRAFFORD Andrew | 13% | 34% | 33% | 16% | 4% | - | - |
| 44 | CHIANG William | 3% | 15% | 29% | 30% | 17% | 5% | 1% |
| 45 | LEE Leo | 1% | 6% | 19% | 32% | 28% | 12% | 2% |
| 45 | WANG Henry | 3% | 16% | 32% | 31% | 15% | 3% | - |
| 47 | CHEN Regis | 8% | 26% | 35% | 23% | 8% | 1% | - |
| 48 | CHEN Jayden A | 13% | 33% | 33% | 16% | 4% | 1% | - |
| 49 | ZHENG Jasper | 1% | 10% | 27% | 34% | 21% | 6% | 1% |
| 50 | WANG William | 19% | 37% | 29% | 12% | 3% | - | - |
| 51 | ZHANG Jacob | 60% | 33% | 6% | 1% | - | - | |
| 52 | LAI Jaxon | 4% | 22% | 38% | 27% | 9% | 1% | |
| 53 | ZHAO Ryan | 6% | 23% | 34% | 25% | 10% | 2% | - |
| 54 | YAO Irvine | 7% | 25% | 35% | 23% | 8% | 1% | - |
| 55 | CHEN Hayden | 1% | 7% | 22% | 34% | 27% | 10% | 1% |
| 56 | YOON Jonathan | 5% | 22% | 34% | 26% | 10% | 2% | - |
| 57 | ZHAO Brandon | 7% | 24% | 35% | 24% | 9% | 2% | - |
| 58 | MAXWELL Taiga | 14% | 36% | 33% | 14% | 3% | - | - |
| 59 | ECCLESTONE Liam | 22% | 44% | 27% | 7% | 1% | - | - |
| 60 | MAURAIS JP | 20% | 40% | 29% | 10% | 2% | - | - |
| 61 | JIN Noah | 28% | 43% | 23% | 6% | 1% | - | - |
| 62 | DALY Liam | 31% | 46% | 19% | 3% | - | - | - |
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.