Pasadena Convention Center - Pasadena, CA, 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 | WONG Aaron | - | 2% | 14% | 39% | 35% | 10% | |
| 2 | DU Evan | - | - | 3% | 16% | 42% | 39% | |
| 3 | FU Nolan | - | 1% | 7% | 24% | 41% | 28% | |
| 3 | VOO Lucas | - | - | 1% | 5% | 20% | 41% | 34% |
| 5 | GUO Luke | - | 3% | 15% | 34% | 34% | 13% | |
| 6 | XUE Michael | - | - | 1% | 6% | 23% | 41% | 28% |
| 7 | RONG Gordon | - | - | 2% | 9% | 27% | 39% | 23% |
| 8 | RAHMAN Zayd | 2% | 13% | 33% | 35% | 15% | 2% | |
| 9 | MA Ryan | - | 1% | 10% | 32% | 40% | 17% | |
| 10 | ENG Kyler | 3% | 16% | 34% | 32% | 13% | 2% | |
| 11 | MAI Sy | 6% | 23% | 35% | 25% | 9% | 2% | - |
| 12 | OLIVAS Joseph | 1% | 9% | 24% | 33% | 23% | 8% | 1% |
| 13 | DODDAPANENI Aarav | - | - | 4% | 19% | 41% | 35% | |
| 14 | WONG Vansen | 2% | 11% | 27% | 33% | 21% | 7% | 1% |
| 15 | MENG Haoyi | 1% | 10% | 29% | 36% | 19% | 4% | |
| 16 | NORTON Henry | - | < 1% | 6% | 28% | 44% | 21% | |
| 17 | WHITE Ryden | - | 2% | 9% | 25% | 35% | 24% | 6% |
| 18 | DENG Destin | - | 4% | 17% | 31% | 31% | 14% | 2% |
| 19 | WANG Dylan | - | 4% | 26% | 41% | 24% | 5% | |
| 20 | NGUYEN Ethan V. | 7% | 25% | 36% | 24% | 7% | 1% | |
| 21 | KOU Mason | 7% | 31% | 42% | 17% | 3% | - | |
| 22 | MAXU Tiger | - | - | 5% | 26% | 45% | 24% | |
| 23 | ROBINSON Dax | 2% | 16% | 35% | 33% | 12% | 1% | |
| 24 | SUN Jiarui (Jerry) | 11% | 31% | 35% | 19% | 5% | - | |
| 25 | SCHWARTZMAN Ethan | - | 1% | 7% | 22% | 36% | 27% | 7% |
| 26 | RAHMAN Ali | 4% | 18% | 32% | 29% | 14% | 3% | - |
| 27 | TOUSSAINT Wizard | 5% | 21% | 34% | 26% | 11% | 2% | - |
| 28 | RONG Marcus | - | 2% | 18% | 39% | 32% | 9% | |
| 29 | WANG Lucas | 1% | 7% | 23% | 37% | 26% | 6% | |
| 30 | HAMILTON Travis | - | 5% | 20% | 36% | 30% | 9% | |
| 31 | LAU Caleb | 6% | 24% | 35% | 25% | 9% | 1% | - |
| 32 | HU Jingsen | 5% | 20% | 35% | 28% | 11% | 1% | |
| 33 | PARRA Lucas | 3% | 17% | 33% | 31% | 13% | 2% | |
| 34 | WOO Lucas | - | 2% | 10% | 27% | 36% | 21% | 4% |
| 35 | LEE Lucas | - | 2% | 10% | 26% | 34% | 22% | 6% |
| 36 | CHEONG Cameron | - | 2% | 9% | 24% | 35% | 24% | 6% |
| 37 | KIM Remington | - | 1% | 8% | 23% | 34% | 26% | 8% |
| 38 | SHOURIE Seth | 13% | 37% | 33% | 14% | 3% | - | |
| 39 | GADHVI Darius | - | 1% | 11% | 33% | 39% | 16% | |
| 40 | SARMIENTO Luke | - | 6% | 22% | 37% | 28% | 8% | |
| 41 | ONG David | 6% | 24% | 36% | 25% | 8% | 1% | |
| 42 | YU Haoyun | 4% | 18% | 34% | 29% | 13% | 2% | - |
| 43 | CHARETTE Alex | - | 4% | 18% | 37% | 33% | 9% | |
| 44 | BERTEL Florian | - | 2% | 9% | 24% | 34% | 24% | 7% |
| 45 | CHIEN Ian | 4% | 19% | 34% | 29% | 12% | 2% | - |
| 46 | SZETO Zachary | 15% | 43% | 33% | 8% | 1% | - | |
| 47 | YU Brandon | 11% | 32% | 35% | 18% | 4% | - | |
| 48 | ROLAND Nikolas | 11% | 57% | 27% | 5% | - | - | |
| 49 | AUYEUNG Aedan Ho lam | 9% | 34% | 37% | 17% | 3% | - | |
| 50 | TAMAYO-SARVER Daniel | 3% | 15% | 31% | 31% | 15% | 4% | - |
| 51 | KIM Leejay | 2% | 12% | 30% | 34% | 18% | 3% | |
| 52 | LIN Daniel | 1% | 5% | 19% | 33% | 29% | 12% | 2% |
| 53 | OR Anson | 5% | 20% | 33% | 28% | 12% | 3% | - |
| 54 | LIN Bryan | 3% | 17% | 33% | 30% | 14% | 3% | - |
| 55 | GE Austin | 36% | 42% | 18% | 4% | - | - | |
| 56 | NUGENT Curtis | 4% | 18% | 32% | 29% | 14% | 3% | - |
| 57 | LIU Yihong | 10% | 31% | 36% | 19% | 4% | - | |
| 57 | HUANG Eason | 38% | 44% | 16% | 2% | - | - | |
| 59 | BYUN Matthew | 29% | 42% | 23% | 6% | 1% | - | |
| 60 | YUN Nicholas | 25% | 40% | 25% | 8% | 1% | - | - |
| 61 | SHOURIE Neel | 10% | 29% | 34% | 20% | 6% | 1% | - |
| 64 | PARADKAR Akshay | 16% | 36% | 31% | 13% | 3% | - | - |
| 65 | NIE Shuobo | 13% | 32% | 33% | 17% | 4% | 1% | - |
| 66 | GOSS Aiden | 78% | 21% | 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.