King of Prussia, PA - King of Prussia, PA, 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 | ||
| 1 | YUROVCHAK Andrew T. | - | 2% | 16% | 45% | 37% | |
| 2 | IVAKIMOV Vasil | - | 2% | 16% | 42% | 40% | |
| 3 | GOHEL Dayus T. | - | 3% | 15% | 34% | 36% | 13% |
| 3 | TUCKER Owen J. | - | 7% | 28% | 39% | 22% | 4% |
| 5 | SMITH Nicholas S. | - | 4% | 26% | 48% | 22% | |
| 6 | JIN Alexander | - | 1% | 7% | 24% | 42% | 27% |
| 7 | KUMAR Anitya | - | 2% | 13% | 32% | 37% | 16% |
| 8 | LOYOLA TORRIENTE Padick | 1% | 8% | 27% | 37% | 23% | 5% |
| 9 | WU Joseph | - | 4% | 19% | 36% | 31% | 10% |
| 10 | MCCOMISKEY Aiden J. | 1% | 13% | 36% | 37% | 13% | |
| 11 | BHATNAGAR Ayan | 2% | 19% | 41% | 31% | 7% | |
| 12 | NOVOJILOV Alexei | 1% | 26% | 41% | 24% | 6% | 1% |
| 13 | FELDMAN Jaemin | - | 5% | 21% | 38% | 28% | 7% |
| 13 | GAO Daniel | 5% | 22% | 37% | 27% | 9% | 1% |
| 15 | SIVAKUMAR Ajit | - | 3% | 16% | 35% | 35% | 11% |
| 16 | JIN Owen | - | 2% | 13% | 32% | 37% | 15% |
| 17 | PARK Ian C. | - | 2% | 13% | 32% | 37% | 16% |
| 18 | MORSE Tyler | - | 2% | 12% | 32% | 39% | 16% |
| 19 | AGAON Ethan | 4% | 23% | 38% | 26% | 8% | 1% |
| 20 | PARK Brian | - | 4% | 21% | 40% | 29% | 7% |
| 21 | SUICO Zachary Emanuel O. | - | - | 5% | 23% | 43% | 29% |
| 22 | GANA Jr Jorge M. | - | 1% | 6% | 22% | 42% | 29% |
| 23 | DOLMETSCH Max | - | - | 5% | 23% | 43% | 29% |
| 24 | SHEN Max | 10% | 35% | 37% | 16% | 2% | |
| 25 | SIMPSON Patrick | 5% | 26% | 41% | 24% | 4% | |
| 26 | SHIV Rishi | - | 2% | 14% | 37% | 36% | 11% |
| 27 | KIM Byung | 3% | 17% | 35% | 31% | 12% | 2% |
| 28 | SJOSTEDT Jacob H. | - | 2% | 14% | 42% | 42% | |
| 29 | KROPP Jack | - | 6% | 25% | 43% | 26% | |
| 30 | SINGH Aryaman | 34% | 42% | 19% | 4% | - | - |
| 31 | LI Jalen | 42% | 44% | 12% | 1% | - | |
| 32 | MARRAN Erik R. | 2% | 19% | 45% | 28% | 5% | |
| 33 | SITBON-TAYLOR Noe B. | - | 1% | 7% | 26% | 42% | 24% |
| 34 | CHATZIKALFAS Dimitris E. | 8% | 29% | 37% | 20% | 5% | - |
| 35 | PARK Frederick | 7% | 34% | 40% | 17% | 2% | |
| 36 | LEHR William D. | 2% | 14% | 37% | 36% | 10% | |
| 37 | RHYU Kozmo | - | 1% | 8% | 27% | 41% | 23% |
| 38 | KOKENGE Reid | 2% | 17% | 35% | 32% | 12% | 2% |
| 39 | DIXON Thomas | 4% | 21% | 36% | 28% | 10% | 1% |
| 40 | MACARTY Jordan T. | 2% | 14% | 33% | 33% | 15% | 2% |
| 41 | AGAON Shawn | - | 9% | 31% | 38% | 19% | 3% |
| 42 | MISHIMA Torata | 3% | 16% | 33% | 32% | 14% | 2% |
| 43 | PAHLAVI Kamran | 23% | 48% | 24% | 4% | - | |
| 44 | CHOI Mason | 3% | 20% | 41% | 30% | 6% | |
| 45 | POZOVSKIY Mitchell R. | 1% | 10% | 35% | 37% | 15% | 2% |
| 46 | JEYOON Ryan S. | - | 3% | 19% | 38% | 31% | 8% |
| 47 | CHEN Eric | 1% | 10% | 29% | 36% | 20% | 4% |
| 48 | MAGDA Daniel | 4% | 20% | 37% | 28% | 10% | 1% |
| 49 | ZHAO corey | 2% | 14% | 34% | 34% | 14% | 2% |
| 50 | STALL-RYAN Jonathan | 27% | 41% | 24% | 7% | 1% | - |
| 51 | DISIMONE David Z. | 3% | 17% | 36% | 31% | 12% | 2% |
| 51 | CHOE Andrew | 23% | 40% | 27% | 9% | 1% | - |
| 53 | WU Jonathan | 9% | 45% | 35% | 10% | 1% | - |
| 54 | PRIHODKO Max | 4% | 22% | 40% | 28% | 6% | |
| 55 | ZHAO Luhan | 19% | 42% | 30% | 8% | 1% | |
| 56 | MARTINEZ Joshua | 36% | 43% | 18% | 3% | - | |
| 57 | KUMAR Aidan | 24% | 43% | 26% | 6% | - | |
| 58 | BINDAS Odinn A. | 5% | 24% | 37% | 25% | 8% | 1% |
| 59 | WHITEHURST JJ | 4% | 21% | 37% | 28% | 9% | 1% |
| 59 | LI Jeffrey | 5% | 23% | 37% | 26% | 8% | 1% |
| 61 | LEE Seungwon | 4% | 24% | 38% | 25% | 8% | 1% |
| 62 | MCCRACKEN Dylan | 43% | 40% | 14% | 3% | - | - |
| 63 | LAI Coby | 3% | 17% | 35% | 32% | 13% | 2% |
| 64 | ZHANG William | 50% | 39% | 10% | 1% | - | |
| 65 | HU Robert J. | 66% | 29% | 4% | - | - | - |
| 66 | GONG Haixiang | 40% | 41% | 16% | 3% | - | - |
| 67 | MAHESH Tarun | 40% | 41% | 16% | 3% | - | - |
| 68 | FENG du | 90% | 9% | - | - | - | - |
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.