San Diego, CA - San Diego, 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 | FUKUDA Renzo K. | - | - | 1% | 10% | 29% | 40% | 20% |
| 2 | MUSHER Benjamin J. | - | - | - | 1% | 14% | 44% | 41% |
| 3 | YU Anders | - | - | - | 6% | 25% | 43% | 26% |
| 3 | JEON Caleb A. | - | - | 3% | 12% | 29% | 38% | 19% |
| 5 | STRUGAR Marcus A. | - | - | - | 4% | 18% | 42% | 37% |
| 6 | CHIRASHNYA Adam | - | - | 4% | 19% | 36% | 31% | 9% |
| 7 | COELHO Cristiano P. | - | - | - | 4% | 31% | 65% | |
| 8 | WOO Christian | 30% | 44% | 21% | 5% | - | - | - |
| 9 | BANERJEE ANUP | - | - | - | 1% | 8% | 35% | 55% |
| 10 | JAIN Aditya | - | - | - | 3% | 20% | 50% | 27% |
| 11 | TSAY Jeremy M. | - | - | 4% | 19% | 38% | 32% | 7% |
| 12 | LI Richard | - | - | - | 3% | 19% | 49% | 29% |
| 13 | LI Peihong | 1% | 6% | 22% | 36% | 27% | 8% | 1% |
| 14 | LAKE Wyatt J. | - | 2% | 13% | 33% | 34% | 15% | 2% |
| 15 | HOOSHI Jayden C. | - | - | 3% | 14% | 32% | 35% | 15% |
| 16 | GOBBO Alexander | - | - | 2% | 11% | 32% | 41% | 15% |
| 17 | YAKUSHKIN Ernest D. | - | - | - | 1% | 9% | 36% | 54% |
| 18 | BAO Aaron | - | 2% | 10% | 27% | 36% | 21% | 4% |
| 19 | CHIN Julian S. | - | - | - | 2% | 13% | 41% | 45% |
| 20 | PIESNER Zachary C. | - | 2% | 11% | 29% | 35% | 19% | 3% |
| 21 | PAI Lakshan K. | - | 1% | 6% | 23% | 39% | 27% | 5% |
| 22 | KANG Anthony Jaegu | - | 1% | 7% | 24% | 37% | 25% | 6% |
| 23 | GOOR Julian | - | - | 4% | 20% | 39% | 29% | 7% |
| 24 | NG Eben S. | - | - | 7% | 34% | 49% | 10% | |
| 25 | KHER Roan | - | 3% | 17% | 37% | 31% | 11% | 1% |
| 26 | MASCARI DUMONT Louis | - | 6% | 23% | 36% | 26% | 8% | 1% |
| 27 | HOSKERI Anik S. | 38% | 41% | 17% | 3% | < 1% | - | - |
| 28 | ZHOU Oscar J. | - | 3% | 16% | 34% | 32% | 13% | 2% |
| 29 | ZHANG Jiening G. | - | - | 4% | 17% | 35% | 33% | 11% |
| 30 | TAN Christien | 1% | 11% | 37% | 40% | 10% | 1% | - |
| 31 | WONG Antonio | 4% | 19% | 33% | 28% | 13% | 3% | - |
| 32 | CANLAS Nathan | - | 1% | 8% | 24% | 36% | 25% | 6% |
| 33 | LO Conrad | - | - | 2% | 14% | 47% | 31% | 6% |
| 34 | ZHAI Jeffrey | - | 1% | 9% | 29% | 40% | 19% | 3% |
| 35 | ANTON Nathaniel | - | - | 4% | 19% | 38% | 32% | 6% |
| 36 | LYNCH Owen C. | - | - | 2% | 12% | 29% | 37% | 19% |
| 37 | SHEN Owen | - | 3% | 16% | 34% | 32% | 13% | 2% |
| 38 | CHOU Jared T. | - | 1% | 7% | 23% | 36% | 26% | 7% |
| 39 | DETERING Julian | 1% | 11% | 32% | 36% | 17% | 3% | - |
| 40 | WANG Ethan | 1% | 9% | 28% | 36% | 20% | 5% | - |
| 41 | MA Andrew | 3% | 16% | 36% | 32% | 11% | 1% | - |
| 42 | SADOVSKY Leor B. | 2% | 12% | 27% | 32% | 20% | 6% | 1% |
| 43 | CHIRASHNYA Daniel | - | - | - | 3% | 18% | 44% | 34% |
| 44 | KIM Jackson | - | 1% | 7% | 21% | 34% | 28% | 9% |
| 45 | OH Joshua | 18% | 37% | 30% | 12% | 2% | - | - |
| 46 | LLOYD henry | 1% | 9% | 34% | 39% | 16% | 2% | |
| 47 | NGUYEN Liam | - | 1% | 6% | 21% | 36% | 28% | 7% |
| 48 | CORTRIGHT Joshua C. | - | 4% | 18% | 34% | 30% | 12% | 2% |
| 49 | FINNEY Lorenz | 3% | 15% | 31% | 31% | 16% | 4% | - |
| 50 | LEE Christopher T. | - | - | - | 4% | 24% | 51% | 21% |
| 51 | WU Lucas | - | - | 2% | 13% | 35% | 38% | 13% |
| 52 | DINSAY Kristjan | - | 5% | 20% | 36% | 28% | 9% | 1% |
| 53 | TAN Peter | 1% | 7% | 22% | 34% | 26% | 9% | 1% |
| 54 | KRYLTSOV Michael | 4% | 23% | 42% | 25% | 6% | 1% | - |
| 55 | BAUER Roman | - | 1% | 6% | 20% | 34% | 29% | 10% |
| 56 | CHEN Jaden K. | 3% | 18% | 34% | 29% | 13% | 3% | - |
| 57 | SOTO-ULEV Aden A. | - | 5% | 21% | 36% | 28% | 9% | 1% |
| 57 | LLIDO Soren | 27% | 42% | 24% | 6% | 1% | - | - |
| 59 | RENTERIA Emiliano | 2% | 14% | 35% | 33% | 14% | 3% | - |
| 60 | OROSZLAN Benjamin | - | 2% | 13% | 35% | 37% | 12% | 1% |
| 61 | TEH Ryan | 9% | 34% | 36% | 17% | 3% | - | - |
| 62 | RUBIN Max | 22% | 45% | 28% | 6% | - | - | |
| 63 | ZHOU Hao Kai (Kevin) | 17% | 47% | 28% | 7% | 1% | - | - |
| 63 | MA Bryant | 9% | 31% | 36% | 19% | 5% | 1% | - |
| 65 | WONG Matthew H. | 4% | 23% | 42% | 27% | 3% | - | |
| 66 | KIM Aiden | 21% | 43% | 28% | 8% | 1% | - | - |
| 67 | SUEDA Connor | 2% | 11% | 27% | 33% | 20% | 6% | 1% |
| 67 | NORIEGA Julian | 6% | 28% | 41% | 21% | 4% | - | - |
| 69 | KIM Harrison | - | 1% | 6% | 25% | 38% | 24% | 5% |
| 70 | CORTRIGHT Skipper (Matthew) | 1% | 8% | 30% | 38% | 19% | 4% | - |
| 71 | MAK Osman K. | 5% | 25% | 37% | 24% | 7% | 1% | - |
| 72 | ZUO Ethan | 17% | 38% | 31% | 11% | 2% | - | - |
| 73 | ZHONG Alan D. | 4% | 21% | 37% | 28% | 9% | 1% | - |
| 74 | SHAPHIR Liad | 5% | 22% | 36% | 27% | 9% | 1% | - |
| 75 | BAEK David | 1% | 10% | 31% | 36% | 18% | 4% | - |
| 76 | LI Jett | 28% | 45% | 22% | 4% | - | - | - |
| 77 | LO Preston | 1% | 6% | 25% | 38% | 24% | 6% | 1% |
| 78 | OH Jaden | 23% | 45% | 25% | 6% | 1% | - | - |
| 79 | CHEN Justin K. | 1% | 8% | 26% | 37% | 23% | 6% | - |
| 80 | CHENG Jonathan | - | 4% | 17% | 35% | 31% | 11% | 1% |
| 80 | MYERS Dean | 38% | 43% | 17% | 3% | - | - | - |
| 82 | ZHENG zhe | 42% | 42% | 15% | 2% | - | - | - |
| 82 | DE LA FUENTE Ian | 11% | 31% | 35% | 18% | 5% | - | - |
| 84 | TAN Peyton | 2% | 15% | 36% | 34% | 12% | 1% | - |
| 85 | ZENG Chuyi | 16% | 40% | 31% | 11% | 2% | - | - |
| 86 | NG Micah | 1% | 13% | 35% | 34% | 14% | 2% | - |
| 87 | FRCEK Armand A. | 12% | 34% | 34% | 16% | 4% | - | - |
| 88 | TUAN Evan | 12% | 35% | 35% | 15% | 3% | - | - |
| 89 | FRANC Geoffrey C. | 21% | 44% | 29% | 7% | - | - | - |
| 90 | MARTIN IV Elmer D. | 7% | 24% | 34% | 24% | 9% | 2% | - |
| 91 | FUKUDA Diego | 3% | 15% | 31% | 31% | 16% | 4% | - |
| 92 | SHPOLYANSKY Jax F. | 32% | 47% | 19% | 2% | - | - | |
| 93 | BHARADWAJ Venkatesh | 41% | 41% | 15% | 3% | - | - | - |
| 93 | AGRAWAL Niki | 29% | 47% | 22% | 3% | - | - | - |
| 95 | RAJ Jay | 26% | 41% | 25% | 7% | 1% | - | - |
| 96 | AGEYEV Aleksey | 14% | 48% | 31% | 7% | 1% | - | - |
| 97 | CHEN Tyler | 15% | 38% | 33% | 12% | 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.