Minneapolis, MN, 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 | KOTOV Leonid | 1% | 5% | 18% | 32% | 29% | 13% | 2% |
| 2 | WU Roger (Mengke) | - | - | 5% | 21% | 43% | 31% | |
| 3 | HOUTZ Jackson | - | 3% | 14% | 33% | 35% | 14% | |
| 3 | LIU kelly | - | - | 3% | 14% | 32% | 35% | 15% |
| 5 | GREENBAUM Maxwell H. | - | - | 1% | 6% | 21% | 41% | 31% |
| 6 | BERGER Oliver | - | 1% | 8% | 23% | 34% | 25% | 7% |
| 7 | YANG Ziyi | - | 1% | 4% | 15% | 32% | 34% | 15% |
| 8 | ESCUETA Tony V. | - | 3% | 14% | 32% | 35% | 15% | |
| 9 | MICHELL Bailey | - | 2% | 10% | 29% | 39% | 20% | |
| 10 | BABAYEV Gabriel A. | - | 1% | 6% | 20% | 34% | 29% | 9% |
| 11 | SHAHZAD Azlan A. | 7% | 26% | 36% | 23% | 7% | 1% | |
| 12 | CHEONG Heonjae | 4% | 19% | 34% | 29% | 12% | 2% | |
| 13 | YEN Preston | - | 4% | 16% | 34% | 33% | 12% | |
| 14 | KIM-COGAN Ryan | - | 3% | 13% | 28% | 32% | 19% | 5% |
| 15 | MARGULIES William | - | 3% | 14% | 29% | 32% | 17% | 4% |
| 16 | PAN Alex | 12% | 34% | 34% | 16% | 4% | - | |
| 17 | REYES Xavier M. | - | 1% | 8% | 24% | 34% | 25% | 7% |
| 18 | WOODWARD Dylan P. | 1% | 5% | 19% | 32% | 28% | 13% | 2% |
| 19 | WANG Eric Y. | - | 3% | 15% | 33% | 34% | 14% | |
| 20 | HONG Vincent Q. | - | 1% | 7% | 24% | 41% | 27% | |
| 21 | LINDHOLM Oliver S. | 2% | 11% | 30% | 35% | 19% | 4% | |
| 22 | LUO George F. | - | 2% | 14% | 34% | 37% | 14% | |
| 22 | NOBLE Colin | - | 4% | 17% | 34% | 32% | 12% | |
| 24 | PIWOWAR Alex | 13% | 33% | 33% | 16% | 4% | 1% | - |
| 25 | WOODWARD Connor | - | 3% | 12% | 27% | 33% | 20% | 5% |
| 25 | VOCHOSKA Aidan F. | - | 1% | 7% | 21% | 34% | 28% | 9% |
| 27 | GUAN Luke | 1% | 10% | 28% | 33% | 20% | 6% | 1% |
| 28 | RIGHTLER Samuel | 4% | 17% | 33% | 30% | 14% | 2% | |
| 29 | FENG Leo | - | 1% | 8% | 24% | 35% | 25% | 7% |
| 30 | KROON Lucas | 6% | 24% | 36% | 25% | 8% | 1% | |
| 31 | CHOI Silas | 1% | 8% | 24% | 35% | 25% | 7% | |
| 32 | PANDEY Neil | 4% | 17% | 32% | 29% | 14% | 3% | - |
| 33 | WONG Ryan | 1% | 7% | 25% | 37% | 25% | 5% | |
| 34 | XU Andrew | 1% | 6% | 20% | 32% | 28% | 12% | 2% |
| 35 | SCHERER Max | 1% | 10% | 25% | 33% | 22% | 7% | 1% |
| 36 | CHANG Colin S. | 1% | 7% | 21% | 33% | 27% | 10% | 1% |
| 37 | YUN Jake | - | 5% | 18% | 34% | 31% | 11% | |
| 38 | HONG Steven | 4% | 18% | 33% | 30% | 13% | 2% | |
| 39 | COLE Alexander | 1% | 11% | 31% | 36% | 18% | 3% | |
| 40 | FLOT Tai A. | - | 4% | 16% | 31% | 31% | 15% | 3% |
| 41 | EDELMAN Seth A. | 7% | 24% | 34% | 24% | 9% | 2% | - |
| 42 | POPE Nico | - | 1% | 8% | 27% | 41% | 23% | |
| 43 | MICLAUS Justin | 1% | 10% | 28% | 36% | 21% | 5% | |
| 44 | FALLICK Ozzie | - | 1% | 8% | 30% | 45% | 17% | |
| 45 | PI Alexander | 12% | 33% | 34% | 17% | 4% | - | |
| 45 | LIU Mingyang Ryan | 8% | 27% | 35% | 22% | 7% | 1% | |
| 47 | CAISSE Simon B. | 4% | 22% | 39% | 27% | 7% | 1% | |
| 48 | SHOMAN Noah | 1% | 8% | 25% | 36% | 24% | 6% | |
| 48 | LEITH Jack | 7% | 33% | 39% | 18% | 3% | - | |
| 50 | SHOMAN Zachary | 1% | 8% | 25% | 36% | 24% | 6% | |
| 51 | EICHHORN Lukas H. | 2% | 11% | 28% | 35% | 20% | 4% | |
| 52 | BAUER Hank E. | 2% | 13% | 29% | 31% | 18% | 5% | 1% |
| 53 | MURZYN III CJ | 2% | 13% | 29% | 31% | 18% | 5% | 1% |
| 54 | PRIMUS Nazir | 5% | 22% | 35% | 27% | 10% | 1% | |
| 55 | ZHOU Miles | 3% | 17% | 35% | 31% | 13% | 2% | |
| 56 | CHEN Evan P. | 1% | 9% | 26% | 35% | 23% | 6% | |
| 57 | MEDVEDEV Michail D. | 18% | 38% | 30% | 12% | 2% | - | |
| 58 | DOLAN Charles R. | 3% | 19% | 36% | 30% | 11% | 1% | |
| 59 | FREYRE DE ANDRADE Elian R. | - | 3% | 14% | 30% | 32% | 17% | 4% |
| 60 | DENG Andrew | - | 2% | 10% | 24% | 34% | 24% | 7% |
| 61 | LOPEZ Lucas M. | 16% | 36% | 31% | 14% | 3% | - | - |
| 61 | SINGH Angadh | 7% | 24% | 34% | 24% | 9% | 2% | - |
| 63 | CORTEZ Christopher | 4% | 19% | 33% | 29% | 13% | 3% | - |
| 64 | PATIL Aaryan A. | 1% | 12% | 31% | 35% | 17% | 3% | |
| 65 | COVINGTON Max G. | - | 3% | 13% | 28% | 32% | 18% | 4% |
| 66 | KIM Alexander M. | 1% | 6% | 20% | 33% | 28% | 11% | 2% |
| 67 | CHAUDHURI Eeshaan A. | 3% | 15% | 31% | 31% | 16% | 4% | - |
| 68 | MORALES Jonathan | 10% | 29% | 34% | 20% | 6% | 1% | - |
| 69 | RHEE Ethan N. | 2% | 15% | 34% | 33% | 14% | 2% | |
| 70 | ZHU Charlie | 4% | 21% | 37% | 28% | 8% | 1% | |
| 71 | GLOZMAN Justin | 13% | 34% | 33% | 16% | 4% | - | |
| 72 | HONG Rubin | 5% | 22% | 35% | 26% | 9% | 1% | |
| 73 | CHAVES Matthew J. | 4% | 20% | 35% | 28% | 11% | 2% | |
| 74 | BULL Anderson | 2% | 13% | 30% | 33% | 18% | 4% | |
| 75 | BEITEL Noah | 6% | 25% | 36% | 24% | 8% | 1% | |
| 76 | DELARUE NELSON Y. | 4% | 20% | 34% | 29% | 12% | 2% | |
| 77 | HOLMES Aiden G. | - | 3% | 13% | 29% | 33% | 18% | 3% |
| 78 | CHEONG Heonjun | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
| 79 | SCHARDINE James | 2% | 13% | 31% | 32% | 17% | 5% | - |
| 80 | RAMANAN Jaisimh | 29% | 41% | 23% | 6% | 1% | - | |
| 81 | SHANKAR Karthik | 38% | 41% | 17% | 3% | - | - | |
| 82 | HAN Daniel Y. | 1% | 11% | 29% | 35% | 20% | 4% | |
| 83 | GOLDIN Lucca | 18% | 40% | 30% | 10% | 1% | - | |
| 83 | KIM Matthew | 9% | 28% | 35% | 21% | 6% | 1% | |
| 85 | CHAN Aidan | 22% | 41% | 28% | 8% | 1% | - | |
| 86 | MCCARTHY Gabriel | 1% | 7% | 23% | 36% | 26% | 7% | |
| 87 | SOUTHWORTH Nathaniel | 12% | 31% | 33% | 18% | 5% | 1% | - |
| 88 | LIN Nick | 1% | 5% | 18% | 31% | 29% | 14% | 3% |
| 89 | FIELDS Matthew S. | 9% | 29% | 34% | 20% | 6% | 1% | - |
| 90 | HUANG Zekai | 9% | 28% | 35% | 21% | 7% | 1% | - |
| 91 | REN Richard | 6% | 22% | 34% | 26% | 10% | 2% | - |
| 92 | SHANAHAN Adam E. | 1% | 8% | 24% | 36% | 25% | 7% | |
| 93 | GRATHWOL-SEAR Oliver | 14% | 35% | 33% | 14% | 3% | - | |
| 94 | SHETTY VIVAN | 22% | 41% | 28% | 9% | 1% | - | |
| 95 | AN Damon | 12% | 32% | 33% | 17% | 5% | 1% | - |
| 96 | WILKINSON James | 53% | 36% | 10% | 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.