Suffern, NY - Suffern, 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-COGAN Ryan | - | - | - | 3% | 18% | 42% | 36% |
| 2 | WILSON Jude | - | - | - | 1% | 10% | 39% | 49% |
| 3 | FLOT Tai A. | - | 1% | 6% | 22% | 36% | 27% | 7% |
| 3 | SKINNER Graham B. | - | - | - | 1% | 8% | 40% | 51% |
| 5 | WU Wilmund | - | 1% | 7% | 23% | 36% | 26% | 7% |
| 6 | LEE Justin | - | 2% | 15% | 36% | 35% | 11% | |
| 6 | DENG Andrew | - | 1% | 9% | 31% | 41% | 19% | |
| 8 | KUSHKOV Veniamin | - | - | 3% | 12% | 30% | 37% | 18% |
| 9 | NOBLE Colin | - | - | 3% | 14% | 34% | 37% | 12% |
| 10 | SHOMAN Zachary | - | - | 1% | 13% | 43% | 43% | |
| 11 | MAKLIN Edward P. | - | - | 4% | 18% | 36% | 32% | 10% |
| 12 | ZHENG Edward L. | - | 1% | 13% | 36% | 37% | 13% | |
| 13 | FIELDS Matthew S. | - | 4% | 16% | 32% | 31% | 14% | 3% |
| 14 | SPOSATO Andrew P. | 2% | 15% | 36% | 34% | 12% | 1% | |
| 15 | WAXLER Seth B. | - | - | 3% | 14% | 32% | 36% | 15% |
| 16 | MARGULIES William | 1% | 11% | 30% | 34% | 18% | 4% | - |
| 17 | ZHOU Miles | - | 1% | 6% | 21% | 35% | 29% | 8% |
| 18 | WONG Ryan | - | - | 4% | 17% | 34% | 33% | 12% |
| 19 | ZENG Noah | - | 1% | 6% | 22% | 38% | 28% | 5% |
| 20 | GINIS Nathan | - | - | - | 3% | 16% | 42% | 39% |
| 21 | SAVOY Luca | 1% | 7% | 23% | 36% | 25% | 7% | 1% |
| 22 | CHAUDHURI Eeshaan A. | 1% | 5% | 18% | 31% | 29% | 14% | 3% |
| 23 | SHTEYN Mark | - | 2% | 11% | 27% | 34% | 21% | 5% |
| 24 | NOURELDIN Gabriel | - | 1% | 6% | 21% | 37% | 28% | 7% |
| 25 | KILGALLEN William | - | 2% | 12% | 30% | 34% | 18% | 3% |
| 26 | EPSTEIN Oliver D. | 1% | 11% | 30% | 35% | 19% | 5% | - |
| 27 | OH Triton | - | 1% | 7% | 22% | 35% | 27% | 8% |
| 28 | BREKHMAN Eric | 1% | 9% | 26% | 35% | 22% | 6% | - |
| 29 | WEBER Mattias A. | - | 6% | 23% | 38% | 26% | 7% | - |
| 29 | LIU Mingyang Ryan | 7% | 31% | 38% | 19% | 5% | 1% | - |
| 31 | LEMPERT Adam | 3% | 21% | 36% | 28% | 11% | 2% | - |
| 32 | GILSON Lucas B. | - | 4% | 17% | 32% | 31% | 14% | 2% |
| 33 | CHANG Yufeng | 1% | 5% | 19% | 33% | 28% | 12% | 2% |
| 34 | CLYMER Lucas Y. | - | 2% | 11% | 27% | 34% | 21% | 5% |
| 34 | MYLEK Peter | - | - | 4% | 16% | 34% | 33% | 12% |
| 36 | KIM Shaun M. | - | - | - | 2% | 15% | 42% | 40% |
| 37 | PANDEY Neil | 1% | 9% | 27% | 35% | 22% | 6% | 1% |
| 38 | SHOMAN Noah | - | - | 2% | 11% | 30% | 39% | 18% |
| 39 | MEDVEDEV Michail D. | - | 1% | 8% | 41% | 38% | 11% | 1% |
| 40 | BAE Jason I. | - | - | 2% | 12% | 31% | 38% | 17% |
| 40 | ZHU Shao | 2% | 12% | 28% | 33% | 19% | 6% | 1% |
| 42 | RODE Leon J. | - | - | - | 4% | 25% | 51% | 20% |
| 43 | KOGAN Nikita | - | 2% | 9% | 24% | 34% | 25% | 7% |
| 44 | HUANG Alexander C. | - | 1% | 5% | 21% | 36% | 29% | 9% |
| 45 | LEONARD Charles | 1% | 6% | 21% | 35% | 27% | 9% | 1% |
| 46 | KOVACH Jonah F. | - | 5% | 23% | 38% | 27% | 7% | |
| 47 | GOLDMAN Noah R. | - | 7% | 34% | 39% | 17% | 3% | |
| 48 | DOWNEY Baran | 2% | 14% | 32% | 33% | 16% | 3% | - |
| 49 | SANDERS Samuel B. | - | 2% | 15% | 35% | 34% | 13% | 1% |
| 50 | OVERDECK Andrew | - | 4% | 18% | 35% | 30% | 11% | 2% |
| 51 | SHIPITSIN Alexander | - | 1% | 8% | 23% | 35% | 26% | 7% |
| 52 | ZHANG Yankun | 21% | 46% | 27% | 6% | 1% | - | - |
| 53 | TANG Charles | 9% | 30% | 36% | 20% | 5% | 1% | - |
| 54 | SHTEIN Yan | - | 2% | 10% | 27% | 35% | 21% | 5% |
| 55 | OKEEFE Mitchell | - | 4% | 18% | 38% | 32% | 8% | - |
| 56 | POSY Daniel | 19% | 41% | 29% | 9% | 1% | - | - |
| 57 | WU Hunter | - | 6% | 24% | 36% | 25% | 8% | 1% |
| 58 | RUIGOMEZ Eduardo | 6% | 24% | 36% | 24% | 8% | 1% | - |
| 59 | GONG Jerry | 13% | 34% | 34% | 15% | 3% | - | - |
| 60 | MORALES Jonathan | 3% | 20% | 40% | 29% | 7% | 1% | |
| 61 | BRIDGES Benjamin | - | 3% | 16% | 36% | 33% | 11% | 1% |
| 62 | LUCAS Hayden | 1% | 7% | 25% | 37% | 24% | 6% | - |
| 63 | LAU Justin Y. | - | 4% | 17% | 35% | 31% | 11% | 1% |
| 64 | ZHENG Joshua | 44% | 40% | 14% | 2% | - | - | - |
| 65 | MOULTON Ian | 10% | 36% | 36% | 15% | 3% | - | - |
| 66 | CHENG Cody | - | 4% | 15% | 29% | 31% | 17% | 4% |
| 67 | VOSS Jeffer | 8% | 30% | 36% | 20% | 5% | 1% | - |
| 68 | MAZURENKO Alexander | 1% | 6% | 22% | 34% | 26% | 10% | 1% |
| 69 | MALONE Gregory D. | - | 1% | 6% | 24% | 40% | 26% | 4% |
| 70 | KULKARNI Rohan | 7% | 30% | 42% | 19% | 2% | - | - |
| 71 | DEPEW Spencer | 2% | 14% | 30% | 32% | 17% | 4% | - |
| 72 | TIAGI Daniel | 1% | 10% | 26% | 33% | 22% | 7% | 1% |
| 73 | CHENG Hong | 56% | 36% | 7% | 1% | - | - | |
| 74 | ALI Rahman | 25% | 46% | 24% | 5% | - | - | |
| 75 | HUANG Connor | 1% | 6% | 22% | 35% | 26% | 9% | 1% |
| 76 | SHI Erick | 11% | 32% | 35% | 18% | 4% | - | - |
| 77 | WASSERMAN Aiden | - | 3% | 13% | 29% | 33% | 19% | 4% |
| 78 | HOFFMAN Pasquale | 17% | 43% | 32% | 8% | 1% | - | - |
| 79 | DE JESUS Jarvin | 6% | 31% | 37% | 20% | 5% | 1% | - |
| 80 | KASPER Aaron | 15% | 36% | 32% | 14% | 3% | - | - |
| 81 | PARKER Benjamin D. | 5% | 25% | 39% | 24% | 7% | 1% | - |
| 81 | KNUDSEN Matthew S. | 4% | 18% | 32% | 28% | 14% | 4% | - |
| 83 | CHUANG Tristan | 1% | 9% | 28% | 35% | 21% | 6% | 1% |
| 84 | CAMPO Alexander P. | 34% | 44% | 18% | 3% | - | - | - |
| 84 | PERRON Robert | 20% | 37% | 28% | 12% | 3% | - | - |
| 86 | PILAT Matthew J. | 11% | 35% | 35% | 16% | 3% | - | - |
| 87 | CHANG Yuyang | 35% | 42% | 19% | 4% | - | - | - |
| 88 | MCCUE Henry | 8% | 38% | 38% | 14% | 2% | - | - |
| 89 | JOYCE cameron | 12% | 33% | 35% | 17% | 3% | - | |
| 90 | GAJDA Jesse | 35% | 42% | 19% | 4% | - | - | - |
| 91 | DALTON Timothy | 10% | 40% | 40% | 9% | 1% | - | |
| 92 | LIU ALAN | 37% | 46% | 16% | 1% | - | - | - |
| 93 | TIAGI George | 11% | 34% | 35% | 16% | 4% | - | - |
| 93 | CSERY Lajos | 15% | 35% | 32% | 15% | 4% | - | - |
| 93 | SWERDLOFF Eli | 49% | 37% | 12% | 2% | - | - | - |
| 96 | DONALDSON Christopher | 8% | 37% | 38% | 14% | 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.