ROCKLAND COMMUNITY COLLEGE - 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 | GAO Daniel | - | - | 2% | 14% | 40% | 44% | |
| 2 | PAN Tristan | - | 1% | 10% | 28% | 36% | 21% | 4% |
| 3 | AGAON Shawn | - | - | 1% | 7% | 38% | 54% | |
| 3 | KNOX James | - | - | 1% | 12% | 43% | 43% | |
| 5 | SUN Jason | - | - | 3% | 15% | 37% | 37% | 9% |
| 6 | DODIN David | - | - | 3% | 20% | 50% | 27% | |
| 7 | WU Jonathan | - | - | - | 2% | 16% | 45% | 36% |
| 8 | BRODSKY Julian | 1% | 12% | 37% | 37% | 12% | 1% | |
| 9 | KOBI Samuel | - | - | - | 1% | 8% | 35% | 56% |
| 10 | ZHANG Ethan | 1% | 7% | 27% | 40% | 22% | 4% | |
| 11 | SAVORETTI Francesco | - | - | 6% | 26% | 47% | 21% | |
| 12 | ZAYDMAN Ethan | 1% | 7% | 25% | 38% | 25% | 5% | |
| 13 | FENG Du | 2% | 14% | 39% | 36% | 9% | 1% | |
| 14 | THAKUR Om S. | - | - | 5% | 27% | 51% | 17% | |
| 15 | FLECKENSTEIN Benjamin T. | - | - | 4% | 21% | 44% | 30% | |
| 16 | MAO Benjamin | - | 2% | 9% | 26% | 37% | 22% | 4% |
| 17 | IARIKOV Nicholas | - | - | - | 1% | 9% | 38% | 52% |
| 18 | SUN Jeffery | 1% | 9% | 34% | 41% | 14% | 1% | |
| 19 | NAKAS Levent | - | 2% | 10% | 27% | 35% | 21% | 5% |
| 20 | SVERDLOV Seth | - | 1% | 11% | 31% | 38% | 17% | 2% |
| 21 | JIANG ryan | - | 1% | 9% | 26% | 36% | 22% | 5% |
| 22 | AGAON Ethan | - | 2% | 17% | 48% | 33% | ||
| 23 | SHCHUR Landon | - | 2% | 18% | 48% | 31% | ||
| 24 | MAHESH Tarun | - | - | 2% | 11% | 30% | 39% | 19% |
| 25 | ZOGRAFOS Nicholas | 51% | 40% | 9% | 1% | < 1% | - | - |
| 26 | BASOK Nikita | - | - | 1% | 8% | 29% | 43% | 19% |
| 27 | LAI Boden | 1% | 6% | 20% | 34% | 28% | 10% | 1% |
| 28 | ZHANG Zixian (Shawn) | 1% | 8% | 27% | 38% | 22% | 3% | |
| 29 | LEE Noah | - | - | 1% | 10% | 45% | 45% | |
| 30 | OTTO Nathaniel B. | 2% | 18% | 42% | 31% | 6% | - | |
| 31 | SAVORETTI Pietro | - | 4% | 19% | 40% | 29% | 7% | 1% |
| 32 | OKUN Benjamin | 10% | 35% | 37% | 15% | 2% | - | |
| 33 | ATKINS Levi H. | 1% | 11% | 28% | 34% | 20% | 5% | - |
| 34 | WANG zhixing (Daniel） | - | - | 6% | 27% | 45% | 22% | |
| 35 | POCHATKO Christian | 14% | 40% | 34% | 11% | 1% | - | |
| 36 | TANG Charles | 15% | 39% | 34% | 11% | 1% | - | |
| 37 | CZEPLA Andrew | 33% | 49% | 17% | 2% | - | ||
| 38 | DUSSEAU Maddax | - | 5% | 21% | 37% | 28% | 8% | 1% |
| 39 | ZOU Xianyang (Max) | - | 4% | 20% | 37% | 29% | 9% | 1% |
| 40 | CHEN Jun Ho | 3% | 21% | 47% | 25% | 4% | ||
| 41 | MEN Junda | 3% | 16% | 33% | 31% | 14% | 3% | - |
| 42 | KUGLER Luke | 8% | 31% | 37% | 19% | 4% | - | |
| 43 | CASASSOVICI Georges | 3% | 20% | 38% | 29% | 9% | 1% | |
| 44 | HU Robert J. | 2% | 19% | 44% | 29% | 6% | - | |
| 45 | ZENG Andrew | 1% | 7% | 29% | 38% | 21% | 4% | - |
| 46 | MCWILLIAMS Miles | 10% | 35% | 35% | 16% | 4% | - | - |
| 47 | KRAUSS Judah | 21% | 48% | 25% | 5% | 1% | - | - |
| 48 | FUSSMAN Yuval | 2% | 18% | 41% | 31% | 8% | 1% | |
| 49 | GLUSHKOV David | 60% | 34% | 6% | - | - | - | |
| 50 | REPIC Oliver | 35% | 42% | 19% | 4% | - | - | |
| 51 | SARIDAKIS Ioannis Thanos | 19% | 45% | 29% | 7% | - | - | |
| 52 | DOUBOV Andrew | 22% | 40% | 28% | 9% | 2% | - | - |
| 53 | RAFIQUE Faizan | 1% | 12% | 48% | 31% | 7% | 1% | - |
| 54 | JONELEIT Aidan | 3% | 16% | 34% | 31% | 13% | 3% | - |
| 55 | WELIWATTA kenula | 37% | 42% | 17% | 3% | - | - | - |
| 56 | SIRICO John | 37% | 44% | 16% | 2% | - | - | |
| 57 | ZHANG Roland | 34% | 48% | 16% | 2% | - | ||
| 58 | NILSEN Mark | 45% | 42% | 11% | 1% | - | - | |
| 59 | RITTERSHAUS Bryce | 22% | 43% | 27% | 7% | 1% | - | |
| 59 | SETO Jing | 11% | 43% | 36% | 10% | 1% | - | |
| 61 | GOON Tristan Yang | 6% | 25% | 36% | 24% | 8% | 1% | - |
| 62 | HIGGASON Hugh | 15% | 44% | 31% | 9% | 1% | - | - |
| 63 | PEDICONE Joseph | 36% | 43% | 17% | 3% | - | - | - |
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.