Parsippany, NJ - Parsippany, NJ, 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 | MOSZCZYNSKI Adam | - | - | - | 5% | 25% | 47% | 23% |
| 2 | KIM Minwook | - | - | - | 5% | 22% | 45% | 28% |
| 3 | KIM Avery J. | - | 1% | 9% | 25% | 36% | 23% | 6% |
| 3 | BASALYGA Jeffrey | - | - | 2% | 11% | 30% | 39% | 18% |
| 5 | YAO Jonathan | - | 3% | 16% | 32% | 31% | 15% | 3% |
| 6 | TAKEMARU Leo | - | - | 1% | 9% | 27% | 40% | 22% |
| 7 | MORRILL Justin | - | 1% | 9% | 29% | 38% | 20% | 4% |
| 8 | MOSKOWITZ Mason C. | - | 4% | 17% | 32% | 30% | 14% | 2% |
| 9 | YEN Preston | - | 1% | 9% | 25% | 35% | 24% | 6% |
| 9 | CHAN Matthew | - | - | 3% | 17% | 38% | 33% | 10% |
| 11 | NG Jonathan H. | - | - | 3% | 16% | 35% | 34% | 12% |
| 12 | MORREALE John | - | 2% | 8% | 22% | 33% | 26% | 8% |
| 13 | WUN William | - | 1% | 9% | 29% | 38% | 20% | 4% |
| 14 | MURTHY Mukund | - | - | 1% | 7% | 26% | 42% | 23% |
| 15 | SUBBIAH Prashanth V. | - | - | 2% | 12% | 32% | 37% | 16% |
| 16 | STANLEY Hanno | - | 4% | 16% | 33% | 31% | 13% | 2% |
| 17 | CHO Brandon | 1% | 7% | 22% | 34% | 26% | 10% | 1% |
| 18 | LAU Jeremy Y. | - | 3% | 15% | 30% | 31% | 16% | 3% |
| 19 | LILOV Neil | - | - | 1% | 7% | 26% | 41% | 24% |
| 20 | GHOSH Tuhin | - | 2% | 10% | 27% | 35% | 21% | 4% |
| 21 | WIND Nicky E. | - | - | 2% | 12% | 34% | 38% | 14% |
| 22 | SZEWCZYK Thomas D. | - | 2% | 12% | 30% | 36% | 18% | 3% |
| 23 | CZYZEWSKI Konrad R. | - | - | 4% | 17% | 36% | 33% | 10% |
| 24 | LEVIN Mark A. | - | 1% | 7% | 22% | 34% | 27% | 8% |
| 25 | WALKER Robert Connor | 20% | 39% | 29% | 10% | 2% | - | - |
| 26 | BARTOLO Domenic V. | - | - | 1% | 11% | 32% | 39% | 16% |
| 27 | MORRILL William | - | 3% | 14% | 31% | 33% | 16% | 3% |
| 28 | LIN William | 3% | 18% | 34% | 30% | 13% | 3% | - |
| 29 | ZHOU Miles | 1% | 17% | 38% | 31% | 11% | 2% | - |
| 30 | LUO ZiRui | - | 6% | 24% | 37% | 24% | 7% | 1% |
| 31 | TANG Albert | 1% | 9% | 33% | 36% | 17% | 4% | - |
| 32 | WILSON Jude | - | 1% | 5% | 19% | 35% | 30% | 9% |
| 33 | CZAHA Balint | - | - | 5% | 22% | 38% | 28% | 7% |
| 34 | TSODIKOV Matthew G. | - | 1% | 10% | 30% | 37% | 19% | 3% |
| 35 | SO Hananiah | - | - | 1% | 7% | 27% | 44% | 22% |
| 36 | LASORSA Matthew | - | 1% | 12% | 34% | 36% | 15% | 2% |
| 37 | METTKE Nathaniel | 1% | 6% | 22% | 36% | 26% | 8% | 1% |
| 38 | CHAN Daniel | 1% | 10% | 29% | 34% | 20% | 6% | 1% |
| 39 | CHEN Henry H. | 13% | 40% | 33% | 12% | 2% | - | - |
| 40 | HUANG Ethan F. | 2% | 13% | 28% | 32% | 19% | 5% | 1% |
| 41 | LEDERER Justin W. | 1% | 13% | 33% | 34% | 16% | 3% | - |
| 42 | GANTA Vijay | 1% | 11% | 35% | 36% | 15% | 2% | - |
| 43 | HUANG Tyler T. | 3% | 14% | 29% | 31% | 18% | 5% | 1% |
| 44 | BOURGHOL Matthew | 16% | 38% | 32% | 12% | 2% | - | - |
| 45 | JUN Ryan | 15% | 43% | 33% | 8% | 1% | - | - |
| 46 | REDA Myles | 2% | 12% | 28% | 32% | 19% | 6% | 1% |
| 47 | XU Eric | 4% | 23% | 42% | 25% | 6% | 1% | - |
| 48 | FISK Ethan | 37% | 41% | 17% | 4% | - | - | - |
| 49 | PINKHASSIK Timothy M. | 4% | 26% | 42% | 23% | 5% | 1% | - |
| 50 | HAQ Kamran R. | 2% | 14% | 32% | 32% | 16% | 4% | - |
| 51 | GOLD Jackson | 3% | 17% | 32% | 30% | 15% | 4% | - |
| 52 | MARTINEZ Justin | 8% | 26% | 33% | 22% | 8% | 2% | - |
| 53 | ALTIRS Alexander | 48% | 42% | 9% | 1% | - | - | - |
| 54 | TREJO Oliver | 36% | 44% | 18% | 3% | - | - | - |
| 55 | WU Wilmund | 21% | 43% | 29% | 6% | 1% | - | - |
| 56 | EDELMAN Seth A. | 1% | 8% | 26% | 36% | 23% | 5% | - |
| 57 | COOK Aidan J. | 20% | 50% | 25% | 4% | - | - | - |
| 58 | VON TULGANBURG Cameron C. | 3% | 21% | 42% | 27% | 7% | 1% | - |
| 60 | SPRINGER Patrick | 19% | 42% | 30% | 8% | 1% | - | - |
| 61 | GEORGE Daniel | 22% | 43% | 28% | 7% | 1% | - | - |
| 62 | YAO Andy | 25% | 41% | 25% | 7% | 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.