New Haven, CT - New Haven, CT, 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 | JING Emily | - | - | - | - | 5% | 34% | 61% |
| 2 | PERLMAN Talia | - | - | 2% | 15% | 37% | 35% | 11% |
| 3 | DAVIA Daniella V. | - | - | - | - | 5% | 30% | 65% |
| 3 | XU Madison | - | - | 4% | 21% | 47% | 24% | 3% |
| 5 | SHAW Kayla M. | - | - | 1% | 8% | 29% | 41% | 20% |
| 6 | FERRETTI Anna Rebecca | - | - | - | 3% | 18% | 43% | 35% |
| 7 | COSTELLO Angeline S. | - | 1% | 4% | 17% | 34% | 32% | 12% |
| 8 | OUYANG Bridgette Z. | - | 2% | 12% | 32% | 37% | 17% | |
| 9 | DRANOVSKY Dasha | - | 2% | 11% | 31% | 39% | 18% | |
| 10 | ACHILOVA Feyza | - | - | 2% | 12% | 33% | 39% | 14% |
| 11 | CHEN Allison V. | - | 1% | 5% | 19% | 35% | 30% | 10% |
| 12 | ZHANG Alina C. | - | - | 3% | 15% | 36% | 35% | 11% |
| 13 | SHEN Lydia | - | - | 2% | 14% | 36% | 36% | 12% |
| 14 | CHO Rebecca H. | - | 1% | 6% | 21% | 35% | 28% | 9% |
| 15 | TAN Kaitlyn N. | - | - | - | 5% | 31% | 50% | 14% |
| 16 | WU Julianna Y. | 3% | 16% | 32% | 30% | 14% | 3% | - |
| 17 | DU Hannah | - | 1% | 7% | 24% | 39% | 25% | 5% |
| 18 | LI Meilin | - | - | 2% | 12% | 32% | 38% | 16% |
| 19 | WU Irene M. | - | - | 1% | 8% | 28% | 42% | 21% |
| 20 | WANG Chloe | 4% | 20% | 36% | 28% | 10% | 1% | |
| 21 | KOENIG Charlotte R. | - | - | - | 4% | 21% | 43% | 32% |
| 22 | PAHLAVI Dahlia | 1% | 8% | 27% | 37% | 22% | 6% | - |
| 23 | HOLLE Aviella S. | 1% | 7% | 25% | 37% | 24% | 6% | |
| 24 | CHEN Georgia M. | 2% | 15% | 35% | 33% | 13% | 2% | |
| 25 | BASSON Bayley D. | - | 3% | 16% | 36% | 32% | 12% | 1% |
| 26 | MUELLER Tatum J. | 2% | 17% | 35% | 31% | 13% | 2% | |
| 27 | BECCHINA Claire E. | 3% | 19% | 36% | 30% | 11% | 1% | |
| 28 | ORVANANOS Anice | - | 1% | 10% | 34% | 37% | 16% | 2% |
| 29 | EYER Hailey M. | - | 1% | 7% | 26% | 38% | 23% | 5% |
| 30 | LOGAN Jade | 1% | 20% | 48% | 26% | 6% | 1% | - |
| 31 | SLASKI Caroline O. | - | 11% | 32% | 36% | 17% | 3% | - |
| 32 | MCKEE Alexandra K. | 5% | 25% | 37% | 24% | 7% | 1% | |
| 33 | WONG Sophia M. | - | - | 4% | 19% | 39% | 32% | 5% |
| 34 | BHAN Zala | - | 4% | 21% | 38% | 28% | 8% | 1% |
| 35 | LI Rachel Y. | - | 1% | 10% | 30% | 40% | 19% | |
| 36 | LIU Sophia | 1% | 11% | 30% | 35% | 19% | 4% | - |
| 37 | JENKINS Hannah G. | 4% | 22% | 38% | 27% | 8% | 1% | - |
| 38 | MAESTRADO Ashley R. | 1% | 13% | 33% | 34% | 15% | 3% | - |
| 39 | OLIVEIRA Lavinia M. | 2% | 18% | 37% | 30% | 11% | 2% | - |
| 40 | WEINTRAUB Io H. | 1% | 6% | 22% | 36% | 27% | 8% | |
| 41 | FU Qihan | 3% | 17% | 33% | 30% | 13% | 3% | - |
| 42 | YANG Liu (Willow) | 8% | 30% | 39% | 20% | 3% | - | - |
| 43 | MI Anning | 4% | 26% | 39% | 24% | 6% | 1% | - |
| 44 | LENZ Zoe N. | 3% | 21% | 38% | 28% | 9% | 1% | - |
| 45 | CHARALEL Jessica | 2% | 46% | 40% | 10% | 1% | - | - |
| 46 | NICOU Melina | 5% | 24% | 40% | 26% | 5% | - | - |
| 47 | BROWN Cameryn | 2% | 28% | 41% | 22% | 5% | 1% | - |
| 48 | GINDE Maithili | 8% | 30% | 39% | 19% | 3% | - | - |
| 49 | MUSTO Isabella | 34% | 42% | 19% | 4% | - | - | |
| 50 | JANNACCIO morgan | 41% | 41% | 15% | 3% | - | - | |
| 51 | THIRUVENGADAM Harini | 51% | 37% | 10% | 1% | - | - | - |
| 52 | RASO Olivia | 5% | 22% | 35% | 26% | 10% | 2% | - |
| 53 | SU Michelle | - | 2% | 13% | 33% | 36% | 14% | 1% |
| 54 | HUNT Abigail S. | 20% | 38% | 29% | 11% | 2% | - | - |
| 55 | WALLACE Susannah | 3% | 18% | 36% | 30% | 11% | 2% | - |
| 55 | BAMFORD Anna | 28% | 42% | 23% | 6% | 1% | - | - |
| 57 | TAYLOR-CASAMAYOR Marisol | 11% | 36% | 35% | 15% | 3% | - | - |
| 58 | YU Hannah | 50% | 38% | 10% | 1% | - | - | - |
| 59 | PARK Caitlyn | 28% | 43% | 24% | 5% | - | - | - |
| 59 | YEUNG Cherry | 87% | 13% | 1% | - | - | - | - |
| 61 | CHEN Miley | 92% | 8% | - | - | - | - | - |
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.