Secaucus, NJ - Secaucus, 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 | LI Yuhe | - | 1% | 11% | 31% | 36% | 18% | 3% |
| 2 | YIN Julia | - | - | - | - | 7% | 41% | 51% |
| 3 | XUAN Nicole J. | - | 1% | 5% | 24% | 43% | 27% | |
| 3 | RANDLEMAN Teresa | - | - | 3% | 14% | 36% | 37% | 10% |
| 5 | ZHU Serene M. | - | 2% | 15% | 37% | 36% | 11% | |
| 6 | GAJJALA Sharika R. | - | - | 2% | 12% | 32% | 38% | 16% |
| 7 | HAFEEZ Hiba | - | 1% | 11% | 34% | 40% | 14% | |
| 8 | HAFEEZ Hania | - | 2% | 12% | 31% | 35% | 17% | 3% |
| 9 | REID Anousheh | - | - | - | 4% | 18% | 42% | 36% |
| 10 | ZIGALO Elizabeth | - | 1% | 11% | 31% | 39% | 18% | |
| 11 | WU Celine | - | - | 3% | 17% | 37% | 33% | 9% |
| 11 | GUJJA Misha | - | - | 3% | 16% | 41% | 32% | 7% |
| 13 | YU Nicole J. | - | - | 3% | 17% | 42% | 38% | |
| 14 | YOU Emily | - | 6% | 23% | 39% | 27% | 5% | - |
| 15 | FURMAN Maria | - | 3% | 17% | 39% | 33% | 9% | |
| 16 | RAKHOVSKI Alexandra | - | - | 1% | 10% | 35% | 40% | 13% |
| 17 | YANG Alisa | 1% | 10% | 30% | 37% | 19% | 3% | |
| 18 | MUELLER Emma M. | - | 2% | 16% | 39% | 34% | 8% | |
| 19 | QI Jarynne Valerie | - | - | 4% | 22% | 44% | 29% | |
| 20 | XIAO Ruien | - | - | 1% | 5% | 22% | 42% | 30% |
| 21 | LEACH Meka A. | - | - | - | - | 6% | 36% | 58% |
| 21 | FAN Elizabeth | - | 2% | 11% | 28% | 36% | 19% | 3% |
| 23 | LI yu | - | 4% | 19% | 36% | 30% | 9% | 1% |
| 24 | AGAON Evelyn | 1% | 7% | 26% | 37% | 24% | 5% | |
| 25 | LEE Scarlett | - | 2% | 16% | 37% | 34% | 10% | |
| 26 | CHATIKHINE Anastasia | - | 4% | 20% | 39% | 30% | 8% | |
| 27 | LIU Nicole | 6% | 30% | 42% | 18% | 3% | - | |
| 28 | AZMEH nour | 3% | 22% | 39% | 27% | 8% | 1% | |
| 29 | SU Evelyn | 1% | 12% | 33% | 36% | 16% | 2% | |
| 30 | FAN Catherine | 16% | 38% | 32% | 12% | 2% | - | - |
| 31 | LIN Elaine | 4% | 24% | 41% | 24% | 6% | - | |
| 32 | KUMAR Eva | 15% | 40% | 33% | 10% | 1% | - | |
| 33 | WANG Esther | 1% | 9% | 29% | 38% | 20% | 4% | |
| 34 | ZHANG Laura | 1% | 11% | 31% | 37% | 17% | 2% | - |
| 35 | KOVALCHUK Erika S. | - | 2% | 12% | 35% | 39% | 12% | |
| 36 | YOU Isabel B. | - | 5% | 21% | 39% | 29% | 6% | - |
| 37 | LI Olivia | 8% | 27% | 35% | 22% | 7% | 1% | - |
| 38 | AI Amy | - | 3% | 16% | 34% | 32% | 12% | 2% |
| 39 | CHISHOLM Phoebe C. | 1% | 12% | 33% | 35% | 16% | 3% | - |
| 40 | CHEN Vivi | - | 2% | 9% | 26% | 35% | 23% | 5% |
| 41 | NIX Reagan | 14% | 39% | 33% | 12% | 2% | - | - |
| 42 | COSTA LEah | 2% | 11% | 28% | 35% | 21% | 5% | |
| 43 | LEE Claire | 30% | 44% | 21% | 4% | - | - | |
| 44 | SMUK Alexandra S. | 4% | 22% | 39% | 26% | 8% | 1% | - |
| 45 | CAFASSO Natalya | 1% | 11% | 30% | 34% | 19% | 5% | - |
| 46 | MEYER Rebecca | 2% | 16% | 39% | 31% | 10% | 1% | - |
| 47 | LIU Charlotte | 13% | 35% | 34% | 15% | 3% | - | - |
| 48 | JAKEL Alysa C. | 2% | 16% | 39% | 32% | 10% | 1% | |
| 49 | ZHOU Michelle | 26% | 44% | 24% | 5% | - | - | |
| 50 | SPRINGER Sierra | 25% | 41% | 26% | 7% | 1% | - | |
| 51 | LIU Baihan | 3% | 21% | 38% | 28% | 9% | 1% | |
| 52 | HOAGLAND Sally | 10% | 33% | 37% | 17% | 3% | - | - |
| 53 | NELSON Grace E. | 14% | 42% | 33% | 10% | 2% | - | - |
| 54 | DAGLI Saira Veronica | 2% | 11% | 29% | 34% | 19% | 4% | - |
| 55 | STOFFEL Halle | 6% | 24% | 35% | 25% | 9% | 1% | - |
| 56 | MEYER Rachel | 5% | 25% | 41% | 24% | 4% | - | |
| 57 | LI Runhan | 13% | 36% | 34% | 14% | 2% | - | |
| 58 | MISHIMA Audrey | 25% | 46% | 24% | 4% | - | - | |
| 59 | ALVES Arianna | 4% | 26% | 43% | 23% | 4% | - | - |
| 60 | ANIELLO Maisie | 4% | 23% | 38% | 26% | 8% | 1% | - |
| 61 | PAN Angela | 36% | 45% | 16% | 2% | - | - | - |
| 62 | NGUYEN Ashley L. | 46% | 41% | 11% | 1% | - | - | - |
| 62 | NEROSLAVSKY Katherine | 7% | 31% | 37% | 19% | 5% | 1% | - |
| 64 | PAI Remi | 10% | 32% | 36% | 18% | 3% | - | |
| 65 | FELGNER Bryn | 59% | 34% | 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.