SportsPlex at Metuchen - Metuchen, 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 | FALLON Kyle R. | - | - | - | - | - | 11% | 88% |
| 2 | RAKHOVSKI Alexandra | - | - | - | 4% | 27% | 68% | |
| 3 | SMOTRITSKY Mia | - | - | - | - | 4% | 29% | 67% |
| 3 | CHEN Lefu | - | - | - | - | 4% | 29% | 66% |
| 5 | PRESMAN Aerin | - | 5% | 25% | 41% | 24% | 5% | |
| 6 | LEE Claire | - | - | 1% | 8% | 31% | 49% | 11% |
| 7 | ELKHATEEB Fajr | - | 1% | 14% | 37% | 35% | 11% | 1% |
| 8 | MONOVA Lilyana | 1% | 8% | 28% | 38% | 20% | 4% | |
| 9 | GU Sarah | - | - | - | - | 1% | 13% | 87% |
| 10 | SUICO Kyubi Emmanuelle | - | 5% | 26% | 40% | 23% | 5% | - |
| 11 | MISHIMA Audrey | - | 3% | 15% | 35% | 35% | 11% | - |
| 12 | WATTANAKIT Anda | - | - | 5% | 24% | 45% | 26% | |
| 13 | PROFIS Liora | - | 1% | 10% | 31% | 40% | 17% | |
| 14 | FURMAN Maria | - | - | 1% | 10% | 36% | 49% | 5% |
| 15 | SHANKERDAS Shreeya | 5% | 22% | 37% | 27% | 8% | 1% | |
| 16 | YOU Isabel B. | 1% | 11% | 38% | 37% | 13% | 1% | |
| 17 | LIN Elaine | - | - | 1% | 7% | 42% | 50% | |
| 18 | PAN Angela | - | 6% | 26% | 40% | 23% | 4% | - |
| 19 | RANDLEMAN Teresa | - | - | 1% | 13% | 42% | 44% | |
| 20 | SMOTRITSKY Liat | - | 7% | 30% | 41% | 19% | 3% | |
| 21 | NOVOJILOV Anastasia | - | 4% | 19% | 36% | 30% | 9% | 1% |
| 22 | BASRALIAN Azniv | - | - | 4% | 19% | 41% | 34% | 2% |
| 23 | LIN Victoria T. | 1% | 6% | 24% | 39% | 26% | 5% | - |
| 24 | PRIHODKO Nina | - | - | 5% | 26% | 45% | 23% | |
| 25 | DEPOMMIER Isabelle | - | 1% | 11% | 34% | 41% | 13% | |
| 26 | SHU Youshan | - | 1% | 6% | 25% | 43% | 25% | |
| 27 | BAWA Jenya | 9% | 34% | 37% | 16% | 3% | - | |
| 28 | GUJJA Misha | - | - | - | 4% | 23% | 46% | 27% |
| 29 | BRUNSON Nile | - | - | 4% | 17% | 38% | 35% | 6% |
| 30 | KAUR Manroop | 5% | 23% | 37% | 26% | 8% | - | |
| 31 | REKEDA Anna | 2% | 18% | 38% | 31% | 10% | 1% | |
| 32 | GOODSON Tia | 19% | 51% | 25% | 4% | - | - | |
| 33 | FENG Ge | - | - | - | 3% | 19% | 46% | 31% |
| 34 | CHANG Chloe | 2% | 16% | 39% | 35% | 7% | - | |
| 35 | GANSER Nicole | 1% | 11% | 36% | 37% | 13% | 1% | |
| 36 | ZHU Serene M. | - | - | 2% | 18% | 53% | 26% | |
| 37 | SEREGIN Katya | 1% | 10% | 29% | 36% | 20% | 4% | - |
| 38 | UNGURIANU Nika | 1% | 7% | 25% | 39% | 24% | 4% | - |
| 39 | YANG Charlotte | 1% | 9% | 31% | 38% | 18% | 3% | - |
| 40 | FANG Kayla | 3% | 16% | 35% | 32% | 12% | 2% | - |
| 41 | MEYER Rebecca | 18% | 39% | 31% | 11% | 2% | - | - |
| 42 | CASHMAN Amanda | 15% | 36% | 33% | 13% | 2% | - | |
| 43 | MARTINEZ Cecilia | 16% | 40% | 33% | 10% | 1% | - | |
| 44 | SHAKIR Inaaya | 1% | 11% | 30% | 37% | 19% | 2% | |
| 45 | HE Lizbeth | 46% | 40% | 12% | 2% | - | - | |
| 46 | WEI Sherry | - | 6% | 24% | 39% | 26% | 5% | - |
| 47 | COLELLA Lauren | - | 3% | 24% | 41% | 25% | 6% | - |
| 48 | WANG Selina | 5% | 25% | 38% | 25% | 7% | 1% | - |
| 49 | MOYSTON Elizabeth | 2% | 15% | 34% | 32% | 14% | 2% | - |
| 50 | GEFFNER Olivia | 21% | 55% | 21% | 3% | - | - | - |
| 51 | MILLER Cassandra | 40% | 42% | 16% | 3% | - | - | - |
| 52 | LIN Cynthia | 27% | 45% | 22% | 5% | - | - | - |
| 53 | REISNER Gabriella | 34% | 47% | 17% | 2% | - | - | |
| 54 | PHELAN Gabrielle | 52% | 39% | 8% | 1% | - | - | |
| 55 | HOM Justina | 14% | 38% | 35% | 12% | 1% | - | |
| 56 | SAYAGUES Isabella | 7% | 26% | 37% | 23% | 6% | - | |
| 57 | WANG Sophie Y. | 4% | 21% | 37% | 28% | 9% | 1% | - |
| 58 | KRAJA Emma | 5% | 25% | 39% | 25% | 6% | - | - |
| 59 | HOAGLAND Sally | 6% | 29% | 39% | 21% | 5% | - | - |
| 60 | RITTER Brooklyn | 20% | 41% | 29% | 9% | 1% | - | - |
| 61 | WROBEL Julia | 28% | 46% | 22% | 4% | - | - | - |
| 62 | SANLIKOL Suzan | 16% | 40% | 33% | 10% | 1% | - | |
| 63 | SATO Elyse | 32% | 42% | 21% | 5% | - | - | - |
| 64 | LEEB Zoe | 29% | 48% | 20% | 3% | - | - | |
| 65 | SILVERMAN Sarah | 57% | 37% | 6% | - | - | - | - |
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.