Rockland Community College, Eugene Levy Field House - 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 | MULLER Inara | - | - | - | 1% | 10% | 38% | 51% |
| 2 | OSMINKINA-JONES Kai | - | - | - | - | 1% | 16% | 82% |
| 3 | NEMORIN Rei | - | - | - | - | 5% | 30% | 65% |
| 3 | DANIELS Jordanna | - | - | - | - | 5% | 30% | 65% |
| 5 | KABILING Anika Von Marie | - | - | - | 4% | 20% | 43% | 32% |
| 5 | LI Tira | - | - | 2% | 12% | 39% | 48% | |
| 7 | ILICHEVA Adriana | - | - | 1% | 9% | 27% | 41% | 21% |
| 8 | VARAH Alaia | - | - | 1% | 7% | 26% | 42% | 24% |
| 9 | ZHANG Nikki | - | - | 2% | 11% | 32% | 39% | 16% |
| 10 | JIANG Juliette | - | 1% | 5% | 20% | 38% | 31% | 5% |
| 11 | SOUTHWELL Mia | - | 1% | 5% | 21% | 40% | 29% | 4% |
| 12 | AN Jasmine | 1% | 12% | 33% | 36% | 16% | 2% | |
| 13 | CHEN Chloe | - | 1% | 5% | 19% | 36% | 31% | 9% |
| 14 | KONDE Anika | - | 4% | 19% | 36% | 30% | 10% | 1% |
| 15 | SARBU Esme | 3% | 15% | 31% | 32% | 16% | 4% | - |
| 16 | TSUI Amelia | 1% | 12% | 32% | 36% | 16% | 2% | |
| 17 | MENON Maya | - | - | 1% | 7% | 25% | 42% | 25% |
| 18 | POWERS Waverly | - | - | 2% | 12% | 31% | 38% | 16% |
| 19 | ONG Katherine | - | 3% | 16% | 35% | 33% | 12% | 1% |
| 20 | SCHWARTZ Delphine | 1% | 8% | 27% | 37% | 22% | 5% | - |
| 21 | TSIPORUKHA Arie | 1% | 6% | 23% | 39% | 27% | 5% | |
| 22 | XU Isabella | - | 2% | 12% | 32% | 35% | 16% | 3% |
| 23 | HENDERSON Lucie | 3% | 17% | 35% | 32% | 12% | 2% | - |
| 24 | CHANG Daisy Yijin | 1% | 6% | 22% | 36% | 27% | 9% | 1% |
| 25 | WU Jing | 1% | 6% | 23% | 36% | 26% | 8% | 1% |
| 26 | BHARDWAJ Sara | 24% | 43% | 25% | 6% | 1% | - | |
| 27 | ALPEROVICH Madeline | 3% | 18% | 36% | 30% | 12% | 2% | - |
| 28 | GU Allison | - | 2% | 12% | 33% | 37% | 16% | 1% |
| 29 | DAYNO Riley | 12% | 32% | 33% | 17% | 4% | 1% | - |
| 30 | YANG Jackie | - | 3% | 18% | 37% | 32% | 10% | - |
| 31 | SINGH Zara | 1% | 11% | 31% | 36% | 18% | 3% | - |
| 32 | BORROK Katherine | 17% | 45% | 30% | 8% | 1% | - | - |
| 33 | LIU Alyssa | - | - | 3% | 15% | 34% | 36% | 12% |
| 34 | GAO Anita | - | 3% | 16% | 35% | 32% | 13% | 2% |
| 35 | DEMATTEIS Katarina | 1% | 13% | 37% | 34% | 13% | 2% | - |
| 36 | RUBANOVA Aleksandra | 2% | 13% | 32% | 34% | 16% | 3% | - |
| 37 | BEAL Cameron | 1% | 6% | 20% | 33% | 28% | 11% | 2% |
| 38 | ZHANG Shihan | - | - | 5% | 22% | 40% | 28% | 5% |
| 39 | MADDISON Estelle | - | 1% | 10% | 30% | 38% | 18% | 2% |
| 40 | KONG Hermione | - | 1% | 7% | 26% | 40% | 23% | 4% |
| 40 | STERNBERG Ayleena | - | 5% | 21% | 37% | 27% | 8% | 1% |
| 42 | AVATAPALLI Sri Aadya | - | 1% | 7% | 23% | 36% | 26% | 7% |
| 43 | KIM Chloe | 2% | 16% | 35% | 32% | 13% | 2% | - |
| 44 | PRAKASH Lithika | 1% | 7% | 24% | 36% | 24% | 7% | 1% |
| 45 | TANG Julia | 16% | 40% | 32% | 10% | 1% | - | - |
| 46 | CHARUZA Tabetha | 4% | 20% | 35% | 28% | 11% | 2% | - |
| 47 | HAN Abigail | 23% | 42% | 27% | 7% | 1% | - | - |
| 47 | EDUSA Nayelli | 19% | 41% | 30% | 9% | 1% | - | |
| 49 | LEE Fiona | - | 14% | 36% | 34% | 14% | 3% | - |
| 50 | GAO Madeleine | 18% | 41% | 30% | 10% | 1% | - | - |
| 51 | BIVIJI Rania | 2% | 15% | 37% | 32% | 12% | 2% | - |
| 52 | EL-NAZER Salwa | 12% | 41% | 34% | 12% | 2% | - | - |
| 54 | NAIK Annika | 13% | 35% | 34% | 15% | 3% | - | - |
| 55 | BHALLA Emma | 39% | 43% | 15% | 2% | - | - | - |
| 55 | ZHANG Ellie | 3% | 18% | 36% | 30% | 11% | 2% | - |
| 55 | LONG Penelope | 30% | 43% | 22% | 5% | 1% | - | - |
| 55 | TU Chloe | 16% | 42% | 31% | 10% | 1% | - | - |
| 59 | JAIN Anika | 7% | 26% | 36% | 23% | 7% | 1% | - |
| 60 | HOANG Vienna | 50% | 39% | 10% | 1% | - | - | - |
| 60 | MADDISON Emily | 17% | 42% | 30% | 9% | 1% | - | - |
| 62 | LIU Vivienne | 42% | 40% | 15% | 3% | - | - | - |
| 63 | LEE Olive | 44% | 42% | 12% | 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.