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 | HU Alicia | - | - | - | 4% | 21% | 44% | 30% |
| 2 | XU Elaine | - | - | - | 3% | 18% | 45% | 33% |
| 3 | ZHENG Winona | - | 1% | 12% | 34% | 38% | 15% | |
| 3 | ZHAO Selena | - | - | - | 4% | 18% | 42% | 36% |
| 5 | FOSS Persephone | - | - | - | 4% | 22% | 47% | 26% |
| 6 | LIU Chelsea | - | - | 3% | 13% | 31% | 36% | 16% |
| 7 | SUN Yi | - | - | - | 5% | 25% | 45% | 25% |
| 8 | LEE Kaitlin | - | - | 1% | 9% | 30% | 43% | 18% |
| 9 | CHOWDHERY Myra | - | - | 1% | 6% | 22% | 41% | 30% |
| 10 | PARK Gabriella | - | 3% | 14% | 29% | 32% | 17% | 3% |
| 11 | KIM Grace | - | - | 4% | 16% | 33% | 34% | 13% |
| 12 | PARK Haylie | - | - | 1% | 7% | 27% | 43% | 22% |
| 13 | CAFAGNA Sofia | - | 3% | 14% | 30% | 33% | 17% | 3% |
| 14 | LEE Grace | - | 2% | 9% | 25% | 35% | 23% | 6% |
| 15 | WEI Madison | - | 1% | 9% | 29% | 37% | 20% | 4% |
| 16 | ZHANG Audrey | 1% | 6% | 20% | 33% | 28% | 11% | 2% |
| 17 | WANG MONA | - | - | 4% | 15% | 32% | 35% | 14% |
| 18 | ZHANG Nikki | - | 5% | 22% | 39% | 26% | 7% | 1% |
| 19 | HILD Anya | - | 2% | 16% | 37% | 34% | 11% | |
| 20 | BANDHU Saahiti | - | 2% | 15% | 37% | 35% | 11% | |
| 21 | DANIELS Jordanna | - | 2% | 10% | 26% | 35% | 22% | 5% |
| 22 | CONVERSO-PARSONS Maia | 1% | 7% | 25% | 37% | 24% | 5% | - |
| 23 | MUNSHI Ridhima | 1% | 6% | 21% | 33% | 27% | 10% | 2% |
| 24 | DATLA Aanya | 10% | 30% | 33% | 19% | 6% | 1% | - |
| 25 | CANARAN Daphne M. | 2% | 15% | 32% | 31% | 16% | 4% | - |
| 26 | WANG Chloe | 1% | 7% | 23% | 34% | 25% | 9% | 1% |
| 27 | VARAH Alaia | - | 6% | 27% | 39% | 23% | 5% | |
| 28 | JUN Sofia | 1% | 9% | 24% | 33% | 24% | 8% | 1% |
| 29 | MISHRA Riona | 4% | 18% | 33% | 29% | 13% | 3% | - |
| 30 | BREWSTER Ayaki | 1% | 6% | 23% | 37% | 26% | 7% | 1% |
| 31 | WILLER Anna | 1% | 8% | 24% | 34% | 24% | 8% | 1% |
| 32 | MADDISON Erica | 42% | 40% | 15% | 3% | - | - | - |
| 33 | LIU Teresa | 1% | 8% | 26% | 36% | 23% | 7% | 1% |
| 34 | PATEL Maia | - | - | 3% | 12% | 29% | 37% | 20% |
| 35 | KABILING Anika Von Marie | - | 6% | 22% | 36% | 27% | 8% | 1% |
| 36 | CHEN Chloe | 2% | 14% | 30% | 32% | 17% | 4% | - |
| 37 | GOEL Lineysha | - | - | 4% | 17% | 36% | 34% | 9% |
| 38 | FENG chloe | 4% | 18% | 33% | 29% | 13% | 3% | - |
| 39 | AN Jasmine | 3% | 17% | 38% | 30% | 10% | 1% | - |
| 40 | PARAISO Isabella | 20% | 44% | 28% | 7% | 1% | - | - |
| 41 | LEE Jiyoung | 6% | 23% | 34% | 25% | 10% | 2% | - |
| 42 | AN Jamie | 6% | 24% | 35% | 25% | 9% | 1% | - |
| 43 | LIAO Audrey | 18% | 49% | 27% | 6% | 1% | - | |
| 44 | WEI Avril | 1% | 9% | 25% | 33% | 23% | 8% | 1% |
| 45 | JUNG Elise | - | 2% | 14% | 33% | 35% | 14% | 2% |
| 46 | ENG Gabrielle | 1% | 9% | 28% | 35% | 21% | 5% | - |
| 47 | HU Sophia | 6% | 26% | 38% | 23% | 6% | 1% | - |
| 48 | POTDAR Harper | 30% | 44% | 21% | 4% | - | - | - |
| 49 | KONDE Anika | 7% | 29% | 39% | 20% | 4% | - | - |
| 50 | ONG Katherine | 6% | 27% | 37% | 23% | 6% | 1% | - |
| 51 | MAGITSKY Giadora | 8% | 27% | 35% | 22% | 7% | 1% | - |
| 52 | FAZAL Sasha | 5% | 25% | 37% | 24% | 7% | 1% | - |
| 53 | SAGER Bianca | 9% | 33% | 38% | 17% | 3% | - | - |
| 54 | MULHERN Eleanor | - | 4% | 19% | 37% | 30% | 9% | 1% |
| 55 | WU Jing | 29% | 42% | 23% | 6% | 1% | - | - |
| 56 | CAO Audrey | 19% | 38% | 29% | 11% | 2% | - | - |
| 57 | WU Harper | < 1% | 4% | 15% | 30% | 31% | 16% | 3% |
| 58 | GROSSMAN Ann | 53% | 39% | 8% | 1% | - | - | |
| 59 | LIU Alyssa | 5% | 21% | 34% | 27% | 11% | 2% | - |
| 60 | RIFKIN Talia | 49% | 38% | 11% | 2% | - | - | - |
| 61 | VINBOR COSTA SANTOS Sasha | 6% | 24% | 35% | 25% | 9% | 2% | - |
| 62 | MADDISON Estelle | 35% | 43% | 18% | 3% | - | - | - |
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.