Rockland Community College - 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 | FOSS Persephone | - | - | 1% | 5% | 20% | 42% | 34% |
| 2 | VINOKUR Anita | - | - | - | 3% | 17% | 41% | 37% |
| 3 | ZHANG Ashley | - | - | - | 2% | 13% | 39% | 46% |
| 3 | MAK Jayden | - | 1% | 6% | 21% | 38% | 29% | 6% |
| 5 | CHOWDHERY Myra | - | 1% | 4% | 16% | 32% | 34% | 14% |
| 6 | DEMRY Kylee | 15% | 35% | 32% | 14% | 3% | < 1% | - |
| 7 | NG Sophia | - | 3% | 15% | 34% | 35% | 14% | |
| 8 | MAK Kaitlin | - | - | 1% | 5% | 22% | 42% | 30% |
| 9 | PARK Haylie | - | - | - | 4% | 20% | 43% | 31% |
| 10 | LAFFY Lily | - | - | 1% | 7% | 25% | 42% | 25% |
| 11 | NANDA Maanika | - | 1% | 6% | 23% | 38% | 26% | 6% |
| 12 | LEE Kaitlin | - | - | 5% | 22% | 38% | 28% | 7% |
| 13 | HUANG Pierra | - | 2% | 13% | 31% | 34% | 16% | 3% |
| 14 | WANG Keira | - | 6% | 27% | 38% | 23% | 6% | 1% |
| 15 | BANDHU Saahiti | 1% | 9% | 27% | 36% | 22% | 5% | |
| 16 | LEE Grace | - | 1% | 7% | 25% | 37% | 24% | 5% |
| 17 | VATS Ishita | - | 2% | 11% | 30% | 36% | 18% | 3% |
| 18 | OSMINKINA-JONES Kai | - | - | 1% | 6% | 24% | 42% | 27% |
| 19 | MCCARTHY Nora Louisa Abrous | - | 5% | 18% | 34% | 30% | 12% | 2% |
| 20 | MERZLYAKOVA Maria | - | 1% | 7% | 22% | 35% | 27% | 8% |
| 21 | REDA Sophie | - | 5% | 18% | 33% | 30% | 12% | 2% |
| 22 | ZHANG Audrey | 2% | 16% | 34% | 32% | 14% | 2% | |
| 23 | LEIGH Adalene | - | 1% | 9% | 28% | 37% | 21% | 4% |
| 24 | JOHN Sophia | - | - | 4% | 18% | 35% | 32% | 10% |
| 25 | WONG Charlene | - | - | 1% | 9% | 29% | 42% | 19% |
| 26 | WEI Avril | - | 4% | 15% | 31% | 32% | 15% | 2% |
| 27 | TA-ZHOU Sophia | - | 3% | 19% | 36% | 30% | 11% | 1% |
| 28 | YOUNG Sienna | 1% | 7% | 24% | 36% | 25% | 7% | 1% |
| 29 | LIANG Claire | - | 3% | 14% | 32% | 33% | 15% | 2% |
| 30 | DESAUTELS Alexandra | - | 1% | 7% | 22% | 36% | 27% | 7% |
| 31 | PEREIRA Izumi | 4% | 22% | 38% | 27% | 8% | 1% | - |
| 32 | MOTOVA Masha | 4% | 20% | 35% | 29% | 11% | 2% | - |
| 33 | SHI Chuqing | - | 4% | 18% | 35% | 31% | 11% | 1% |
| 34 | HILD Anya | - | 3% | 12% | 28% | 33% | 20% | 5% |
| 35 | ZHAO Selena | - | 6% | 21% | 36% | 28% | 8% | |
| 36 | CONVERSO-PARSONS Maia | 7% | 25% | 36% | 24% | 7% | 1% | - |
| 37 | LIU Teresa | 2% | 14% | 31% | 32% | 17% | 4% | - |
| 38 | FAZAL Sasha | 14% | 33% | 32% | 16% | 4% | 1% | - |
| 39 | MADDISON Erica | 17% | 39% | 31% | 11% | 2% | - | - |
| 40 | HAGLER Alice | 3% | 15% | 31% | 31% | 16% | 4% | - |
| 41 | HO Sophia | 1% | 7% | 22% | 35% | 26% | 9% | 1% |
| 42 | MARGULIS Roxana | 2% | 14% | 32% | 33% | 16% | 3% | - |
| 43 | ARORA Rhiya | 7% | 27% | 36% | 22% | 7% | 1% | - |
| 44 | CAFAGNA Sofia | - | 6% | 29% | 38% | 21% | 5% | - |
| 45 | FOLEY Serafina | 56% | 37% | 6% | - | - | - | - |
| 46 | CHAN Isla | - | 1% | 10% | 31% | 37% | 18% | 3% |
| 47 | MERZLYAKOVA Alexandra | 46% | 39% | 13% | 2% | - | - | |
| 48 | LEE Janice | 3% | 19% | 34% | 29% | 12% | 2% | - |
| 49 | DIBADJ Ava | 34% | 47% | 17% | 3% | - | - | - |
| 50 | KAKAR Sahana | 23% | 40% | 27% | 8% | 1% | - | - |
| 51 | GOLEN Grace | 7% | 26% | 36% | 23% | 7% | 1% | - |
| 52 | PATEL Sia | 14% | 38% | 33% | 13% | 2% | - | - |
| 53 | LEE Jiyoung | 22% | 44% | 27% | 7% | 1% | - | - |
| 54 | AN Jamie | 8% | 28% | 36% | 22% | 6% | 1% | - |
| 55 | PARKER Mrinali | 20% | 55% | 22% | 3% | - | - | - |
| 56 | BUCCINO Sloane | 29% | 47% | 20% | 4% | - | - | - |
| 57 | LIAO Amber | 10% | 30% | 35% | 19% | 5% | - | - |
| 57 | MISHRA Riona | 4% | 19% | 33% | 29% | 13% | 3% | - |
| 59 | SAGER Bianca | 5% | 24% | 36% | 25% | 8% | 1% | - |
| 60 | HARVEY-LEE Luisa | 2% | 16% | 34% | 32% | 14% | 2% | |
| 61 | WANG Diana | 1% | 11% | 31% | 35% | 19% | 4% | - |
| 62 | LIN Laura | 19% | 40% | 30% | 9% | 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.