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 | DAMBAL Sasha | - | - | 2% | 9% | 27% | 39% | 22% |
| 2 | GUGALA Hanna | - | - | 1% | 6% | 22% | 41% | 30% |
| 3 | HU Anna | - | - | - | 3% | 16% | 40% | 40% |
| 3 | GENTILE Vittoria | 2% | 14% | 31% | 33% | 17% | 3% | |
| 5 | HUANG Doris | - | 1% | 6% | 23% | 42% | 28% | |
| 6 | BAIK Sarah | 1% | 8% | 24% | 35% | 25% | 7% | |
| 7 | LIU Kelly | - | 2% | 13% | 34% | 37% | 14% | |
| 8 | MERMEGAS Olivia | - | 4% | 20% | 37% | 30% | 8% | |
| 9 | VINOKUR Anita | - | - | 5% | 22% | 43% | 30% | |
| 9 | KWON Ava | - | 1% | 9% | 30% | 40% | 19% | |
| 11 | HALPERIN Elizabeth H. | - | 3% | 14% | 32% | 36% | 15% | |
| 12 | LEOU Korina | - | - | 3% | 13% | 31% | 37% | 16% |
| 13 | LAFFY Lily | 7% | 31% | 39% | 19% | 4% | - | |
| 14 | RIFKIN Lielle | 14% | 41% | 33% | 11% | 2% | - | |
| 15 | RANDALL-COLLINS Shea M. | - | 6% | 22% | 35% | 26% | 9% | 1% |
| 16 | XU Elaine | 4% | 18% | 33% | 29% | 13% | 3% | - |
| 17 | KNOBEL Sophia | - | 1% | 8% | 24% | 36% | 25% | 6% |
| 18 | KIM Audrey | 2% | 13% | 31% | 33% | 17% | 3% | |
| 19 | RANJAN Diya | 1% | 9% | 28% | 37% | 21% | 4% | |
| 20 | SHMULER Fiona | - | 4% | 19% | 39% | 30% | 8% | |
| 21 | IANNUZZI Lucy | - | 7% | 25% | 36% | 24% | 7% | 1% |
| 22 | PASUPULETI Laya | 7% | 27% | 35% | 22% | 7% | 1% | - |
| 23 | STADNIK Emilia | 3% | 15% | 32% | 32% | 15% | 3% | |
| 24 | FOSS Persephone | - | 4% | 18% | 37% | 32% | 9% | |
| 25 | CHOI Charlotte | 1% | 7% | 23% | 35% | 26% | 7% | |
| 26 | KHOST Maeve | 1% | 10% | 26% | 34% | 22% | 7% | 1% |
| 27 | LOURENCO Alexandra | - | 4% | 17% | 32% | 30% | 14% | 2% |
| 28 | FUNG Iris | - | 2% | 14% | 36% | 36% | 11% | |
| 29 | PARK Haylie | 2% | 12% | 29% | 33% | 19% | 5% | 1% |
| 30 | PRESANTH Nandana | 1% | 9% | 27% | 35% | 22% | 5% | |
| 31 | NANDA Maanika | 5% | 23% | 37% | 26% | 8% | 1% | |
| 32 | ZONG Eliane | 19% | 38% | 29% | 11% | 2% | - | - |
| 33 | YANNOPOULOS Pompie | - | - | 3% | 14% | 32% | 36% | 15% |
| 34 | MAGITSKY Leila | 4% | 19% | 34% | 30% | 12% | 2% | |
| 35 | LIM Alexa J. | 1% | 12% | 33% | 35% | 16% | 2% | |
| 36 | MYAT Chloe | - | 2% | 14% | 31% | 34% | 16% | 3% |
| 37 | PROBASCO Leila | - | 1% | 6% | 21% | 35% | 29% | 8% |
| 38 | ZHANG Ashley | - | 4% | 16% | 32% | 31% | 15% | 2% |
| 39 | UEMOTO Lynn | - | 4% | 20% | 38% | 30% | 8% | |
| 39 | REN Katherine | 1% | 11% | 33% | 36% | 17% | 3% | |
| 41 | BORGUETA Madison | - | 3% | 19% | 38% | 30% | 8% | |
| 42 | GUHA Surabhi | 2% | 15% | 32% | 31% | 15% | 4% | - |
| 43 | MAK Kaitlin | - | 5% | 18% | 32% | 30% | 13% | 2% |
| 44 | LIANG Claire | 2% | 20% | 37% | 29% | 11% | 2% | - |
| 45 | DESAUTELS Alexandra | 10% | 29% | 34% | 20% | 6% | 1% | - |
| 46 | TA-ZHOU Emma | - | 1% | 8% | 27% | 42% | 23% | |
| 47 | REKHTMAN Alice | 10% | 30% | 35% | 20% | 5% | 1% | |
| 48 | VISWANATHAN Nishka | 12% | 33% | 34% | 17% | 4% | - | |
| 49 | WONG Charlene | 6% | 30% | 40% | 20% | 4% | - | |
| 50 | BARNES Sarah | 27% | 42% | 24% | 6% | 1% | - | |
| 51 | AKULA Roszlynn | 5% | 20% | 34% | 28% | 11% | 2% | - |
| 52 | KRASOWITZ Lucy | - | 3% | 15% | 32% | 33% | 15% | 2% |
| 53 | HILD Anya | 10% | 30% | 34% | 20% | 6% | 1% | - |
| 54 | WANG JiaQi | 1% | 8% | 24% | 36% | 25% | 7% | |
| 55 | FIGELMAN Maya | 21% | 48% | 25% | 5% | - | - | |
| 56 | LEUNG Ella | 38% | 43% | 16% | 3% | - | - | |
| 57 | MANSPERGER Gia | 8% | 31% | 37% | 19% | 4% | - | |
| 58 | VITUG Greta | 40% | 42% | 15% | 2% | - | - | |
| 59 | YOON Sela | 6% | 25% | 35% | 24% | 8% | 1% | - |
| 60 | BERRIOS Catalina | 1% | 8% | 24% | 34% | 24% | 8% | 1% |
| 61 | NG Sophia | 23% | 40% | 27% | 9% | 2% | - | - |
| 62 | COLE Beatrice | 41% | 42% | 15% | 2% | - | - | |
| 63 | LEIGH Adalene | 24% | 40% | 26% | 9% | 1% | - | |
| 64 | YUN Madison | 68% | 27% | 4% | - | - | - | - |
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.