Suffern, NY - 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 | PRIEUR Lauren | - | - | 2% | 15% | 46% | 38% | |
| 2 | VADASZ Ibla P. | - | - | - | - | 5% | 29% | 65% |
| 3 | BEVACQUA Aria F. | - | - | 3% | 15% | 35% | 36% | 11% |
| 3 | CHIANG Emily | - | - | 2% | 12% | 34% | 39% | 13% |
| 5 | MCKEE Ainsley | 3% | 14% | 31% | 31% | 16% | 4% | < 1% |
| 6 | LEE Sophia | 1% | 9% | 27% | 37% | 22% | 4% | |
| 7 | LIGH Erenei J. | - | 4% | 18% | 36% | 32% | 10% | |
| 8 | DUBOIS Lauren N. | - | - | 2% | 15% | 45% | 39% | |
| 9 | SCALAMONI-GOLDSTEIN Charlotte S. | - | - | - | 2% | 15% | 42% | 41% |
| 10 | LIN Angela | - | - | 5% | 26% | 47% | 21% | |
| 11 | MUNGOVAN Cecilia C. | 8% | 46% | 37% | 9% | < 1% | ||
| 12 | SOURIMTO Valeria | - | - | - | 3% | 17% | 42% | 38% |
| 13 | DUCKETT Madison | - | - | - | 2% | 15% | 42% | 41% |
| 14 | ANTHONY Alexia B. | 1% | 21% | 47% | 27% | 4% | ||
| 15 | FEIG Sela | - | 3% | 12% | 28% | 33% | 19% | 4% |
| 16 | PASHIN Anna | - | - | 3% | 13% | 31% | 36% | 17% |
| 17 | REN Xinling | - | 6% | 37% | 42% | 14% | 1% | |
| 18 | FESTA Carina | - | 3% | 13% | 30% | 35% | 17% | 2% |
| 19 | JENKINS Scotland | 6% | 27% | 38% | 23% | 6% | 1% | |
| 20 | YUAN Greta | - | 1% | 8% | 27% | 41% | 22% | |
| 21 | TSUI Natalie | - | 1% | 8% | 28% | 41% | 21% | |
| 22 | NG Sarah W. | 3% | 17% | 35% | 31% | 12% | 2% | |
| 23 | NATH Trisha | - | 6% | 27% | 43% | 20% | 3% | |
| 24 | ILYIN Anna | 12% | 38% | 35% | 13% | 2% | - | |
| 25 | YAN Ava | 1% | 6% | 22% | 36% | 27% | 8% | - |
| 26 | KIM Marley I. | 1% | 9% | 34% | 43% | 13% | ||
| 27 | SO Catelyn | - | - | 2% | 11% | 33% | 41% | 14% |
| 28 | WANG Jianning | - | 2% | 13% | 33% | 35% | 15% | 2% |
| 29 | GIBEK Victoria | 1% | 7% | 27% | 40% | 22% | 3% | |
| 30 | DANK Dina | - | 2% | 12% | 32% | 38% | 16% | |
| 31 | JAVERI Amaya | - | 3% | 16% | 33% | 33% | 13% | 1% |
| 32 | GRINBERG Aliya | - | 5% | 18% | 32% | 30% | 13% | 2% |
| 33 | GOSALIA Nidhi | 1% | 13% | 33% | 34% | 16% | 3% | - |
| 34 | CRUZ Sonia | 14% | 34% | 33% | 15% | 4% | - | - |
| 35 | DAVIS Jordan | - | 4% | 18% | 36% | 31% | 10% | 1% |
| 36 | NAYAK Anika | 4% | 21% | 38% | 27% | 9% | 1% | - |
| 37 | GOMERMAN Sophia | - | 8% | 29% | 38% | 20% | 4% | - |
| 38 | JEONG Katie | - | 4% | 18% | 36% | 30% | 10% | 1% |
| 39 | HE Lizbeth | - | - | 7% | 34% | 43% | 16% | |
| 40 | MESSICK Maya | 19% | 47% | 28% | 6% | - | - | |
| 41 | KHAN Alissa | 11% | 34% | 35% | 16% | 3% | - | |
| 42 | DAMDINSUREN Sophie | 29% | 44% | 22% | 5% | - | - | - |
| 43 | XU ALINA | 3% | 18% | 36% | 30% | 11% | 2% | - |
| 44 | NGUYEN Ella | 14% | 36% | 33% | 14% | 3% | - | - |
| 45 | STRAYER Sofia I. | 54% | 36% | 9% | 1% | - | - | - |
| 46 | WALSHE Kira | 2% | 13% | 33% | 34% | 16% | 3% | - |
| 47 | OGANEZOVA Valerie | - | 3% | 17% | 36% | 32% | 10% | 1% |
| 48 | FLATT Sophia | 17% | 38% | 30% | 12% | 2% | - | - |
| 49 | LI Sophie | - | 7% | 27% | 37% | 22% | 5% | - |
| 50 | MCCREARY Camryn A. | - | < 1% | 8% | 39% | 53% | ||
| 51 | LOPEZ-ONA Mia | - | 5% | 22% | 39% | 27% | 6% | |
| 52 | JIN Zhixin | 39% | 45% | 14% | 1% | - | - | |
| 53 | LEUNG Ashlyn K. | 2% | 19% | 43% | 28% | 6% | - | |
| 54 | PRADO-TUCKER Isabel | 31% | 55% | 13% | 1% | - | - | |
| 55 | FEO ZAKHAROVA Isabella | 60% | 33% | 6% | - | - | - | - |
| 56 | YEN Natalie | 14% | 38% | 33% | 12% | 2% | - | - |
| 56 | MONTORIO Lily M. | 13% | 34% | 33% | 16% | 4% | - | - |
| 58 | STRIZHEVSKY Ariel | 8% | 36% | 37% | 16% | 3% | - | - |
| 59 | BEILEY Erin | 67% | 29% | 4% | - | - | ||
| 60 | ZHANG Sophie | 32% | 42% | 21% | 5% | - | - | |
| 60 | DAI Olivia | 43% | 43% | 12% | 1% | - | - | |
| 62 | YOUNG Audrey | < 1% | 3% | 13% | 29% | 33% | 18% | 4% |
| 63 | YU Abriella R. | 21% | 41% | 28% | 9% | 1% | - | |
| 64 | WANG Audrey | 2% | 21% | 39% | 28% | 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.