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 | WANG JiaQi | - | - | - | 2% | 14% | 40% | 44% |
| 2 | KWON Ava | - | - | - | 3% | 16% | 40% | 40% |
| 3 | MEYERSON Michelle | - | - | 2% | 9% | 26% | 40% | 24% |
| 3 | ZHANG Ashley | - | - | 1% | 8% | 32% | 48% | 12% |
| 5 | NEMORIN Rei | - | - | - | 2% | 15% | 42% | 41% |
| 6 | FOSS Persephone | - | - | 2% | 8% | 26% | 40% | 25% |
| 7 | GONG Joy | - | - | 1% | 9% | 31% | 45% | 13% |
| 8 | FRAZIER Chloe | 1% | 10% | 26% | 34% | 21% | 6% | 1% |
| 9 | CHOWDHERY Myra | - | 1% | 8% | 28% | 41% | 22% | |
| 10 | FUNG Iris | - | - | - | 4% | 17% | 40% | 39% |
| 11 | LIANG Claire | - | - | 2% | 14% | 36% | 37% | 10% |
| 12 | MAK Jayden | - | 1% | 10% | 29% | 37% | 19% | 3% |
| 13 | PARK Haylie | - | 2% | 9% | 24% | 35% | 24% | 6% |
| 14 | TA-ZHOU Sophia | 1% | 9% | 26% | 35% | 23% | 6% | 1% |
| 15 | BANDHU Saahiti | 1% | 7% | 21% | 33% | 27% | 10% | 1% |
| 16 | ZHAO Selena | 3% | 16% | 33% | 31% | 14% | 3% | - |
| 17 | PATEL Maia | 1% | 6% | 21% | 35% | 28% | 9% | 1% |
| 18 | LEE Grace | - | 2% | 8% | 24% | 35% | 25% | 6% |
| 19 | MULLER Inara | - | 1% | 9% | 25% | 37% | 23% | 4% |
| 20 | HUANG Pierra | 5% | 21% | 34% | 27% | 11% | 2% | - |
| 21 | HAGLER Alice | 2% | 11% | 30% | 35% | 18% | 4% | - |
| 22 | KIM Grace | 1% | 7% | 23% | 36% | 26% | 7% | 1% |
| 23 | FONG Zoe | 6% | 26% | 37% | 23% | 7% | 1% | - |
| 24 | WANG Keyu | - | 1% | 8% | 26% | 38% | 22% | 4% |
| 25 | YERENKOVA Ameliia | 1% | 9% | 25% | 33% | 22% | 7% | 1% |
| 26 | ZHANG Audrey | 2% | 12% | 28% | 33% | 20% | 6% | 1% |
| 27 | ALMEDA Galina | - | 3% | 18% | 37% | 32% | 9% | |
| 28 | JOHN Sophia | 1% | 9% | 28% | 36% | 21% | 4% | - |
| 29 | GOEL Lineysha | 1% | 9% | 25% | 34% | 23% | 8% | 1% |
| 30 | NEGROIU Mara | 11% | 31% | 33% | 18% | 5% | 1% | - |
| 31 | MOTOVA Masha | 6% | 26% | 38% | 23% | 6% | 1% | - |
| 32 | PIENKOWSKI Olivia | 7% | 25% | 34% | 23% | 8% | 1% | - |
| 33 | SEO Kaitlyn | - | 3% | 12% | 29% | 34% | 19% | 3% |
| 34 | CAFAGNA Sofia | - | - | - | 2% | 13% | 40% | 45% |
| 35 | JUN Sofia | 36% | 42% | 18% | 3% | - | - | |
| 36 | CONVERSO-PARSONS Maia | 10% | 36% | 36% | 15% | 3% | - | |
| 37 | WANG MONA | 3% | 16% | 32% | 30% | 15% | 3% | - |
| 38 | CHAU Zoey | 2% | 11% | 27% | 33% | 21% | 6% | 1% |
| 39 | KIM Eunjae | 3% | 14% | 30% | 32% | 17% | 4% | - |
| 40 | YOUNG Sienna | 2% | 13% | 29% | 32% | 18% | 5% | 1% |
| 41 | MALUKI Nia | 1% | 7% | 26% | 37% | 24% | 5% | |
| 42 | STOLCKE Saskia | 8% | 26% | 35% | 22% | 7% | 1% | - |
| 43 | KABILING Anika Von Marie | - | 3% | 16% | 34% | 32% | 13% | 2% |
| 44 | WANG Chloe | 13% | 34% | 34% | 15% | 4% | - | - |
| 45 | CHEN Chloe | 3% | 15% | 30% | 31% | 17% | 4% | - |
| 46 | YIN Xizi | - | 2% | 9% | 23% | 33% | 25% | 8% |
| 47 | YAP Anna | 4% | 21% | 36% | 28% | 9% | 1% | - |
| 48 | LIAO Amber | 19% | 39% | 29% | 10% | 2% | - | - |
| 49 | ZHANG Zoe Muchen | 1% | 23% | 41% | 27% | 7% | 1% | - |
| 50 | SAGER Bianca | 30% | 43% | 22% | 5% | - | - | - |
| 51 | CHANG Grace | 6% | 25% | 37% | 24% | 7% | 1% | - |
| 52 | LIU Teresa | - | 3% | 14% | 32% | 34% | 16% | 2% |
| 53 | FADEL Emma | - | 5% | 18% | 34% | 30% | 11% | 1% |
| 54 | PASSMAN Caroline | 9% | 33% | 37% | 17% | 3% | - | - |
| 55 | HURÉ Maïa | 3% | 17% | 32% | 30% | 14% | 3% | - |
| 56 | SMITH Genevieve | 23% | 40% | 27% | 8% | 1% | - | - |
| 57 | BAO Amelia | 19% | 37% | 29% | 12% | 3% | - | - |
| 58 | FUNG Dylan | 2% | 14% | 33% | 34% | 16% | 3% | |
| 59 | MOFFITT Charlotte | 4% | 18% | 33% | 29% | 13% | 3% | - |
| 60 | KARAVAS Lucy | 15% | 35% | 32% | 15% | 3% | - | - |
| 60 | VARAH Alaia | 3% | 16% | 31% | 30% | 15% | 4% | - |
| 62 | GRONEMEYER Emily | 25% | 42% | 25% | 7% | 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.