King of Prussia, PA - King of Prussia, PA, 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 | ||
1 | HOOSHI Erica S. | - | - | 4% | 19% | 42% | 34% |
2 | HORSLEY Asherah | - | - | 1% | 11% | 40% | 47% |
3 | MILLER Naomi E. | - | 2% | 12% | 35% | 38% | 14% |
3 | HECKMANN Emma | 1% | 6% | 24% | 38% | 25% | 6% |
5 | EYER Hailey M. | - | 6% | 24% | 37% | 26% | 7% |
6 | SERBAN Samantha M. | - | 1% | 7% | 25% | 42% | 25% |
7 | JANG Kimberley | - | 1% | 9% | 31% | 40% | 18% |
8 | GU Emily | 20% | 41% | 29% | 9% | 1% | - |
9 | KOENIG Charlotte R. | - | 4% | 19% | 38% | 31% | 8% |
10 | DU Hannah | 8% | 30% | 39% | 20% | 4% | - |
11 | PERLMAN Talia | 1% | 13% | 34% | 34% | 15% | 2% |
12 | SADAN Jordan E. | - | 4% | 19% | 37% | 31% | 9% |
13 | ACHILOVA Feyza | 4% | 23% | 39% | 26% | 7% | 1% |
14 | LOCKE Savannah | 1% | 10% | 30% | 39% | 18% | 2% |
15 | CHEN Allison V. | 1% | 7% | 26% | 39% | 23% | 5% |
16 | CASTANEDA Erika L. | - | 3% | 15% | 35% | 35% | 11% |
17 | PAHLAVI Dahlia | 3% | 19% | 37% | 29% | 10% | 1% |
18 | DAVIA Daniella V. | - | 2% | 12% | 35% | 39% | 12% |
19 | NEWHARD Zelia "Zizi" | - | 2% | 14% | 36% | 36% | 12% |
19 | HUANG NATALIE | 2% | 15% | 39% | 32% | 11% | 1% |
21 | SHEN Lydia | - | 4% | 20% | 37% | 30% | 9% |
22 | ADAMS KIM Natalie | - | 9% | 29% | 37% | 21% | 5% |
23 | MAO Rebecca J. | 17% | 40% | 32% | 10% | 1% | - |
24 | CHEN Jasmine | 57% | 36% | 7% | 1% | - | - |
25 | MCKEE Alexandra K. | 10% | 41% | 35% | 11% | 2% | - |
26 | HOLLE Aviella S. | 26% | 43% | 24% | 6% | 1% | - |
27 | RENTON Samantha | 5% | 27% | 39% | 23% | 6% | - |
28 | WEINTRAUB Io H. | 16% | 40% | 32% | 11% | 2% | - |
29 | PAVE Claire | 45% | 40% | 13% | 2% | - | - |
30 | ROMANO Megan C. | 86% | 13% | 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.