Philadelphia, PA - Philadelphia, 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 | 6 | ||
1 | CHAN Casey | - | - | - | 3% | 25% | 72% | |
2 | SAYLES Nina R. | - | 1% | 5% | 19% | 34% | 31% | 11% |
3 | HONE Katarina G. | - | - | 4% | 17% | 36% | 32% | 10% |
3 | ANDRES Charmaine G. | - | 4% | 18% | 36% | 31% | 10% | |
5 | CAO Stephanie X. | - | - | 4% | 15% | 32% | 34% | 15% |
6 | CHIOLDI Mina | - | 1% | 7% | 25% | 40% | 26% | |
7 | CHANG Emily | - | 4% | 17% | 32% | 30% | 14% | 2% |
8 | SATHYANATH Kailing | - | - | 1% | 7% | 23% | 41% | 28% |
9 | OISHI Megumi | - | - | - | 1% | 7% | 33% | 60% |
10 | BROWNE Alexis G. | - | 1% | 8% | 28% | 43% | 20% | |
11 | MADA Skye | 12% | 32% | 34% | 18% | 4% | - | |
12 | SHOMAN Miriam | - | - | 4% | 17% | 34% | 33% | 11% |
13 | ENGELMAN-SANZ Madeline A. | - | 1% | 7% | 25% | 42% | 26% | |
14 | NEIBART Fiona | 4% | 19% | 34% | 29% | 11% | 2% | |
15 | DANK Dina | 2% | 13% | 30% | 34% | 18% | 3% | |
16 | SUN Alyssa | 8% | 28% | 37% | 21% | 6% | 1% | |
17 | ANDRES Katherine A. | - | - | 2% | 11% | 30% | 39% | 18% |
18 | FEARNS Zara A. | - | 2% | 16% | 41% | 36% | 5% | |
19 | ENDO Miyuki N. | 1% | 10% | 32% | 37% | 17% | 3% | |
20 | BENOIT Adelaide L. | - | 2% | 16% | 36% | 33% | 12% | 1% |
21 | TAO Hannah J. | - | - | 5% | 24% | 44% | 27% | |
22 | PRIEUR Lauren | 1% | 10% | 29% | 36% | 20% | 4% | |
23 | SCALAMONI-GOLDSTEIN Charlotte S. | 1% | 10% | 29% | 36% | 20% | 4% | |
24 | BOIS Adele | - | 3% | 17% | 35% | 33% | 11% | |
25 | NEWELL Alexia C. | - | 1% | 7% | 22% | 35% | 27% | 8% |
26 | BAKER Audrey C. | - | 6% | 26% | 38% | 23% | 6% | 1% |
27 | ROGERS Pauline E. | 2% | 13% | 30% | 33% | 18% | 4% | - |
28 | YANG Ashley M. | 1% | 5% | 18% | 32% | 29% | 13% | 2% |
29 | LIU Rachel | - | 3% | 13% | 29% | 33% | 18% | 4% |
30 | SHI Cathleen | 2% | 16% | 39% | 33% | 9% | - | |
31 | JUNG Irene | 2% | 16% | 37% | 32% | 11% | 1% | |
32 | COLTER Aurora | 25% | 40% | 26% | 8% | 1% | - | - |
33 | MENKE Kavya I. | 1% | 8% | 24% | 34% | 24% | 7% | 1% |
34 | SADIK HANA | 4% | 19% | 34% | 28% | 12% | 2% | - |
35 | TIBURCIO Diana | - | 3% | 14% | 29% | 32% | 18% | 4% |
36 | DEPEW Charlotte R. | 2% | 15% | 31% | 31% | 16% | 4% | - |
37 | YONG Erika E. | - | 4% | 19% | 36% | 31% | 10% | |
38 | LARIMER Katherine E. | 6% | 25% | 37% | 24% | 7% | 1% | |
39 | DRAGON Rainer | - | 4% | 19% | 36% | 31% | 10% | |
40 | ZIELINSKI Isabella G. | - | 3% | 18% | 36% | 30% | 11% | 2% |
41 | SATHE Mehek S. | - | 3% | 21% | 38% | 28% | 8% | 1% |
42 | NI Sharon | - | 1% | 12% | 33% | 36% | 16% | 2% |
43 | STONE Hava S. | - | 1% | 6% | 23% | 38% | 26% | 6% |
44 | YODER Bridget H. | 2% | 12% | 28% | 32% | 19% | 6% | 1% |
45 | VALADEZ Emily T. | - | 5% | 19% | 32% | 29% | 13% | 2% |
46 | TURNOF Kayla M. | - | 1% | 11% | 31% | 37% | 17% | 2% |
47 | YERRAMILLI Kavya | 16% | 36% | 31% | 14% | 3% | - | - |
48 | KALINICHENKO Alexandra (Sasha) | 1% | 10% | 33% | 40% | 16% | 1% | |
49 | JEAN Olympe G. | 19% | 41% | 30% | 10% | 1% | - | |
50 | D'ORAZIO Sofia V. | 43% | 42% | 14% | 2% | - | - | |
51 | TUNG Renee | 11% | 51% | 30% | 7% | 1% | - | - |
52 | HE Cassandra | 3% | 17% | 33% | 29% | 14% | 3% | - |
53 | ARNECKE Lauren A. | 2% | 13% | 30% | 32% | 18% | 5% | - |
54 | DHAR Aamina | 25% | 43% | 25% | 7% | 1% | - | |
55 | MEYTIN Sophia E. | 39% | 43% | 16% | 2% | - | - | |
56 | HUNG Anna | 7% | 25% | 36% | 24% | 8% | 1% | |
57 | NOBREGA Carolina S. | 3% | 15% | 32% | 32% | 15% | 2% | |
58 | CHIN Elise | 31% | 41% | 21% | 6% | 1% | - | - |
59 | PI Sophia | 39% | 46% | 14% | 2% | - | - | - |
60 | TONG Jessie | 29% | 49% | 19% | 3% | - | - | - |
61 | BARTON Mele | 15% | 44% | 32% | 8% | 1% | - | |
62 | GAJOWSKYJ Sophie K. | 13% | 40% | 34% | 12% | 2% | - | |
63 | YUAN Greta | 11% | 31% | 34% | 18% | 5% | 1% | - |
64 | GIRARDI Aemilia | 22% | 40% | 28% | 9% | 1% | - | |
65 | CHEN Athena | 72% | 25% | 2% | - | - | - | - |
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.