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 | ADVINCULA Anabella E. | - | 4% | 19% | 37% | 31% | 9% | |
2 | LU Junyao | - | - | 1% | 7% | 35% | 58% | |
3 | LUO Ashley | - | - | 5% | 22% | 43% | 29% | |
3 | PIEDRAHITA GOMEZ Alejandra | - | - | 3% | 14% | 34% | 35% | 14% |
5 | KIZILBASH Zara | - | 1% | 6% | 20% | 34% | 29% | 10% |
6 | JIMENEZ VASQUEZ SARA | - | - | - | 1% | 7% | 34% | 58% |
7 | ALVIDREZ Francesca A. | - | 2% | 12% | 37% | 40% | 9% | |
8 | DE JAGER Celine | - | 1% | 9% | 28% | 39% | 20% | 3% |
9 | BECCHINA Olivia | - | - | 1% | 9% | 29% | 42% | 18% |
10 | SMUK Daria A. | - | 1% | 8% | 30% | 41% | 19% | |
11 | ZHAO Yingying | - | 1% | 10% | 33% | 40% | 16% | |
12 | YANG Chloe | - | 1% | 8% | 25% | 36% | 24% | 6% |
13 | CORREA SANTA Carmen Andrea | - | 2% | 10% | 28% | 39% | 21% | |
14 | MASTRONARDI Laura | 3% | 16% | 33% | 32% | 14% | 2% | |
15 | KIZILBASH Alizeh H. | 2% | 18% | 41% | 30% | 8% | 1% | |
16 | APPLEBEE Andralyn | 11% | 35% | 36% | 15% | 3% | - | |
17 | SIDDIQUI Ammna K. | - | 1% | 4% | 17% | 34% | 33% | 12% |
18 | SALAZAR Susana | - | 1% | 7% | 27% | 42% | 23% | |
19 | RAI Ananya | 13% | 39% | 34% | 12% | 2% | - | < 1% |
20 | OAKE Erica | 5% | 22% | 35% | 27% | 10% | 1% | |
21 | OSTROVSKY Emily I. | 3% | 16% | 34% | 32% | 13% | 1% | |
22 | EBRAHIM Ameera H. | - | 4% | 18% | 37% | 32% | 9% | |
23 | JOYAL Anne-Sophie | - | 4% | 19% | 36% | 30% | 9% | 1% |
24 | BLAKE Caira | - | 2% | 16% | 38% | 34% | 10% | |
25 | BYRON Karen J. | 4% | 20% | 36% | 29% | 10% | 1% | |
26 | LI Alisha | 2% | 14% | 32% | 34% | 15% | 2% | |
27 | BOOK Ayelet | 15% | 35% | 32% | 14% | 3% | - | |
28 | YAO Jillian | - | - | - | 5% | 21% | 43% | 30% |
29 | GLASSNER Sophia Rose S. | - | 5% | 23% | 38% | 25% | 6% | - |
30 | INAMDAR Nina S. | - | 1% | 9% | 26% | 36% | 23% | 5% |
31 | ZENG Katrina | 7% | 26% | 36% | 23% | 7% | 1% | - |
32 | BANKULLA Misha R. | 1% | 11% | 31% | 35% | 18% | 4% | - |
33 | GAO Judy | - | - | 4% | 19% | 37% | 30% | 9% |
34 | GANGEMI Julia | 1% | 9% | 29% | 36% | 20% | 5% | - |
35 | GUZZI Jordan | 1% | 6% | 21% | 34% | 27% | 10% | 1% |
36 | LEE Yedda | - | 1% | 8% | 25% | 37% | 24% | 4% |
37 | LIN Julia L. | - | 1% | 8% | 26% | 37% | 23% | 5% |
38 | COYLE Dana | - | 4% | 21% | 38% | 29% | 8% | |
39 | BOWIE Charlotta | 1% | 9% | 34% | 38% | 16% | 2% | |
40 | AVERBACH Margaret | 5% | 25% | 40% | 24% | 6% | 1% | - |
41 | JOSEPH mikayla | 11% | 32% | 34% | 18% | 4% | - | |
42 | TEMIRYAEV Anna M. | - | 1% | 4% | 20% | 41% | 34% | |
43 | CORDERO Allison | 1% | 7% | 29% | 42% | 19% | 2% | |
44 | ZAKHAROV Anne E. | 2% | 17% | 38% | 31% | 11% | 1% | |
45 | LI Allison | 6% | 23% | 35% | 26% | 9% | 1% | |
46 | MCGEE Sophia | 1% | 8% | 25% | 36% | 24% | 6% | |
47 | MOK Chloe R. | 12% | 38% | 35% | 13% | 2% | - | |
48 | SANTANA Mia | 6% | 27% | 37% | 22% | 6% | 1% | - |
49 | SINGH Aayushi | 5% | 21% | 36% | 27% | 10% | 2% | - |
50 | HIRSCH Naomi B. | 1% | 7% | 26% | 38% | 23% | 4% | |
51 | GUTKOVSKAYA Nora | 3% | 18% | 34% | 31% | 13% | 2% | |
51 | YOON Katherine | 5% | 21% | 35% | 27% | 10% | 1% | |
53 | GORTI Saumya | 25% | 45% | 25% | 5% | - | - | |
54 | HOSANAGAR Inchara | 32% | 43% | 20% | 4% | - | - | |
55 | PAN Iris | 38% | 47% | 14% | 2% | - | - | |
56 | JIA Elizabeth | 43% | 41% | 14% | 2% | - | - | - |
57 | LEE Anna | 1% | 20% | 39% | 29% | 10% | 1% | - |
58 | ZISCHKE Alexandra A. | 8% | 35% | 37% | 16% | 3% | - | - |
59 | MAMKIN Anastasia | 76% | 22% | 2% | - | - | - | - |
60 | MURRELL Jessica L. | 32% | 47% | 18% | 3% | - | - | |
61 | SHUKLA Tanya | 31% | 49% | 18% | 3% | - | - | |
62 | LIU Angela | 17% | 43% | 30% | 8% | 1% | - | - |
63 | RAMANATHAN Eesha | 39% | 42% | 16% | 3% | - | - | |
64 | RATTRAY Katherine | 22% | 39% | 27% | 10% | 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.