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 | LI Alice | - | - | - | 5% | 30% | 64% | |
2 | VOSKOV Olivia | - | - | - | 2% | 14% | 40% | 44% |
3 | KOUAME Candice | 5% | 23% | 38% | 26% | 8% | 1% | |
3 | WONG Sydney | - | - | - | 4% | 18% | 41% | 36% |
5 | LAW Mila | - | - | 3% | 15% | 34% | 35% | 13% |
6 | MOKRETSOV Leah | - | 1% | 5% | 19% | 37% | 31% | 7% |
7 | CHEN Madeline | - | 4% | 18% | 35% | 32% | 11% | |
8 | HOWARD Katherine | 1% | 8% | 27% | 39% | 22% | 3% | |
9 | BOROTKO Katerina | - | - | 1% | 6% | 23% | 41% | 29% |
10 | TIAN Victoria | - | 4% | 21% | 40% | 30% | 5% | |
11 | ORDORICA Abra | - | - | 4% | 18% | 37% | 31% | 9% |
12 | DESANTIS-IBANEZ Elena | - | - | - | 2% | 14% | 40% | 44% |
13 | ZHANG Ashley | - | 2% | 12% | 30% | 34% | 18% | 3% |
14 | ZHU Una | - | 2% | 12% | 31% | 38% | 17% | |
15 | KIM Abigail | 1% | 12% | 32% | 36% | 16% | 2% | |
16 | REDWINE Louise | 11% | 33% | 35% | 17% | 4% | - | - |
17 | YAN Ximei (Alicia) | - | 1% | 5% | 23% | 43% | 27% | |
18 | CHEN Alina | - | - | - | 4% | 21% | 43% | 31% |
19 | BURROWS Beatrice | - | 1% | 8% | 25% | 37% | 24% | 5% |
20 | SONKU Mira | - | 4% | 18% | 34% | 30% | 12% | 2% |
21 | HAN Emma | - | 1% | 10% | 30% | 38% | 18% | 2% |
22 | KIM Charlotte | 7% | 33% | 39% | 18% | 3% | - | |
23 | XIE ANDREA | 1% | 9% | 30% | 39% | 18% | 2% | |
24 | YU Livia | - | 1% | 7% | 27% | 40% | 22% | 4% |
25 | GOTSABINA Elizabeth | - | 4% | 22% | 39% | 27% | 7% | 1% |
26 | YOON Cora | 4% | 18% | 33% | 29% | 13% | 3% | - |
27 | LI Kayla | 5% | 23% | 36% | 25% | 8% | 1% | - |
28 | KAKANI Aditi | - | - | 2% | 13% | 34% | 37% | 13% |
29 | JIANG Chenxi | - | 1% | 10% | 30% | 41% | 18% | |
30 | KLAUSZ Izabella | - | 3% | 13% | 31% | 35% | 17% | 2% |
31 | CHEN Allison | 1% | 9% | 25% | 33% | 23% | 8% | 1% |
32 | NING Miranda | - | - | < 1% | 6% | 32% | 62% | |
33 | YUSHCHENKO Ivanka | 12% | 34% | 35% | 16% | 3% | - | |
34 | LIU Brinley | 1% | 7% | 24% | 36% | 25% | 7% | 1% |
35 | LI Xier | - | 2% | 9% | 24% | 35% | 24% | 6% |
36 | PATEL Aria | 5% | 23% | 37% | 25% | 8% | 1% | - |
37 | NIKOLLA Vivienne | 4% | 18% | 33% | 29% | 13% | 3% | - |
38 | YOUNG Penelope | 7% | 27% | 37% | 23% | 7% | 1% | - |
40 | WARD Imani | 4% | 20% | 37% | 29% | 9% | 1% | |
41 | ZHANG Chloe | 1% | 11% | 33% | 35% | 17% | 3% | - |
42 | DING Iris Siyue | 2% | 15% | 33% | 33% | 15% | 2% | |
43 | SULLIVAN Adela | 18% | 41% | 31% | 10% | 1% | - | |
44 | GORE Amina | 3% | 18% | 37% | 31% | 10% | 1% | |
45 | YIN Elaine | 6% | 25% | 37% | 24% | 7% | 1% | - |
46 | LEUNG Morgan | 8% | 26% | 34% | 23% | 8% | 1% | - |
47 | CHO Josephine | 25% | 41% | 26% | 7% | 1% | - | - |
48 | GOFMAN Anastasia | 1% | 6% | 22% | 35% | 27% | 9% | 1% |
49 | ZHENG Kristen | - | 5% | 22% | 35% | 27% | 9% | 1% |
50 | LAU Ivana | 44% | 40% | 14% | 2% | - | - | - |
51 | CHAKRAPANI Tara | 3% | 19% | 39% | 30% | 8% | 1% | |
52 | BOUTSIKARIS Asha | 21% | 39% | 28% | 10% | 2% | - | |
53 | LIU Mina | 2% | 18% | 41% | 29% | 8% | 1% | |
54 | LEE Zoe | 4% | 20% | 36% | 29% | 10% | 2% | - |
55 | PATEL Agena | 14% | 35% | 34% | 14% | 2% | - | |
56 | KUO Stella | 10% | 39% | 35% | 13% | 3% | - | - |
57 | PAN Emma | 5% | 20% | 33% | 28% | 12% | 2% | - |
58 | PINCHUK Yael | 4% | 21% | 37% | 29% | 9% | 1% | |
59 | ALLIEVI Simone | - | 2% | 13% | 30% | 34% | 17% | 3% |
59 | JU Jennifer | - | 4% | 16% | 33% | 32% | 13% | 2% |
61 | CHAN Faith Sum Yin | 10% | 45% | 35% | 9% | 1% | - | - |
62 | NYE Emma | - | 4% | 17% | 34% | 31% | 12% | 2% |
63 | WANG Katherine | 25% | 43% | 25% | 7% | 1% | - | |
64 | TANG Jacquelyn | 20% | 39% | 29% | 10% | 2% | - | - |
65 | CHI Evelyn | 33% | 42% | 20% | 4% | - | - | - |
66 | SUN Sarah | 50% | 38% | 11% | 1% | - | - | |
67 | WILLIAMS Valentina | 66% | 30% | 4% | - | - | - | - |
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.