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 | NING Miranda | - | - | - | 3% | 17% | 43% | 37% |
2 | CHEN Madeline | - | - | 1% | 17% | 47% | 35% | |
3 | YANG Hannah | - | - | 1% | 6% | 23% | 42% | 29% |
3 | OLELE Ifechi | - | - | - | 1% | 6% | 32% | 62% |
5 | LEE Kate | - | - | - | 2% | 12% | 38% | 48% |
6 | CHEN Allison | - | 2% | 11% | 29% | 36% | 19% | 4% |
7 | YAN Ximei (Alicia) | - | - | - | 5% | 23% | 44% | 28% |
8 | CHOI Arianna | - | 1% | 8% | 26% | 39% | 22% | 4% |
9 | DHAIYA Tanya | - | - | - | - | 3% | 25% | 72% |
10 | ZHANG Ashley | - | - | 3% | 15% | 33% | 35% | 13% |
11 | HOWARD Katherine | - | 2% | 9% | 25% | 35% | 23% | 6% |
12 | LEE Zoe | 2% | 12% | 30% | 34% | 18% | 4% | - |
13 | LAW Mila | - | - | 3% | 24% | 48% | 25% | |
14 | ZHONG Evelyn | - | - | 1% | 5% | 22% | 42% | 31% |
15 | JIANG Chenxi | - | - | 1% | 7% | 24% | 42% | 26% |
16 | MISHIMA Olivia | 1% | 10% | 27% | 34% | 21% | 6% | - |
17 | LEE Eden | - | - | - | 3% | 17% | 42% | 38% |
18 | FAN Joy | - | - | 1% | 10% | 32% | 40% | 17% |
19 | KAKANI Aditi | - | - | - | 5% | 37% | 58% | |
20 | DING Iris Siyue | - | 1% | 7% | 24% | 37% | 25% | 6% |
21 | MOKRETSOV Leah | - | - | 1% | 10% | 31% | 40% | 18% |
22 | ZHANG lindsay | - | - | 2% | 11% | 29% | 39% | 20% |
23 | SONKU Mira | - | 4% | 20% | 37% | 29% | 9% | 1% |
24 | KIM Abigail | - | 4% | 16% | 31% | 32% | 15% | 2% |
25 | TIAN Victoria | - | 1% | 6% | 22% | 37% | 27% | 7% |
26 | JU Jennifer | - | - | 4% | 24% | 53% | 19% | |
27 | ZHU Una | - | - | 2% | 12% | 34% | 39% | 13% |
28 | PEKKER Adel | - | 3% | 15% | 32% | 32% | 15% | 3% |
29 | JI Susan | - | - | 5% | 23% | 39% | 27% | 6% |
30 | TANG Jacquelyn | 2% | 13% | 36% | 39% | 11% | 1% | |
31 | GRUDZINSKI Josephine | 2% | 11% | 27% | 33% | 20% | 6% | 1% |
32 | YOUNG Penelope | 1% | 7% | 23% | 34% | 25% | 8% | 1% |
33 | HAN Emma | - | - | 3% | 13% | 31% | 36% | 17% |
34 | ZHANG Jane | - | - | 1% | 7% | 25% | 42% | 26% |
35 | ALLIEVI Simone | - | 1% | 8% | 25% | 36% | 23% | 5% |
36 | XIE ANDREA | - | - | 2% | 11% | 34% | 39% | 14% |
37 | ZHU YUNXI | - | 2% | 10% | 29% | 36% | 19% | 4% |
38 | RAJPUT Mahek | - | 1% | 7% | 24% | 39% | 26% | 3% |
39 | XU Mulan | - | - | 4% | 18% | 39% | 31% | 8% |
40 | QI Chelsie | - | 1% | 7% | 23% | 38% | 26% | 6% |
41 | LAI Juliet | 1% | 7% | 22% | 36% | 26% | 8% | 1% |
42 | PARKE Jaime | 4% | 20% | 35% | 29% | 11% | 2% | - |
43 | YOUN Emily | - | 1% | 10% | 28% | 37% | 20% | 4% |
44 | ZHANG Audrey A. | - | 1% | 6% | 21% | 38% | 30% | 5% |
45 | PEKKER Amina | - | 1% | 11% | 44% | 36% | 8% | |
46 | CHEN Laila | - | - | 3% | 15% | 34% | 35% | 12% |
47 | EDGAR Koko | - | 4% | 18% | 32% | 30% | 13% | 2% |
48 | SIU Mila | - | 1% | 8% | 31% | 38% | 19% | 3% |
49 | PATEL Agena | 2% | 15% | 32% | 32% | 16% | 4% | - |
50 | CHEN Reina | 1% | 5% | 20% | 35% | 29% | 9% | 1% |
50 | SAJJA Anwita | 4% | 22% | 36% | 27% | 10% | 2% | - |
52 | MEGGERS Arya | - | 2% | 13% | 32% | 34% | 16% | 3% |
53 | CHALLAMEL Heloise | 1% | 8% | 25% | 35% | 23% | 7% | 1% |
54 | YIN Elaine | 1% | 12% | 33% | 34% | 16% | 3% | - |
55 | ZHANG Flora | 8% | 27% | 35% | 22% | 7% | 1% | - |
56 | SHEN Sophia | 16% | 36% | 31% | 14% | 3% | - | - |
57 | OZALP Tara | 11% | 38% | 35% | 14% | 3% | - | - |
58 | KIM Charlotte | 1% | 7% | 27% | 40% | 21% | 5% | - |
59 | AINSWORTH Esme | 1% | 8% | 24% | 34% | 24% | 7% | 1% |
60 | CHANG Emma | 3% | 17% | 34% | 30% | 13% | 3% | - |
61 | GURTIN Sasha | 10% | 32% | 37% | 17% | 4% | - | - |
62 | MAO Faith | 6% | 24% | 37% | 25% | 8% | 1% | - |
63 | BONDE Trisha | 21% | 40% | 28% | 9% | 2% | - | - |
64 | REDWINE Louise | 9% | 32% | 37% | 18% | 4% | - | - |
65 | PATEL Aria | 1% | 8% | 27% | 36% | 22% | 6% | - |
66 | SELASSIE Semara | 7% | 32% | 40% | 18% | 3% | - | - |
67 | ZHAO Rachel | 1% | 8% | 25% | 36% | 24% | 6% | - |
68 | QIN Olivia | 26% | 40% | 25% | 8% | 1% | - | - |
68 | LIANG Kristy | 9% | 30% | 36% | 20% | 5% | 1% | - |
70 | WANG Jenny wang | 9% | 33% | 40% | 16% | 2% | - | |
71 | LIU Brinley | - | 3% | 14% | 32% | 33% | 15% | 3% |
72 | RICHARDS Seren | 1% | 11% | 30% | 36% | 18% | 4% | - |
73 | GORDON Winter | 16% | 36% | 31% | 13% | 3% | - | - |
74 | LIN Amber | 1% | 11% | 28% | 35% | 20% | 5% | - |
75 | DONE Kennedy | 2% | 19% | 45% | 27% | 7% | 1% | - |
75 | SHEN Zoey | 8% | 29% | 36% | 21% | 6% | 1% | - |
77 | LUO MAOSHUEN | 5% | 28% | 40% | 22% | 5% | - | - |
78 | CHOI Noah | 22% | 41% | 27% | 8% | 1% | - | - |
79 | CHEN Emily | 10% | 39% | 41% | 9% | 1% | - | |
80 | TAN Abriel | 18% | 42% | 32% | 8% | 1% | - | |
81 | YOON Michelle | 19% | 47% | 29% | 4% | - | - | |
82 | HUGHES Mackenzie | 38% | 45% | 15% | 1% | - | - | |
83 | SHERPURI Ananya | 4% | 20% | 34% | 28% | 11% | 2% | - |
84 | LI Kayla | 1% | 8% | 26% | 35% | 22% | 6% | 1% |
85 | WILLIAMS Valentina | 46% | 40% | 12% | 2% | - | - | - |
86 | ERATA Selena | 38% | 41% | 17% | 3% | - | - | - |
87 | WANG Katherine | 2% | 22% | 38% | 27% | 9% | 1% | - |
88 | KUO Stella | 4% | 21% | 36% | 27% | 10% | 2% | - |
89 | YUSHCHENKO Ivanka | 12% | 34% | 34% | 16% | 4% | - | - |
90 | LEE Iona | 2% | 12% | 30% | 34% | 18% | 4% | - |
91 | KAUR Harman | 34% | 49% | 15% | 1% | - | - | - |
92 | HALL Sophie | 1% | 8% | 24% | 35% | 24% | 7% | 1% |
93 | SUN Sarah | 1% | 8% | 25% | 36% | 24% | 6% | - |
94 | LI Juliana | 2% | 15% | 36% | 32% | 13% | 2% | - |
95 | ZHAO Ailsa | 9% | 32% | 36% | 18% | 4% | - | - |
96 | KIM Lina | 26% | 41% | 25% | 8% | 1% | - | - |
97 | KONG Shelby | 21% | 43% | 29% | 7% | 1% | - | - |
97 | SALUBRO Vivianna | 1% | 10% | 38% | 36% | 13% | 2% | - |
99 | CARACCIOLO Emma | 24% | 44% | 26% | 6% | - | - | |
100 | YU sage | 20% | 40% | 29% | 10% | 2% | - | - |
101 | ZHU Kaylee | 33% | 48% | 17% | 2% | - | - | - |
102 | LEE Celine | 47% | 40% | 11% | 1% | - | - | - |
103 | CHOI Serine | 71% | 26% | 3% | - | - | - | - |
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.