Gaylord National Resort and Convention Center - National Harbor, MD, 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 | ADYANTHAYA Anika | - | - | - | 1% | 11% | 41% | 47% |
2 | YANG Hannah | - | - | 4% | 18% | 42% | 36% | |
3 | LEE Kate | - | - | 1% | 9% | 27% | 40% | 22% |
3 | LEE Eden | - | - | 1% | 8% | 27% | 42% | 21% |
5 | OLELE Ifechi | - | - | - | 2% | 15% | 42% | 41% |
6 | DHAIYA Tanya | - | - | - | - | 6% | 31% | 63% |
7 | NING Miranda | - | - | - | 2% | 13% | 41% | 44% |
8 | ZHONG Evelyn | - | - | 1% | 6% | 25% | 43% | 25% |
9 | HE Anna | - | - | - | 1% | 9% | 38% | 52% |
10 | YU Chloe | - | - | 2% | 10% | 28% | 39% | 22% |
11 | CHEN Alina | - | - | 1% | 7% | 24% | 40% | 27% |
12 | ZHANG Jane | - | - | 2% | 11% | 33% | 41% | 14% |
13 | SUN Milly | - | 2% | 14% | 36% | 34% | 13% | 2% |
14 | CHEN Laila | - | - | 5% | 20% | 37% | 30% | 8% |
15 | BOBE Arianna | - | 1% | 5% | 20% | 37% | 30% | 7% |
16 | CHOI Arianna | - | - | 3% | 14% | 37% | 37% | 9% |
17 | LI Xier | - | - | 3% | 15% | 34% | 34% | 13% |
18 | FAN Joy | - | 3% | 17% | 37% | 34% | 10% | |
19 | CHEN Stephanie | - | 1% | 7% | 22% | 35% | 27% | 8% |
20 | CHI Zoe | - | - | - | 2% | 13% | 39% | 46% |
21 | FENG Esther | 1% | 9% | 25% | 35% | 23% | 7% | 1% |
22 | XU Aasta | 1% | 10% | 29% | 37% | 20% | 4% | |
23 | HALE Reagan | - | 4% | 19% | 36% | 30% | 9% | |
24 | CHEN Madeline | - | - | 2% | 13% | 35% | 38% | 11% |
25 | JU Jennifer | 1% | 5% | 18% | 32% | 29% | 13% | 2% |
26 | DIAZ Amber | - | 1% | 6% | 22% | 38% | 29% | 4% |
27 | LAW Mila | 1% | 7% | 21% | 33% | 26% | 10% | 1% |
28 | YAN Ximei (Alicia) | - | - | 2% | 12% | 31% | 37% | 17% |
29 | WANG Ailly | - | 4% | 17% | 33% | 31% | 13% | 2% |
30 | QI Chelsie | 1% | 8% | 27% | 37% | 23% | 5% | |
31 | ZHANG Ashley | - | 7% | 25% | 36% | 24% | 7% | 1% |
32 | RAJPUT Mahek | - | 3% | 16% | 33% | 32% | 14% | 2% |
33 | MOKRETSOV Leah | - | 3% | 14% | 34% | 35% | 14% | |
34 | LIN Alexis | - | - | 3% | 14% | 34% | 38% | 11% |
35 | KAKANI Aditi | - | 1% | 5% | 23% | 42% | 29% | |
36 | CHANG Hannah | 1% | 6% | 21% | 35% | 27% | 10% | 1% |
37 | HUFF Elizabeth | 2% | 11% | 29% | 34% | 19% | 5% | - |
38 | VILLER Alice | - | 1% | 7% | 23% | 37% | 26% | 7% |
39 | HAN Emma | 2% | 16% | 36% | 32% | 12% | 2% | - |
40 | MEGGERS Arya | 1% | 7% | 23% | 35% | 26% | 8% | 1% |
41 | TIAN Anika | 2% | 16% | 35% | 32% | 12% | 2% | - |
42 | ALLIEVI Simone | 1% | 7% | 25% | 40% | 23% | 4% | |
43 | HAGERMAN Siona | 1% | 9% | 28% | 37% | 21% | 4% | |
44 | KIM Abigail | 1% | 10% | 27% | 34% | 21% | 6% | 1% |
45 | JIANG Chenxi | - | 1% | 8% | 27% | 40% | 21% | 3% |
46 | YOUNG Penelope | 2% | 11% | 29% | 34% | 20% | 5% | - |
47 | CHEN Reina | 1% | 10% | 27% | 34% | 21% | 6% | 1% |
48 | ZHU YUNXI | 5% | 22% | 34% | 26% | 10% | 2% | - |
49 | JUBILEE Beata | 1% | 8% | 27% | 37% | 21% | 4% | - |
50 | KOUAME Candice | - | 2% | 12% | 29% | 35% | 19% | 4% |
51 | XIE ANDREA | - | 2% | 11% | 28% | 35% | 20% | 3% |
52 | MARKS Madeline | 1% | 7% | 22% | 35% | 26% | 9% | 1% |
53 | WANG Olivia | 1% | 6% | 24% | 37% | 25% | 6% | - |
54 | ZHANG Yuchen | 1% | 12% | 32% | 35% | 17% | 3% | |
55 | REN Harper | 6% | 28% | 40% | 21% | 4% | - | |
56 | TUMULA Anima | 40% | 41% | 16% | 3% | - | - | |
57 | WILSON Addison | 1% | 7% | 22% | 33% | 26% | 9% | 1% |
58 | GOPU Jyothirvida | 2% | 11% | 28% | 34% | 20% | 5% | - |
59 | GURTIN Aleksandra | 11% | 32% | 34% | 17% | 4% | - | - |
60 | LAI Juliet | 4% | 21% | 36% | 27% | 10% | 2% | - |
61 | NEGRUT Sabina | 22% | 42% | 28% | 7% | 1% | - | - |
62 | YANG Arianna | 4% | 22% | 38% | 27% | 8% | 1% | - |
63 | TRIVULCE Scarlett | 1% | 7% | 23% | 34% | 25% | 9% | 1% |
64 | ZHAO Rachel | 7% | 30% | 38% | 20% | 4% | - | - |
65 | AXELROD Charlotte | - | - | 1% | 7% | 28% | 47% | 17% |
66 | POTAPOVA Natalia | 1% | 7% | 23% | 35% | 26% | 8% | 1% |
67 | LI Yishi | 12% | 33% | 34% | 16% | 4% | - | - |
68 | LEE Iona | 1% | 7% | 23% | 36% | 25% | 7% | 1% |
69 | NIKOLLA Vivienne | 3% | 15% | 32% | 32% | 15% | 3% | - |
70 | KWON Allison | 31% | 42% | 21% | 5% | 1% | - | - |
71 | KWON Claire | 2% | 12% | 28% | 32% | 20% | 6% | 1% |
72 | LEE Zoe | 7% | 27% | 37% | 23% | 6% | 1% | - |
73 | FAN Olivia | 6% | 27% | 37% | 23% | 7% | 1% | - |
74 | PATEL Agena | 6% | 24% | 36% | 25% | 8% | 1% | - |
75 | ILYAS Daanya | 9% | 29% | 36% | 20% | 5% | 1% | - |
76 | LIU Emma | 13% | 34% | 33% | 15% | 3% | - | - |
77 | BUNCH Helena | 13% | 36% | 35% | 13% | 2% | - | - |
78 | ZHAO Crystal | 4% | 19% | 34% | 29% | 12% | 2% | - |
79 | MACAL Zoey | 1% | 14% | 34% | 33% | 15% | 3% | - |
80 | WANG Jenny | 3% | 15% | 31% | 31% | 16% | 4% | - |
81 | MAEDJE Abigail | 2% | 17% | 36% | 31% | 12% | 2% | |
82 | NISHANTH Krishvi | 35% | 43% | 19% | 4% | - | - | |
83 | BOUTSIKARIS Asha | 2% | 14% | 34% | 34% | 14% | 2% | |
84 | CHO Josephine | 23% | 40% | 27% | 9% | 1% | - | - |
85 | MAO Faith | 2% | 22% | 39% | 27% | 9% | 1% | - |
86 | ECCLESTONE Tara | 31% | 41% | 22% | 6% | 1% | - | - |
87 | PATEL Aria | 5% | 23% | 35% | 26% | 9% | 1% | - |
88 | TANG Sophie | 8% | 31% | 37% | 19% | 4% | - | - |
89 | YADAGIRI Aditi | 35% | 41% | 19% | 4% | - | - | - |
90 | LEWIN Isabelle | 7% | 25% | 35% | 24% | 8% | 1% | - |
91 | DONE Kennedy | 10% | 33% | 36% | 17% | 3% | - | - |
92 | KIM Kate | - | 2% | 14% | 36% | 38% | 9% | 1% |
93 | KIM Charlotte | 6% | 26% | 38% | 24% | 7% | 1% | |
94 | BIERL Elinor | 6% | 26% | 37% | 23% | 7% | 1% | |
95 | CHOI Noah | 62% | 32% | 6% | 1% | - | - | |
96 | MOON Leah | 13% | 37% | 34% | 14% | 3% | - | - |
97 | BONTHAPALLY Maitreyee S. | 38% | 42% | 17% | 3% | - | - | - |
97 | WEBB Ensley | 1% | 12% | 33% | 35% | 16% | 3% | - |
99 | CHONG Emma | 14% | 33% | 32% | 16% | 4% | 1% | - |
100 | YOON Michelle | 30% | 42% | 22% | 5% | 1% | - | - |
101 | LOPATINA Anastasiia | 8% | 28% | 37% | 21% | 5% | 1% | - |
102 | YAO Astrid | 73% | 24% | 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.