Charlotte, NC, 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 | NGUYEN Kira | - | 1% | 7% | 26% | 42% | 25% | |
2 | NEMETH Katherine | - | - | 4% | 15% | 32% | 34% | 15% |
3 | WALLER Sarah I. | - | - | 3% | 20% | 39% | 31% | 7% |
3 | LEUNG Wan Kiu Hayley | - | 1% | 10% | 28% | 36% | 21% | 4% |
5 | FAN Yun Cian | - | - | - | 4% | 18% | 41% | 36% |
6 | WONG Alexandra R. | - | 5% | 18% | 34% | 31% | 11% | |
7 | LU Shiqi | - | - | - | 4% | 20% | 43% | 32% |
8 | PRIHODKO Nina | - | 4% | 22% | 38% | 27% | 8% | 1% |
9 | REMEZA Alissa | - | 1% | 7% | 24% | 42% | 27% | |
10 | GAO Judy | - | - | 2% | 15% | 36% | 35% | 12% |
11 | LI Alisha | - | - | 5% | 23% | 41% | 26% | 5% |
12 | HICKS Grace | 1% | 7% | 22% | 33% | 26% | 10% | 1% |
13 | CHIRASHNYA Noya | - | 7% | 26% | 36% | 23% | 7% | 1% |
14 | LIN Elaine | - | - | 1% | 10% | 31% | 40% | 18% |
15 | HUANG Lanlan | 1% | 5% | 16% | 30% | 30% | 15% | 3% |
16 | SMUK Daria A. | 1% | 9% | 28% | 37% | 21% | 4% | |
17 | LEE yat ching | - | - | 3% | 14% | 33% | 36% | 14% |
18 | MCSHINE Katelyn H. | - | - | 1% | 11% | 34% | 40% | 14% |
19 | LIN Ashley | 1% | 8% | 23% | 32% | 25% | 10% | 2% |
20 | FAN Elizabeth | 2% | 15% | 35% | 33% | 13% | 2% | |
21 | EDWARDS Auprell | - | - | - | 3% | 17% | 44% | 36% |
22 | MYERS Jeanelle Christina A. | - | - | 2% | 11% | 29% | 38% | 19% |
23 | ANDERSON Claire | - | 2% | 9% | 25% | 35% | 23% | 6% |
24 | DENG Annie | 14% | 37% | 33% | 13% | 2% | - | |
25 | PINNAMANENI Drithi | 1% | 10% | 28% | 36% | 21% | 4% | |
26 | NGUYEN Audrey | - | 1% | 5% | 20% | 36% | 29% | 9% |
27 | ZHU Serene M. | - | 1% | 11% | 31% | 36% | 17% | 3% |
28 | ZENG Katrina | 1% | 8% | 26% | 35% | 22% | 7% | 1% |
29 | WITTER Catherine A. | - | 2% | 11% | 30% | 38% | 19% | |
30 | SONG Angela | 4% | 20% | 34% | 28% | 11% | 2% | |
31 | HONG Elaine | - | 5% | 20% | 36% | 30% | 9% | |
32 | PEELER Julia | - | - | 3% | 15% | 34% | 35% | 13% |
33 | XUAN Nicole J. | - | - | - | 2% | 13% | 40% | 45% |
34 | AHUJA Arianna | - | - | 3% | 15% | 36% | 35% | 11% |
35 | LEE Olivia | 1% | 9% | 27% | 36% | 22% | 5% | |
36 | GUJJA Misha | - | 2% | 9% | 25% | 34% | 24% | 6% |
37 | PARK Judy | - | 10% | 30% | 35% | 19% | 5% | - |
38 | YAO KATHARINE | - | - | 6% | 27% | 40% | 22% | 4% |
39 | LONADIER Keira | - | - | 3% | 14% | 32% | 36% | 15% |
40 | SHU Youshan | - | 2% | 10% | 26% | 35% | 22% | 5% |
41 | KELLY Jenna | 1% | 7% | 24% | 35% | 24% | 8% | 1% |
42 | HAWKINS Laura A. | - | - | 6% | 26% | 39% | 24% | 5% |
43 | BUSH emma | - | - | 4% | 22% | 39% | 28% | 7% |
43 | LI Fei | 1% | 6% | 24% | 36% | 25% | 8% | 1% |
45 | NGUYEN Ashley L. | 24% | 43% | 26% | 7% | 1% | - | |
46 | SOTELO Michelle | 11% | 32% | 35% | 17% | 4% | - | |
47 | PEARSON Heila | 1% | 6% | 21% | 35% | 28% | 9% | |
48 | KIZILBASH Zara | 1% | 8% | 28% | 38% | 21% | 4% | |
49 | JOHN Venus | 8% | 35% | 36% | 16% | 4% | - | - |
50 | ABRAMSON Mariela R. | - | 1% | 26% | 42% | 25% | 6% | - |
51 | AI Amy | - | 8% | 26% | 35% | 23% | 7% | 1% |
52 | LEE Yedda | - | 1% | 6% | 20% | 35% | 29% | 9% |
53 | ZHANG ANGELA | 3% | 22% | 36% | 27% | 10% | 2% | - |
54 | HSIU Elizabeth | 1% | 7% | 24% | 35% | 24% | 8% | 1% |
55 | ANDERSON Nora E. | - | 2% | 12% | 29% | 34% | 18% | 4% |
56 | ENRILE Erica | - | 4% | 22% | 40% | 26% | 6% | 1% |
57 | RHEINECKER Claire | 21% | 55% | 21% | 3% | - | - | - |
58 | SPURLIN Alicen | - | 5% | 21% | 37% | 29% | 8% | |
59 | SHARMA Sanvi | 2% | 13% | 32% | 35% | 16% | 3% | |
60 | OLORVIDA Isabella | 2% | 15% | 34% | 32% | 14% | 3% | - |
61 | WANG Esther | 6% | 24% | 35% | 24% | 9% | 1% | - |
62 | ALEXANDER Amelia | 10% | 30% | 35% | 20% | 5% | 1% | |
63 | KUMAR Anusha | 23% | 40% | 27% | 9% | 1% | - | |
64 | TAYLOR-CASAMAYOR Maia | - | 4% | 19% | 35% | 30% | 11% | 1% |
65 | AZMEH nour | - | 3% | 13% | 29% | 33% | 18% | 4% |
66 | XIONG Angelica | 2% | 10% | 26% | 32% | 22% | 7% | 1% |
67 | DU Shunyi(Wendy) | - | 5% | 25% | 38% | 25% | 7% | 1% |
68 | ZANGA Kaitlyn | 6% | 24% | 34% | 24% | 9% | 2% | - |
69 | ZHEREBCHEVSKA Veronika | - | - | 3% | 14% | 32% | 35% | 15% |
70 | MALLAVARPU Aarthi C. | - | 1% | 7% | 27% | 42% | 23% | |
71 | RAKHOVSKI Alexandra | - | 2% | 12% | 32% | 38% | 15% | |
72 | SINHA Zara | 4% | 19% | 36% | 29% | 11% | 1% | |
72 | KANEVSKY Samantha | 7% | 28% | 37% | 22% | 6% | 1% | |
74 | ZHAO Ivy | 8% | 27% | 35% | 23% | 7% | 1% | |
75 | UNGURIANU Nika | 8% | 28% | 35% | 21% | 7% | 1% | - |
76 | COURTNEY Elya Rebekah | 1% | 10% | 26% | 33% | 22% | 7% | 1% |
77 | BYBEE Lucy J. | - | 1% | 15% | 39% | 33% | 11% | 1% |
78 | PEARSON Arwa | 14% | 38% | 33% | 13% | 2% | - | - |
79 | XIE Fiona | 3% | 20% | 41% | 28% | 8% | 1% | - |
80 | MOON Seojung | 2% | 13% | 30% | 33% | 17% | 3% | |
81 | WILKENS Patricia A. | 14% | 35% | 33% | 15% | 3% | - | |
82 | DONG Ava | 1% | 9% | 26% | 36% | 23% | 5% | |
83 | SANDERS Charlotte | 26% | 42% | 24% | 6% | 1% | - | |
84 | CHENG Katherine | 6% | 24% | 35% | 24% | 9% | 1% | - |
85 | DONGES Anna | 1% | 15% | 45% | 30% | 8% | 1% | - |
86 | GOLART Alexis A. | 11% | 30% | 34% | 19% | 5% | 1% | - |
87 | BA Sujuan | 12% | 45% | 34% | 9% | 1% | - | - |
88 | SHERTZ Kira E. | 1% | 8% | 24% | 33% | 24% | 9% | 1% |
89 | NOH Rachel | 55% | 38% | 7% | - | - | - | - |
90 | JACKSON Viktoria | 13% | 48% | 30% | 8% | 1% | - | - |
91 | GORTI Ramya | 19% | 71% | 9% | - | - | - | - |
92 | PULLEN Ayah | 6% | 24% | 36% | 25% | 8% | 1% | |
93 | NEELAM Neha | 22% | 43% | 27% | 7% | 1% | - | |
94 | STECKMEISTER Evelyn | 52% | 38% | 9% | 1% | - | - | - |
95 | DAVIS Elisabeth | 65% | 31% | 4% | - | - | - | - |
96 | MIHILL Margaret | 56% | 35% | 8% | 1% | - | - | - |
96 | RHEINECKER Eleanora Grace | 33% | 43% | 20% | 4% | - | - | - |
98 | GOSART Hailee | 88% | 12% | 1% | - | - | - | - |
99 | MAY Courtney | 26% | 40% | 25% | 8% | 1% | - | - |
100 | BURDOO Nora | 77% | 23% | - | - | - | - | - |
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.