National Harbor, MD - 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 | XIAO Ruien | - | - | - | 1% | 11% | 41% | 47% |
2 | YIN Julia | - | - | - | 2% | 13% | 40% | 45% |
3 | HAFEEZ Hiba | - | - | 3% | 21% | 45% | 31% | |
3 | ZHANG Victoria R. | - | - | 1% | 9% | 31% | 42% | 17% |
5 | MUELLER Emma M. | - | 4% | 18% | 36% | 32% | 10% | |
6 | ZIGALO Elizabeth | - | - | 1% | 10% | 37% | 51% | |
7 | RANDLEMAN Teresa | - | - | 1% | 8% | 32% | 44% | 15% |
8 | YANG Alisa | - | 1% | 8% | 26% | 41% | 24% | |
9 | GAJJALA Sharika R. | - | - | - | 3% | 15% | 41% | 41% |
10 | SWENSON Nikita G. | - | 1% | 9% | 30% | 44% | 16% | |
11 | HAFEEZ Hania | - | - | 6% | 24% | 39% | 26% | 6% |
12 | LEACH Meka A. | - | - | - | 2% | 13% | 39% | 46% |
13 | FAN Elizabeth | - | 4% | 19% | 38% | 32% | 7% | |
14 | SU Evelyn | - | - | 5% | 23% | 38% | 27% | 6% |
15 | YOU Emily | - | 2% | 16% | 42% | 32% | 8% | 1% |
16 | IVY Zhao | 1% | 9% | 27% | 36% | 22% | 5% | |
17 | AZMEH nour | - | 5% | 21% | 36% | 28% | 9% | 1% |
18 | KORFONTA Jolie | - | 2% | 11% | 30% | 36% | 19% | 3% |
19 | BARCLAY Khyri | 1% | 9% | 27% | 36% | 22% | 5% | |
20 | FURMAN Maria | - | 2% | 14% | 37% | 36% | 11% | |
21 | WATTANAKIT Anda | - | 2% | 12% | 31% | 35% | 18% | 3% |
22 | AGAON Evelyn | - | 4% | 16% | 33% | 32% | 13% | 2% |
23 | BECKMAN Ana | 4% | 23% | 39% | 27% | 7% | 1% | |
24 | JAKEL Alysa C. | 4% | 22% | 37% | 28% | 8% | 1% | |
25 | LIU Nicole | 5% | 22% | 36% | 27% | 9% | 1% | |
26 | FERREIRA DE MELO Adriana | 2% | 13% | 32% | 34% | 16% | 3% | |
27 | CANNING Charlotte | 1% | 7% | 24% | 36% | 24% | 7% | 1% |
28 | CHISHOLM Phoebe C. | - | - | 5% | 27% | 43% | 22% | 3% |
29 | QIU Emily | - | 2% | 13% | 32% | 35% | 16% | 2% |
30 | ZHU Serene M. | 3% | 17% | 35% | 31% | 12% | 2% | |
31 | TOLSMA Chloe | - | 1% | 10% | 35% | 40% | 14% | |
32 | CAFASSO Natalya | 1% | 14% | 34% | 33% | 15% | 3% | - |
33 | WITTER Catherine A. | - | 4% | 16% | 33% | 32% | 13% | 2% |
34 | RAKHOVSKI Alexandra | - | - | 3% | 16% | 43% | 38% | |
35 | NGUYEN Ashley L. | 26% | 43% | 24% | 5% | 1% | - | |
36 | LEE Olivia | 4% | 20% | 36% | 28% | 10% | 1% | |
37 | HAYNES Antonia | 4% | 25% | 43% | 23% | 5% | 1% | - |
38 | LEE Scarlett | - | - | 3% | 17% | 37% | 34% | 8% |
39 | LUO Amy | - | 1% | 8% | 25% | 37% | 23% | 4% |
40 | SMUK Alexandra S. | 6% | 25% | 38% | 24% | 6% | - | |
41 | YAO Melinda | - | 2% | 10% | 29% | 39% | 19% | |
42 | RAJU Laya | 14% | 35% | 33% | 15% | 3% | - | |
43 | WONG Caitlin | 4% | 23% | 39% | 27% | 7% | 1% | |
44 | SHIN Jihyo | 35% | 42% | 19% | 4% | - | - | - |
45 | PINNAMANENI Drithi | 14% | 35% | 33% | 14% | 3% | - | - |
46 | NIKOLIC DE JACINTO Alix P. | 6% | 29% | 43% | 19% | 3% | - | - |
47 | PULLEN Ayah | 5% | 29% | 39% | 21% | 5% | 1% | - |
48 | MISHIMA Audrey | 8% | 31% | 36% | 19% | 5% | 1% | - |
49 | LEE Camilla | 1% | 11% | 30% | 34% | 18% | 4% | - |
50 | JONES Charlotte | 16% | 42% | 33% | 8% | 1% | - | |
51 | YOU Isabel B. | 6% | 26% | 38% | 24% | 6% | - | |
52 | HOAGLAND Sally | 41% | 41% | 15% | 2% | - | - | |
53 | LEE Claire | 9% | 31% | 36% | 19% | 4% | - | |
54 | TOSH Audrey | 32% | 48% | 17% | 2% | - | - | - |
55 | GUAN Isabella | 10% | 34% | 38% | 16% | 3% | - | - |
56 | KOZAREZ Brooklyn O. | - | < 1% | 4% | 19% | 37% | 31% | 9% |
57 | FORBES Sophia | 25% | 45% | 25% | 5% | - | - | - |
58 | RUFFNER Taylor | 38% | 44% | 16% | 2% | - | - | - |
59 | CUEVA Viola | 4% | 21% | 39% | 28% | 7% | 1% | |
60 | NIX Reagan | 22% | 41% | 28% | 8% | 1% | - | |
60 | JUN Bomie | 38% | 41% | 17% | 3% | - | - | |
62 | YANG Han Yue | 65% | 30% | 5% | - | - | - | - |
63 | RUFFNER Elin | 11% | 36% | 38% | 13% | 2% | - | |
64 | KIRKELL Mia | 13% | 35% | 34% | 15% | 3% | - | - |
65 | NGUYEN Ella | 19% | 49% | 27% | 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.