Ontario Convention Center - Ontario, CA, 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 | WANG Victoria | - | - | 1% | 7% | 35% | 57% | |
2 | WANG Jessie | - | - | - | 4% | 24% | 51% | 20% |
3 | HABEK Sophia | - | - | - | 2% | 11% | 39% | 48% |
3 | HANKINS Morgan | - | - | - | - | 2% | 19% | 79% |
5 | WU Jessica | - | - | - | 2% | 14% | 40% | 44% |
6 | FU Shannon | - | - | 2% | 12% | 35% | 40% | 11% |
7 | HE Anna | - | - | 3% | 25% | 72% | ||
8 | XU Amy(Chenyu) | - | 2% | 15% | 38% | 35% | 11% | |
9 | FISCHBEIN Quinley | - | - | 13% | 40% | 37% | 10% | |
10 | PACHECO Carys | - | 1% | 10% | 33% | 40% | 16% | |
11 | SUN Karolyn | - | 2% | 12% | 37% | 40% | 9% | |
12 | WONG Sydney | - | - | 1% | 8% | 27% | 41% | 22% |
13 | LIN Laura | - | - | 2% | 11% | 32% | 39% | 17% |
14 | RADOV Una | - | 4% | 40% | 40% | 13% | 1% | |
15 | CHO Anya | 1% | 11% | 34% | 37% | 15% | 2% | |
16 | XIONG Alice | 3% | 18% | 39% | 31% | 9% | 1% | |
17 | BUCA Nora | - | 5% | 20% | 37% | 29% | 8% | |
18 | VIJAY Vaishnavi | - | 3% | 14% | 32% | 34% | 15% | 2% |
19 | WANG Lihong | - | - | 2% | 12% | 33% | 40% | 13% |
20 | DU Chloe | - | 4% | 16% | 32% | 33% | 14% | 1% |
21 | CIOBANU Celine | - | 7% | 31% | 39% | 20% | 3% | |
22 | LI Yunxuan (Joy) | - | 1% | 8% | 26% | 36% | 23% | 5% |
23 | LIN Isabel | - | - | 1% | 6% | 23% | 43% | 28% |
24 | LU Chloe | 3% | 17% | 34% | 31% | 13% | 2% | - |
25 | DWIGGINS Reese | - | - | 3% | 13% | 32% | 37% | 15% |
26 | KUTSY Olga | - | - | 11% | 39% | 39% | 11% | |
26 | WANG Chantal | - | 3% | 21% | 39% | 29% | 7% | |
28 | ARULKUMAR Lashia | 1% | 7% | 25% | 37% | 24% | 6% | |
29 | ZHAO Emma | - | - | 3% | 14% | 34% | 37% | 13% |
30 | WANG Ailly | 1% | 6% | 22% | 36% | 26% | 8% | 1% |
31 | CHIOU-WILLIAMS Matea | - | 3% | 13% | 30% | 34% | 18% | 3% |
32 | MAENG Gloria | 8% | 28% | 35% | 22% | 6% | 1% | - |
33 | LIN Ariel | - | - | - | 1% | 11% | 40% | 47% |
34 | ROBLES Claudia | - | 1% | 6% | 24% | 38% | 25% | 6% |
35 | CHEN Julia Z. | - | 2% | 13% | 31% | 35% | 16% | 2% |
36 | ZHAO Ellie | 1% | 10% | 28% | 35% | 20% | 5% | - |
37 | MANDAP Alessandra | - | 2% | 14% | 36% | 36% | 12% | |
38 | SHERMAN Olivia | - | 4% | 18% | 36% | 32% | 10% | |
39 | WANG Nicole | - | 5% | 27% | 40% | 23% | 5% | |
40 | ARNOLD Evangeline | 2% | 15% | 40% | 38% | 6% | ||
41 | ERISMAN Gabriella | 2% | 16% | 34% | 32% | 14% | 3% | - |
42 | DENEALE Lucia | - | 5% | 22% | 37% | 27% | 8% | 1% |
43 | LI Anna | - | 1% | 10% | 30% | 37% | 19% | 4% |
44 | KOU Cynthia | - | 1% | 9% | 27% | 37% | 22% | 3% |
45 | YOON Claire | 17% | 42% | 31% | 9% | 1% | - | |
46 | HAN Sydney | 1% | 8% | 25% | 35% | 24% | 7% | 1% |
47 | VOO Evelyn | 6% | 24% | 35% | 24% | 8% | 1% | - |
48 | DAI Sophie | 38% | 43% | 16% | 3% | - | - | |
49 | LIAO irene | - | 1% | 6% | 20% | 36% | 29% | 7% |
50 | MOHAN Riya | - | - | 2% | 14% | 34% | 36% | 13% |
51 | KOHLER Chrissy | 8% | 31% | 37% | 19% | 5% | 1% | - |
52 | YIP Allison | - | 4% | 17% | 33% | 32% | 12% | 1% |
53 | BUDMAN Ava | - | 3% | 15% | 33% | 32% | 14% | 2% |
54 | WANG Olivia | 3% | 16% | 32% | 31% | 15% | 3% | - |
55 | YUNG Bethany | - | 1% | 8% | 28% | 42% | 21% | |
57 | HAN Yuchen | - | - | 2% | 15% | 43% | 40% | |
58 | GUO Elena | - | 2% | 11% | 26% | 33% | 22% | 6% |
59 | LE Luana | 6% | 30% | 38% | 20% | 5% | - | - |
60 | LEE Kaitlyn | 1% | 8% | 27% | 37% | 22% | 5% | - |
61 | THOMAS Mackenzie | 28% | 50% | 20% | 3% | - | - | |
62 | XU Aasta | 5% | 27% | 42% | 22% | 4% | - | |
63 | LI Wan-Tao | 4% | 19% | 34% | 29% | 12% | 2% | - |
65 | TIEN Shaylin | 1% | 7% | 28% | 41% | 20% | 2% | |
66 | LEONG Andrea | 13% | 39% | 36% | 11% | 1% | ||
67 | GAN Shelby | - | 1% | 10% | 32% | 42% | 14% | |
68 | KIM Vivian | - | 4% | 19% | 36% | 30% | 10% | 1% |
69 | DEKERMANJI kate | 12% | 33% | 34% | 16% | 4% | - | - |
70 | LI Carlie | 7% | 25% | 35% | 24% | 8% | 1% | - |
71 | LEE Adelynn | 1% | 7% | 23% | 35% | 26% | 8% | 1% |
72 | GARCIA Sophia Noelle | 10% | 31% | 35% | 19% | 5% | 1% | - |
73 | GIERAT-KATZ Izabella | - | - | 2% | 14% | 42% | 43% | |
74 | UEMURA Lyllia | 19% | 52% | 24% | 4% | - | - | |
75 | LEE Yeriel | - | 1% | 11% | 34% | 39% | 15% | |
76 | LI Mia | 16% | 47% | 29% | 7% | 1% | - | - |
77 | LI Allison | 7% | 27% | 36% | 22% | 7% | 1% | - |
78 | STEPHAN Ella Whitney | 2% | 13% | 32% | 34% | 16% | 3% | - |
79 | SCANLAN Alina Nev | 1% | 10% | 30% | 36% | 19% | 4% | - |
80 | LICHTENFELD Naomi | 2% | 18% | 36% | 30% | 12% | 2% | - |
81 | DEJOY Leilah | 16% | 36% | 32% | 13% | 3% | - | - |
82 | DYMAR Anna | - | 4% | 18% | 36% | 32% | 11% | |
83 | FLYNN Kensington | 20% | 42% | 28% | 8% | 1% | - | |
84 | YIN Angelina | 21% | 43% | 29% | 6% | - | ||
85 | BEATINGO Chelli | 39% | 54% | 6% | - | - | - | |
86 | PARKE Jaime | 43% | 45% | 11% | 1% | - | - | |
87 | SUN Joanna | 27% | 44% | 23% | 5% | 1% | - | |
88 | HATHAWAY Alesya | 2% | 13% | 32% | 34% | 16% | 3% | - |
89 | ZU Jacqueline | 7% | 25% | 35% | 24% | 8% | 1% | - |
90 | ZHAO Yanning | - | 4% | 17% | 32% | 31% | 13% | 2% |
91 | CHAE Avery | 21% | 41% | 28% | 9% | 1% | - | - |
92 | XIE Yuyan | 2% | 18% | 42% | 28% | 8% | 1% | - |
93 | MUKKU Emily | 14% | 36% | 34% | 14% | 3% | - | - |
94 | AGARWAL Keya | 22% | 40% | 27% | 9% | 1% | - | - |
95 | MIAO Anthea | 4% | 22% | 37% | 26% | 8% | 1% | - |
96 | GRAZIANO Josephine | 32% | 42% | 20% | 5% | - | - | - |
96 | VINLUAN Emma | 1% | 5% | 17% | 30% | 30% | 15% | 3% |
98 | LUCENA Yaretzi | 12% | 40% | 35% | 11% | 1% | - | |
99 | TRUONG Chloe | 55% | 38% | 6% | - | - | - | |
100 | REN Ivanka | 17% | 42% | 33% | 8% | - | ||
101 | PARK Rachel | 32% | 44% | 20% | 4% | - | - | |
102 | TANG Zixin | 53% | 37% | 9% | 1% | - | - | - |
103 | CHU Brianna | 54% | 36% | 9% | 1% | - | - | - |
104 | CHAI Serena | 52% | 45% | 3% | - | - | - | |
105 | TAI AMANDA | 2% | 17% | 38% | 31% | 10% | 1% | - |
106 | LI Jennifer | 44% | 41% | 13% | 2% | - | - | - |
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.