Santa Clara Convention Center - Santa Clara, 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 | KOZLOWSKI Maya M. | - | - | - | - | 1% | 14% | 85% |
2 | MCCLURE Samar | - | 1% | 6% | 21% | 37% | 29% | 5% |
3 | LIN Ariel | - | - | - | 3% | 15% | 41% | 41% |
3 | XU Serena | - | - | - | 1% | 9% | 36% | 54% |
5 | CARRIER Meredith | - | - | - | - | 3% | 25% | 71% |
6 | BEAVER Ava | - | - | - | 3% | 32% | 65% | |
7 | ABUELFUTUH Sama | - | - | - | 1% | 12% | 42% | 44% |
8 | MOLLINIER Angel | - | - | 2% | 12% | 34% | 40% | 12% |
9 | WANG Jessie | - | - | - | 1% | 10% | 36% | 53% |
9 | HABEK Sophia | - | - | - | 1% | 13% | 49% | 37% |
11 | XU Chenyu | - | 2% | 14% | 34% | 35% | 14% | 1% |
12 | NGUYEN Renee | - | 2% | 11% | 30% | 38% | 18% | 1% |
13 | CHEN Stephanie | - | 1% | 9% | 34% | 44% | 12% | |
14 | SALAZAR Emma | 1% | 10% | 29% | 35% | 20% | 5% | - |
15 | WANG Ziqiao (Claire) | - | 1% | 6% | 22% | 41% | 30% | |
16 | BLANCO Ariia | - | 4% | 18% | 36% | 32% | 10% | |
17 | CAMAMA Tessa | - | - | - | 2% | 14% | 48% | 36% |
18 | BURICEA Ada | - | - | 1% | 6% | 29% | 46% | 18% |
19 | WANG Victoria | - | - | - | 1% | 11% | 40% | 47% |
20 | BUCA Nora | - | 2% | 14% | 36% | 37% | 10% | 1% |
21 | KANE Chloe | - | 1% | 8% | 25% | 37% | 23% | 5% |
22 | WU Jessica | - | 4% | 17% | 36% | 33% | 10% | |
23 | LEE Valerie | - | 6% | 24% | 38% | 25% | 6% | - |
24 | LI Yunxuan (Joy) | - | 1% | 8% | 25% | 39% | 23% | 4% |
25 | WANG Aria | - | 1% | 9% | 27% | 37% | 22% | 4% |
26 | SCHOR Elisabeth | - | 2% | 12% | 29% | 35% | 18% | 2% |
27 | HE Anna | 1% | 9% | 28% | 37% | 21% | 4% | |
28 | CHIOU-WILLIAMS Matea | 2% | 15% | 34% | 33% | 14% | 2% | |
29 | KANDALA Aanya | 4% | 19% | 35% | 30% | 12% | 2% | |
29 | YUNG Bethany | 2% | 15% | 34% | 33% | 14% | 2% | |
31 | HANKINS Morgan | - | 1% | 6% | 23% | 42% | 28% | |
32 | XU Jessica | - | 2% | 13% | 33% | 36% | 15% | 1% |
33 | WANG Zoe | - | - | - | 1% | 6% | 32% | 61% |
34 | GUAN Isabella | - | - | - | 2% | 15% | 42% | 41% |
35 | MYRAH Vivienne | - | - | 1% | 5% | 21% | 42% | 32% |
36 | PEI Claire | 1% | 12% | 33% | 35% | 16% | 3% | |
37 | DYMAR Anna | 2% | 14% | 32% | 33% | 16% | 3% | |
38 | LEE Emily | - | - | 4% | 22% | 45% | 24% | 4% |
39 | DWIGGINS Reese | - | 3% | 18% | 36% | 31% | 11% | 1% |
40 | LEE Adelynn | 1% | 12% | 36% | 36% | 13% | 2% | - |
41 | ZHAO Emma | - | 2% | 13% | 31% | 34% | 17% | 3% |
42 | LIN Isabel | - | 1% | 5% | 19% | 37% | 31% | 8% |
43 | AIRES Julia | - | 1% | 7% | 26% | 42% | 25% | |
44 | LEE Kaitlyn | 11% | 32% | 35% | 18% | 4% | - | |
45 | JAQUISH Zoey | 1% | 14% | 42% | 34% | 8% | - | |
46 | CAYETANO Audrey | 1% | 6% | 22% | 35% | 27% | 9% | 1% |
46 | ZHAO Yanning | 2% | 11% | 29% | 35% | 19% | 5% | - |
48 | YAN Ximei (Alicia) | 3% | 19% | 38% | 30% | 9% | 1% | - |
49 | YOUSSEF Caroline | - | 5% | 20% | 36% | 30% | 9% | - |
50 | RIVERA MEZA Azul | - | - | 4% | 18% | 37% | 31% | 9% |
51 | LEE Emma | 11% | 31% | 35% | 19% | 5% | 1% | - |
52 | CHEN Julia Z. | 1% | 9% | 28% | 36% | 21% | 5% | - |
53 | GAN Shelby | 2% | 12% | 30% | 34% | 18% | 4% | - |
54 | RADOV Una | 10% | 33% | 36% | 17% | 4% | - | |
55 | HOLDEN Helena | 1% | 7% | 22% | 35% | 26% | 8% | - |
55 | MERRIMAN Rie | 7% | 31% | 38% | 19% | 5% | - | - |
57 | SCANLAN Alina Nev | 3% | 18% | 35% | 30% | 12% | 2% | - |
58 | KELMAN Nora | 9% | 29% | 36% | 20% | 5% | 1% | - |
59 | CHI Zoe | - | 4% | 20% | 36% | 29% | 10% | 1% |
60 | RICHARDSON Gianna | 1% | 10% | 28% | 36% | 21% | 4% | |
61 | SIMHADRI Sanjana | 11% | 32% | 35% | 18% | 4% | - | |
62 | EYUNNI Vibha | 9% | 35% | 37% | 16% | 3% | - | |
63 | GARINEY tanvi | 7% | 27% | 37% | 22% | 6% | 1% | - |
64 | MADANNAVAR Trisha | 5% | 20% | 34% | 28% | 11% | 2% | - |
65 | LI Chloe | 6% | 25% | 37% | 24% | 7% | 1% | - |
66 | SHERMAN Olivia | 1% | 10% | 27% | 35% | 22% | 6% | - |
67 | SUN Zhanwen | 4% | 19% | 34% | 29% | 12% | 2% | - |
68 | ZHU Riley | - | 3% | 15% | 33% | 32% | 14% | 2% |
69 | FISCHBEIN Quinley | - | 1% | 7% | 24% | 38% | 26% | 4% |
70 | LI Carlie | 4% | 21% | 36% | 28% | 10% | 2% | - |
71 | SUN Karolyn | - | 8% | 34% | 43% | 14% | 1% | |
72 | ZHANG Rose | 41% | 41% | 15% | 2% | - | - | |
73 | BUDMAN Ava | 2% | 15% | 32% | 32% | 15% | 3% | - |
74 | JAIN Prisha | 3% | 19% | 40% | 30% | 8% | 1% | - |
75 | REED Katya | 3% | 22% | 39% | 27% | 8% | 1% | - |
76 | WIMERT Dahlia | 17% | 38% | 31% | 12% | 2% | - | - |
77 | PATTERSON Liliya | 1% | 6% | 24% | 37% | 25% | 6% | - |
78 | TESLENKO Ekaterina | - | 6% | 26% | 38% | 23% | 6% | - |
79 | DENEALE Lucia | 1% | 11% | 30% | 35% | 18% | 4% | - |
79 | ARULKUMAR Lashia | 10% | 30% | 35% | 19% | 5% | 1% | - |
81 | TEACHWORTH Samantha | 7% | 25% | 36% | 24% | 7% | 1% | - |
82 | RAPTIS Layla | 20% | 42% | 29% | 8% | 1% | - | - |
83 | DING Calista | 2% | 15% | 37% | 35% | 11% | 1% | - |
84 | BURKS Madison | 3% | 17% | 36% | 32% | 11% | 1% | - |
85 | TISHKOVA-ROBERTS Daria | 25% | 41% | 26% | 7% | 1% | - | |
86 | LEE Grace | 10% | 46% | 35% | 9% | 1% | - | |
87 | GIERAT-KATZ Izabella | 4% | 22% | 36% | 27% | 9% | 1% | - |
88 | ZU Jacqueline | 37% | 42% | 18% | 3% | - | - | - |
89 | MAI Blair | 28% | 46% | 22% | 4% | - | - | - |
90 | REN Ivanka | 11% | 36% | 35% | 15% | 3% | - | - |
90 | YU Xintong | 18% | 38% | 30% | 11% | 2% | - | - |
92 | ALI Zoya | 14% | 39% | 34% | 12% | 2% | - | - |
92 | LINARES Olivia | 35% | 42% | 19% | 4% | - | - | - |
94 | SIDDABATHUNI ananya | 42% | 44% | 12% | 2% | - | - | - |
95 | MIXON Ivory | 22% | 46% | 26% | 6% | 1% | - | - |
96 | PADHI Nisha | 10% | 33% | 36% | 17% | 4% | - | - |
97 | PIOVESAN Rachel | 41% | 40% | 15% | 3% | - | - | - |
98 | UEMURA Lyllia | 26% | 43% | 24% | 6% | - | - | - |
99 | WANG Ailly | 66% | 30% | 4% | - | - | - | |
100 | RIVERA Natalie | 3% | 22% | 37% | 27% | 10% | 2% | - |
101 | YOON Claire | 58% | 34% | 7% | 1% | - | - | - |
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.