Capitol Clash SYC & RCC with Non-Regional Veteran and Y8

Y-14 Women's Épée

Saturday, February 2, 2019 at 8:00 AM

National Harbor, MD - National Harbor, MD, USA

Probability density of pool victories

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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 JOYCE Michaela - - - - 3% 24% 73%
2 WATRALL Christina - - - - 5% 31% 64%
3 TYLER Syd - - 1% 5% 23% 44% 27%
3 PARK Faith K. - - - 1% 11% 47% 40%
5 ZHU Heidi - - 1% 7% 29% 43% 20%
6 MUCSI Angela Lilla - - 4% 16% 34% 34% 12%
7 LEE Michelle - 6% 21% 33% 27% 11% 2%
8 DING Jiahe (Heidi) - - - - 3% 24% 73%
9 CHEN Zhengnan(Janet) - - - - 7% 39% 54%
10 ZAFFT Tatiana M. - 1% 7% 29% 41% 20% 3%
11 KUZNETSOV Victoria - - 1% 6% 24% 42% 27%
12 PATURU Meghana - - 1% 5% 21% 42% 31%
13 SUN XiaoQi (Angelica) - 1% 6% 20% 34% 29% 10%
14 KIM Erika S. - 4% 26% 43% 23% 4% -
15 CHIN Isabella - - 1% 7% 30% 43% 19%
16 XIAO Ruien 1% 7% 24% 36% 24% 7% 1%
17 LEUNG Natalie - - - 2% 18% 46% 33%
18 LU Junyao - - 3% 17% 36% 32% 11%
19 ZUHARS Renee A. - - - 5% 23% 45% 27%
20 TOLBA Salma - - 4% 23% 44% 25% 4%
21 GABERKORN Nadia - - 4% 16% 34% 34% 12%
22 KIM Diane E. - - - 4% 23% 51% 22%
23 RUNIONS Emersyn - - - 5% 26% 45% 23%
24 YERMOLENKO Liza - 3% 13% 30% 35% 18% 2%
25 LOWENSTEIN Penelope J. - - 2% 15% 37% 35% 11%
26 REID Anousheh - 3% 15% 33% 32% 14% 2%
27 REID Sobia - 3% 17% 38% 32% 9% 1%
28 LI Bingqi - 2% 17% 42% 30% 8% 1%
29 MEHROTRA Anya - - 2% 13% 32% 37% 15%
30 LUO Ashley 1% 5% 19% 33% 29% 12% 2%
31 PADHYE Tanishka 1% 7% 24% 34% 24% 9% 1%
32 GAJJALA Sharika R. 2% 13% 31% 34% 17% 3% -
33 CHAN Elizabeth - 1% 6% 21% 36% 29% 8%
34 ZHANG Tina - 1% 6% 21% 35% 28% 8%
34 NING Emma - - 4% 20% 43% 28% 6%
36 WILLIAMS Mckenzie - - 4% 18% 39% 35% 5%
37 GU Sarah - - 2% 14% 39% 38% 7%
38 SMITH Grace L. - 1% 5% 24% 45% 23% 2%
39 DROVETSKY Alexandra M. - - - 5% 24% 46% 24%
40 CHERNYSHOVA Victoria - 2% 11% 27% 34% 21% 5%
41 PALMER Amelia C. 3% 18% 35% 31% 11% 1% -
42 WU Fan 1% 8% 23% 34% 25% 9% 1%
43 ELLENT Isabella S. 5% 24% 39% 25% 6% 1% -
44 JAKEL Sophia N. - - - 5% 27% 49% 19%
45 SEBASTIAN Felicity A. - - - 5% 22% 43% 29%
46 YANG Miranda (Yinuo) - 2% 17% 38% 31% 10% 1%
47 GUMAGAY Erika L. 4% 19% 34% 29% 12% 2% -
48 XUAN Nicole J. - 1% 7% 26% 41% 22% 3%
49 KIM Elizabeth Y. 1% 8% 26% 36% 22% 6% 1%
50 GAO Judy 1% 11% 31% 37% 17% 3% -
51 CHENG Ava - 4% 17% 32% 30% 14% 3%
51 KIM Angelina 4% 21% 36% 28% 10% 1% -
53 XU Jessica 36% 43% 17% 3% - - -
54 MAO Amy 3% 17% 34% 32% 13% 2% -
55 ALEXANDROV Katherine S. 2% 13% 30% 33% 18% 4% -
57 YU Bailey 1% 12% 33% 37% 15% 2% -
58 ZHENG Linden 21% 47% 27% 5% - - -
59 DREFKE Sigrid 1% 15% 42% 32% 8% 1% -
60 TAYLOR Kiera S. - 2% 10% 29% 36% 20% 4%
61 SHEN Stephanie 7% 28% 37% 22% 5% - -
62 ZENG Katrina 14% 41% 33% 10% 1% - -
63 MUELLER Emma M. 4% 20% 35% 29% 11% 1% -
64 RICHARDSON Lauren C. 25% 44% 25% 5% - - -
65 PALANSKI Cate 1% 9% 27% 36% 22% 5% -
66 LEE Yedda 2% 15% 42% 33% 9% 1% -
67 KIM Zoe L. - 3% 15% 34% 34% 13% 1%
68 OSTROVSKY Emily I. 3% 21% 40% 27% 7% 1% -
70 GOSHKO Audrey 1% 8% 24% 35% 24% 8% 1%
71 DESAI Meera P. 1% 8% 25% 34% 23% 8% 1%
72 NAYAK Mira 13% 37% 35% 12% 2% - -
73 BLIN Margaux J. 3% 19% 37% 29% 10% 2% -
74 MING Cynthia 28% 51% 18% 2% - - -
75 KONG Carina 14% 34% 32% 16% 4% 1% -
76 JEAN Olympe G. 10% 33% 36% 17% 4% - -
77 NIEMAN Anjolie 10% 37% 41% 12% 1% - -
78 MCLAREN Rachel 8% 28% 36% 22% 6% 1% -
79 KOKES Ava 15% 40% 32% 11% 2% - -
80 REMEZA Alissa 10% 32% 37% 18% 4% - -
83 HU Chelsea 6% 31% 43% 17% 2% - -
83 FLO Sena 23% 43% 26% 7% 1% - -
85 GLICK Nina 17% 38% 31% 12% 2% - -
86 KEE Bea Isabelle 6% 26% 39% 23% 5% - -
87 YIN Julia 1% 9% 25% 34% 23% 7% 1%
88 PAYNE Elizabeth 12% 35% 34% 16% 3% - -
89 LU Samantha R. 18% 38% 30% 12% 2% - -
90 BEEM Marin 17% 40% 31% 10% 1% - -
90 JOYAL Anne-Sophie 15% 51% 28% 5% - - -
92 KRUMHOLZ Nicole 39% 45% 14% 2% - - -
93 LIU Nicole 38% 43% 16% 3% - - -
94 MACEY Hadley 17% 37% 31% 12% 2% - -
95 LEE Anna 33% 45% 19% 3% - - -
96 RAI Ananya 57% 34% 8% 1% - - -
97 WU ALLYSON 5% 23% 36% 26% 9% 1% -
98 MACEDON Gianna 60% 35% 5% - - - -

Explanation

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.