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(1) Maria Panyi, (2) Andrey Geva, (3) Igor Chirashnya, and (4) Sue Moheb.

November NAC

Y-14 Women's Épée

Monday, November 11, 2019 at 8:00 AM

Milwaukee, WI - Milwaukee, WI, 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 MACHULSKY Leehi - - - 1% 10% 38% 50%
2 DING Jiahe (Heidi) - - - - 2% 22% 76%
3 LIN Katie Y. - - 2% 10% 28% 39% 21%
3 LEE Michelle J. - - - 3% 16% 42% 39%
5 LEUNG Natalie - - - 4% 17% 41% 38%
6 NELSON-LOVE Lily B. - - 4% 16% 33% 34% 14%
7 CHAN Cheri K. - 3% 18% 36% 32% 11%
8 PADHYE Tanishka - 4% 18% 34% 30% 13% 2%
9 LIU Christina A. - 1% 7% 25% 37% 25% 5%
10 MEHROTRA Anya - - 5% 23% 47% 24%
11 NING Emma - - 1% 7% 26% 43% 23%
12 LABRACHE Ella P. - 2% 15% 35% 34% 13% 1%
13 LU Shiqi - 1% 7% 24% 37% 25% 6%
14 GHIDINA O'Livia G. - - 3% 17% 45% 36%
15 GEBALA Natalie Brooke A. - 4% 19% 43% 35%
16 HU Grace - - 1% 6% 25% 45% 23%
17 KUZNETSOV Victoria - - 2% 11% 31% 39% 18%
18 ZHANG Tina - - 3% 17% 36% 32% 10%
19 CHIN Isabella - - 1% 6% 23% 42% 28%
20 REMEZA Alissa - 1% 9% 28% 38% 20% 4%
21 MCCUTCHEN Lauren (Lulu) - 1% 9% 26% 36% 23% 5%
22 SEBASTIAN Felicity A. - - 1% 6% 24% 44% 26%
23 DROVETSKY Alexandra M. - 1% 6% 21% 35% 28% 9%
24 GAJJALA Sharika R. - 2% 12% 30% 36% 18% 1%
25 TEMIRYAEV Anna M. 1% 9% 29% 36% 21% 4%
26 YU Nicole J. - 4% 16% 31% 30% 15% 3%
27 DESAI Meera P. - 2% 12% 32% 36% 16% 2%
28 SMITH Grace L. - 1% 7% 23% 37% 25% 6%
29 GLASER Drew - 5% 22% 37% 27% 9% 1%
30 FALLON Kyle R. - 1% 9% 29% 37% 20% 4%
31 GU Sarah - 1% 10% 32% 41% 16%
32 CALDERA Lexi I. - 3% 17% 36% 32% 11%
33 WADE-CURRIE Ava S. - 1% 5% 23% 43% 28%
34 JAKEL Sophia N. - - 1% 7% 28% 44% 21%
35 LAVERY Chloe K. - 3% 14% 30% 32% 17% 4%
36 MALLAVARPU Aarthi C. - 3% 15% 31% 32% 16% 3%
37 FILONOVA Alisa 1% 21% 39% 28% 9% 1%
38 DANIEL Olivia 3% 18% 38% 32% 8%
39 YANG Miranda (Yinuo) - - 3% 18% 38% 33% 7%
40 LEE Sumin - - 1% 5% 23% 44% 28%
41 SEMIKIN Julia - - 1% 9% 29% 41% 19%
42 WANG Nora - 2% 9% 24% 34% 24% 7%
43 TAYLOR-CASAMAYOR Maia - 1% 7% 23% 36% 26% 7%
44 LUO Ashley - 1% 9% 28% 39% 20% 3%
45 HAFEEZ Hania 5% 26% 40% 24% 5% -
46 CHIRASHNYA Noya 7% 29% 40% 21% 4% -
47 REID Anousheh - 5% 23% 38% 27% 7%
48 NGUYEN Kira 2% 12% 31% 34% 17% 4% -
49 GORNOVSKY Abigail 1% 6% 21% 34% 26% 10% 2%
49 XIAO Ruien 1% 8% 25% 34% 24% 8% 1%
51 SHEN Stephanie - 2% 13% 31% 34% 17% 3%
52 RUNIONS Emersyn - - 3% 15% 34% 35% 13%
53 CAPELLUA Mariasole 6% 27% 40% 23% 4%
54 KIZILBASH Zara 19% 40% 30% 9% 1%
55 DUMAS Marie 7% 36% 38% 16% 3% - -
56 MUELLER Emma M. 2% 14% 32% 33% 16% 3% -
57 MING Cynthia 2% 15% 32% 32% 15% 3% -
58 BURN Lauren M. - 6% 23% 39% 26% 6%
59 GUJJA Misha 17% 40% 31% 10% 1% -
60 GUMAGAY Erika L. - 4% 17% 34% 32% 12% 1%
61 ELSTON Sophia 3% 19% 38% 29% 10% 1% -
62 HONG Elaine 2% 18% 37% 31% 11% 2% -
63 HAFEEZ Hiba 3% 21% 37% 28% 10% 2% -
64 HU Chelsea 13% 38% 35% 12% 2% - -
65 KIM Zoe L. - 4% 18% 35% 30% 12% 2%
66 PEHLIVANI Zara 1% 7% 24% 36% 25% 7% -
67 SUN XiaoQi (Angelica) - - 3% 15% 35% 34% 12%
68 LI Alisha 7% 31% 39% 18% 4% - -
69 TAYLOR Kiera S. - 3% 15% 32% 32% 14% 2%
70 RUMMEL Katherine E. 11% 33% 35% 17% 4% - -
71 LIN Waiyuk - - 4% 18% 36% 31% 10%
72 HESS Heidi J. 1% 14% 35% 34% 14% 2% -
73 ZHENG Linden 21% 40% 28% 9% 2% - -
73 ALEXANDROV Katherine S. - 1% 9% 26% 36% 22% 4%
75 YAO KATHARINE 1% 8% 27% 36% 21% 6% 1%
76 DU Angela 3% 18% 35% 30% 11% 2% -
77 MAO Amy - 4% 18% 34% 30% 12% 1%
78 CHERNYSHOVA Victoria - 3% 16% 35% 33% 12% 1%
79 KNOX Alexia 25% 41% 25% 7% 1% - -
80 SWENSON Nikita G. 23% 43% 27% 7% 1% -
81 LIN Elaine 42% 41% 14% 2% - -
82 CHERNIS Zoe C. - 1% 8% 23% 34% 25% 7%
83 LI Suri 2% 17% 36% 31% 12% 2% -
84 SMOTRITSKY Mia 7% 30% 38% 20% 5% - -
85 LEACH Meka A. - 1% 9% 28% 38% 21% 4%
85 JOYAL Anne-Sophie 9% 29% 36% 20% 5% 1% -
87 HOSANAGAR Inchara 41% 41% 15% 3% - - -
88 PRIHODKO Nina 23% 46% 25% 6% 1% - -
89 MONE Kylie 40% 41% 16% 3% - - -
90 JAMES Josephine 1% 10% 29% 36% 19% 4% -
91 RAUSCH Juliana 2% 13% 36% 34% 13% 2% -
92 CHEN Quanyou Lisa 74% 24% 1% - - - -
93 LEE Yedda 2% 16% 33% 31% 14% 3% -
94 ZENG Katrina 18% 38% 30% 12% 3% - -
95 CHANG Ella 3% 21% 40% 28% 7% 1%
96 QURESHI Nisa 3% 21% 39% 28% 8% 1% -
97 WU ALLYSON 2% 13% 32% 34% 16% 3% -
98 BYBEE Lucy J. 16% 37% 32% 12% 2% - -
99 YU Bailey 15% 36% 31% 14% 3% - -
100 LIU Alice 62% 31% 6% - - - -
100 MOON Seojung 23% 40% 27% 9% 1% - -
102 BEEM Marin 32% 44% 20% 4% - - -
103 NELSON Grace E. 67% 29% 4% - - - -
104 GREGORY Aleksandra 16% 40% 33% 11% 1%
105 HSU Adele Y. 19% 41% 29% 10% 2% - -
106 MA ELISE 5% 24% 40% 25% 6% -
107 KALE Anika A. 2% 12% 29% 33% 19% 5% 1%
108 KOKES Ava < 1% 7% 27% 38% 22% 6% -
109 SKOURLETOS Angelina 3% 18% 35% 30% 12% 2% -
110 MACEY Hadley 61% 32% 6% 1% - - -
111 GLICK Nina 18% 39% 30% 10% 2% - -
112 MAMEDOVA Farah 73% 23% 3% - - -
113 KRUMHOLZ Nicole 33% 45% 18% 3% - - -
114 WITTER Catherine A. 6% 35% 38% 17% 4% - -

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.