National Championships & July Challenge (Summer Nationals)

Div I Women's Épée

Monday, July 3, 2023 at 8:00 AM

Phoenix Convention Center - Phoenix, AZ, 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 GUZZI VINCENTI Margherita A. - - - 2% 14% 41% 43%
2 NIXON Catherine (Kasia) D. - - - 1% 7% 33% 60%
3 CEBULA Anne - - 1% 9% 28% 40% 21%
3 TOBY Natalia R. - - - 2% 14% 41% 43%
5 JOYCE Michaela - - 1% 7% 25% 41% 26%
6 KHARCHYNA Polina - 2% 9% 26% 36% 22% 4%
7 LIN Jessica Y. - - 1% 5% 21% 42% 31%
8 YIN Julia - 5% 21% 36% 28% 9% 1%
9 LIN Waiyuk - 4% 17% 33% 31% 13% 2%
10 OXENREIDER Tierna A. - - 1% 7% 25% 41% 25%
11 HUSISIAN Hadley N. - - - - 6% 31% 63%
12 ZIGALO Elizabeth - 2% 11% 28% 35% 20% 4%
13 SEBASTIAN Felicity A. 1% 5% 18% 32% 29% 13% 2%
14 SHEFFIELD Lake Mawu - - 4% 17% 36% 33% 9%
15 CHIN Isabella - - 2% 14% 33% 36% 15%
16 CHU Audrey - 1% 6% 22% 38% 29% 5%
17 LIU Charlene (Kai) - - - 1% 6% 31% 63%
18 KETKAR Ketki - - - 3% 15% 41% 40%
19 KORFONTA Jolie 2% 13% 35% 37% 13% 1%
20 GRADY Miriam A. - - - 3% 15% 40% 41%
21 WASHINGTON Isis - - - 3% 19% 46% 31%
22 GAJJALA Sharika R. - 2% 11% 32% 39% 15% 2%
23 VIVEROS Montserrat - - - 2% 15% 45% 38%
24 LEE Sumin - 2% 9% 26% 36% 22% 5%
25 WANG Karen - - 2% 10% 28% 40% 21%
26 GANDHI Sedna S. - - 4% 18% 36% 32% 9%
27 TYLER Syd - 1% 9% 27% 37% 21% 4%
28 LUO Ashley - 5% 20% 35% 29% 10% 1%
29 YANG Alisa 6% 27% 40% 23% 4% -
30 FALLON Kyle R. - - 4% 15% 32% 34% 14%
31 RAUSCH Ariana (Ari) M. - 1% 8% 25% 36% 23% 5%
32 KOWALSKY Rachel A. - 2% 13% 32% 36% 16% 2%
33 MACHULSKY Leehi - - 3% 16% 35% 35% 11%
34 WU Fan 1% 6% 23% 37% 26% 7% 1%
35 KUZNETSOV Victoria - - 2% 10% 29% 40% 19%
36 JAKEL Sophia N. - - 5% 21% 37% 29% 8%
37 CHEN Lefu - 1% 8% 24% 36% 25% 6%
38 XIAO Ruien - - 1% 8% 27% 41% 22%
39 WADE-CURRIE Ava S. - 2% 9% 24% 34% 25% 7%
40 KHAMIS Yasmine A. - - 1% 6% 25% 45% 24%
41 GU Sarah - 1% 8% 24% 36% 25% 6%
42 HU Grace - 1% 7% 24% 39% 26% 4%
43 WANG Elizabeth - - 3% 16% 36% 35% 10%
44 CAFASSO Natalya 6% 23% 35% 25% 9% 1% -
45 YU Nicole J. 1% 7% 23% 34% 25% 8% 1%
46 DROVETSKY Alexandra M. - 1% 7% 24% 38% 25% 5%
47 BEI Karen - 3% 14% 30% 33% 17% 3%
48 AI Amy 14% 35% 33% 15% 3% - -
49 HURLEY Kelley A. - - - 3% 20% 50% 27%
50 PARK Faith K. - - 1% 7% 25% 42% 25%
51 MCCUTCHEN Lauren (Lulu) 9% 30% 35% 19% 5% 1% -
52 HAFEEZ Hania 4% 19% 35% 29% 12% 2% -
53 LEE Scarlett 4% 19% 35% 29% 12% 2% -
54 ZUHARS Renee A. - 2% 12% 29% 35% 18% 3%
55 ZHANG Victoria R. - 5% 19% 34% 29% 11% 1%
56 NGUYEN Tallulah - 1% 6% 21% 36% 28% 8%
57 MEHROTRA Anya - 4% 18% 34% 30% 12% 2%
58 FENG ge 15% 39% 32% 12% 2% - -
59 ALEXANDROV Katherine S. 10% 35% 37% 15% 2% -
60 PADHYE Tanishka 1% 8% 24% 34% 24% 8% 1%
61 LEE Natasha 2% 12% 28% 32% 19% 6% 1%
62 CALDERA Lexi I. 5% 22% 35% 26% 10% 2% -
63 DAMRATOSKI Anna Z. 3% 16% 34% 32% 14% 2% -
64 LAN Alice S. 2% 12% 29% 34% 19% 4% -
65 PEHLIVANI Zara 1% 11% 30% 35% 18% 4% -
66 LEE Michelle J. - 1% 9% 27% 37% 22% 4%
67 REID Anousheh 5% 21% 35% 27% 10% 2% -
68 MUELLER Emma M. 9% 35% 37% 16% 3% - -
69 WU Amelia 1% 6% 22% 36% 26% 8% 1%
70 GEBALA Natalie Brooke A. - 4% 18% 35% 30% 11% 1%
71 LIN Ashley 30% 43% 22% 5% 1% - -
72 MAO Amy 1% 9% 28% 36% 20% 5% -
73 ELSTON Sophia 15% 39% 32% 11% 2% - -
74 BASSA Francesca A. - - - 3% 27% 70%
75 RUNIONS Emersyn 2% 13% 31% 33% 16% 3% -
76 WITTER Catherine A. 3% 17% 34% 30% 13% 2% -
77 MAZUR Yeva - 1% 6% 20% 36% 29% 8%
78 CAPELLUA Mariasole 1% 8% 25% 36% 23% 6% -
79 XUAN Nicole J. - 1% 7% 24% 37% 25% 6%
80 DOROSHKEVICH Victoriia 1% 6% 22% 34% 26% 9% 1%
81 NING Emma - 2% 11% 29% 36% 20% 2%
82 ZHOU Wenjun 6% 25% 36% 24% 8% 1% -
83 SMUK Alexandra S. 3% 17% 33% 30% 14% 3% -
84 BECKMAN Ana 10% 32% 36% 18% 4% - -
85 NIXON Caroline (Karolina) L. - - 2% 12% 32% 38% 15%
85 NGUYEN Kira 1% 10% 28% 35% 20% 5% -
87 SMOTRITSKY Mia 1% 8% 24% 33% 24% 9% 1%
88 LI Fei 29% 42% 23% 6% 1% - -
89 SPRINGER Sierra 2% 14% 31% 32% 16% 4% -
90 CANNING Charlotte 29% 42% 22% 6% 1% - -
91 SONG Angela 5% 24% 38% 25% 7% 1% -
92 LIU Nicole 20% 39% 29% 10% 2% - -
93 DESAI Meera P. 5% 22% 36% 27% 9% 1% -
94 YAO Melinda 9% 29% 35% 20% 6% 1% -
95 PHUKAN Indra 25% 41% 26% 7% 1% - -
96 PAPADAKIS Lily 3% 18% 38% 31% 9% 1% -
97 DAVIS Jessica L. 3% 17% 33% 30% 13% 3% -
98 O'DONNELL Amanda A. - 1% 6% 23% 37% 26% 7%
99 ISERT Sarah - 3% 15% 33% 33% 14% 2%
99 YOU Emily 7% 27% 36% 22% 7% 1% -
101 HONG Elaine 7% 28% 37% 21% 6% 1% -
102 GAO Judy 12% 32% 33% 18% 5% 1% -
103 DING Jiahe (Heidi) - - 1% 6% 23% 41% 29%
103 QI Jarynne Valerie 9% 31% 36% 18% 4% - -
105 PINNAMANENI Drithi 28% 43% 23% 5% 1% - -
106 SWENSON Nikita G. 8% 30% 38% 20% 5% - -
107 KIM Zoe L. - 4% 18% 36% 31% 10% 1%
108 KIM Jayna 5% 21% 35% 27% 10% 2% -
109 SMUK Daria A. 9% 31% 37% 18% 4% - -
110 PRIHODKO Nina 11% 33% 35% 17% 4% - -
111 POTAPENKO Margarita D. 5% 27% 40% 22% 6% 1% -
112 YAMANAKA Mina - 2% 13% 38% 40% 7%
113 SHU Youshan 35% 43% 19% 3% - -
114 KETKAR Mallika 1% 7% 24% 36% 25% 7% 1%
115 SHELIN Chelsea 17% 41% 30% 10% 2% - -
116 MONTOYA Kimberlee C. 1% 8% 24% 35% 24% 8% 1%
116 SANTA MARIA Luisa F. 13% 35% 33% 15% 3% - -
118 ZHU Serene M. 10% 29% 34% 20% 6% 1% -
119 WONG Alexandra R. 19% 39% 30% 11% 2% - -
120 KORKIN Alice 28% 42% 23% 6% 1% - -
121 LI Zhenni (Jenny) 16% 42% 31% 10% 1% - -
122 BOYS Nishta B. 1% 6% 22% 36% 27% 8% 1%
122 MCLANE Lauren 2% 11% 29% 34% 19% 5% -
122 KENT Elizabeth J. 29% 41% 23% 6% 1% - -
125 KALE Anika A. 4% 20% 35% 28% 10% 2% -
125 GARCIA Luciana 28% 42% 23% 6% 1% - -
127 SMITH Grace L. 2% 16% 36% 33% 12% 1% -
128 CHA Eugenie 14% 34% 33% 15% 4% - -
129 NELSON-LOVE Lily B. 3% 15% 32% 32% 15% 3% -
130 LEUNG Natalie 1% 9% 28% 35% 21% 5% -
131 TAN Jocelyn 18% 38% 31% 11% 2% - -
132 LEE Olivia 2% 13% 29% 33% 18% 5% -
133 BOTNER Olivia 16% 36% 32% 14% 3% - -
134 SU Evelyn 27% 43% 24% 5% - - -
135 BUSH emma 9% 32% 37% 18% 4% - -
136 KIM Elizabeth Y. 5% 22% 35% 27% 10% 2% -
137 CHANG Celine A. 23% 41% 27% 8% 1% - -
138 SHARMA Sanvi 44% 41% 13% 2% - - -
139 ANDERSON Claire 25% 42% 25% 7% 1% - -

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.