June NAC

Div I Women's Épée

Sunday, June 6, 2021 at 1:45 PM

, - Richmond, VA, 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 HUSISIAN Hadley N. - - - 3% 18% 42% 36%
2 HURLEY Courtney L. - - - 1% 7% 35% 57%
3 GUZZI VINCENTI Margherita A. - - - 1% 11% 38% 49%
3 GANDHI Sedna S. - 3% 21% 47% 25% 4%
5 HOLMES Katharine (Kat) W. - - - - 1% 16% 83%
6 WASHINGTON Isis - - - - 4% 26% 69%
7 HURLEY Kelley A. - - 1% 9% 41% 49%
8 WINES Victoria R. - 2% 12% 31% 38% 17%
9 KETKAR Ketki - - - 4% 19% 45% 32%
9 CEBULA Anne - - 3% 12% 29% 36% 19%
11 PIRKOWSKI Amanda L. - - 2% 10% 29% 40% 19%
12 OXENREIDER Tierna A. - - 2% 9% 28% 40% 21%
13 NIXON Catherine (Kasia) D. - - - 1% 8% 37% 55%
14 JOYCE Michaela - - - 1% 10% 38% 50%
15 PARK Faith K. - - 2% 14% 41% 42%
16 WADE-CURRIE Ava S. - 4% 17% 34% 32% 11% 1%
17 LIN Jessica Y. - - - 1% 10% 37% 52%
18 WANG Elizabeth - 3% 13% 31% 34% 17% 2%
19 LEE Sumin - 1% 9% 27% 39% 22% 2%
20 LIU Charlene (Kai) - - 1% 10% 37% 52%
21 MACHULSKY Leehi - 3% 14% 36% 37% 11%
22 LIN Katie Y. - 6% 24% 41% 25% 5%
23 GRADY Miriam A. - - 4% 20% 43% 32%
24 WU Amelia 2% 12% 32% 36% 16% 2%
25 PATURU Meghana - 1% 9% 25% 35% 24% 6%
26 BATES Cassandra L. - - 1% 6% 23% 41% 29%
27 BALAKRISHNAN Monica S. - 4% 19% 36% 30% 10% 1%
27 LEE Michelle J. - 4% 16% 32% 31% 14% 3%
29 WANG Karen - - 1% 6% 26% 45% 22%
30 KUZNETSOV Victoria 2% 13% 31% 34% 16% 3% -
31 LURYE Sarah - 2% 13% 35% 38% 13%
32 GABERKORN Nadia 6% 25% 38% 24% 6% -
33 MCLANE Lauren - 1% 9% 25% 35% 23% 6%
34 LEUNG Natalie - 5% 19% 35% 30% 10% 1%
35 FALLON Kyle R. - 2% 12% 28% 34% 20% 4%
36 BASSA Francesca A. - - - - 2% 19% 80%
37 NIXON Caroline (Karolina) L. - - 3% 14% 35% 36% 11%
38 JAKEL Sophia N. - 4% 18% 35% 31% 11% 1%
39 GARINA Ania (Ganusia) - - 3% 15% 37% 37% 8%
40 SMITH Grace L. 3% 15% 32% 33% 15% 3% -
41 WATRALL Christina - - 4% 17% 36% 34% 8%
42 CHOI Lyla 1% 10% 30% 37% 19% 3%
43 DROVETSKY Alexandra M. - 3% 15% 33% 33% 14% 2%
44 NGUYEN Kira 8% 28% 36% 22% 6% 1% -
45 ZHANG Tina Tianyi 1% 8% 22% 32% 25% 10% 1%
46 GEBALA Natalie Brooke A. - 3% 13% 32% 36% 15% 1%
47 MALDONADO Pilar I. - 4% 17% 33% 31% 12% 2%
48 RUNIONS Emersyn 1% 7% 24% 36% 25% 7% -
49 CHERNIS Zoe C. 6% 22% 33% 25% 11% 2% -
50 KHAMIS Yasmine A. - - 4% 22% 46% 28%
50 CHOI Eunice 7% 34% 42% 15% 2% -
52 GU Sarah 1% 10% 31% 38% 17% 3%
53 O'DONNELL Amanda A. - 3% 17% 35% 33% 11%
54 TYLER Syd - 5% 22% 39% 29% 5%
55 CONSTANTINO Lola - - 2% 11% 38% 49%
56 KOWALSKY Rachel A. 1% 8% 26% 36% 23% 6% -
57 NING Emma 1% 6% 21% 35% 28% 10% 1%
58 MEHROTRA Anya 2% 14% 30% 32% 17% 4% -
59 RUEDA Rylie - - 4% 16% 33% 33% 13%
60 CHOY LeeAnn - 3% 14% 31% 34% 16% 2%
61 WHITTEMORE Lucy K. 3% 17% 33% 30% 14% 3% -
62 CHEN Lefu 1% 9% 28% 36% 21% 5% -
63 STEWART Tatijana I. - - 5% 28% 48% 18%
64 BEI Karen - 3% 14% 33% 34% 15% 1%
65 NI Emma - 2% 13% 32% 36% 14% 2%
66 KIM Elizabeth Y. 4% 19% 35% 29% 11% 2% -
67 BOYS Nishta B. - 4% 15% 32% 32% 14% 2%
68 YANG Miranda (Yinuo) - 3% 14% 30% 33% 16% 3%
69 HU Grace 1% 12% 31% 35% 18% 3%
70 JAMES Josephine 30% 42% 22% 5% 1% -
71 DESAI Meera P. 8% 30% 38% 20% 4% -
72 CAPELLUA Mariasole 21% 41% 28% 8% 1% -
73 GLASSNER Sophia Rose S. 47% 39% 12% 2% - -
74 MORGAN Elizabeth (Ella) R. 4% 27% 40% 23% 6% -
75 CHU Audrey 1% 7% 23% 36% 26% 8% -
76 PAPADAKIS Lily 2% 13% 32% 34% 15% 3% -
76 GUMAGAY Erika L. 8% 27% 35% 22% 7% 1% -
76 MAO Amy 4% 19% 34% 29% 12% 2% -
79 BENATER Lauren 2% 12% 30% 35% 18% 4% -
80 LU Junyao 1% 6% 22% 36% 27% 8% -
81 CHAN Elizabeth 5% 23% 36% 26% 8% 1% -
82 LUO Ashley 4% 20% 35% 28% 11% 2% -
83 GAJJALA Sharika R. 1% 9% 24% 32% 24% 9% 1%
84 SZEWC Alexandra 9% 29% 36% 20% 6% 1% -
85 GAO Judy 15% 44% 33% 7% 1% -
86 LEANG Priscilla Y. 5% 24% 38% 25% 7% 1%
87 NGUYEN Kaylin A. 1% 10% 29% 37% 20% 3%
88 LEE kyungmin 3% 20% 36% 29% 10% 1%
89 COBERT Helen G. 7% 29% 38% 21% 5% -
90 SCHMIDT Lori M. 2% 16% 35% 32% 13% 2%
91 RAUSCH Ariana (Ari) M. - 2% 11% 30% 39% 19%
92 SHEN Stephanie 12% 35% 35% 15% 3% -
93 KETKAR Mallika 1% 7% 20% 32% 27% 11% 2%
94 ANGEN Katie R. - - 1% 8% 29% 48% 15%
95 KIM Zoe L. 5% 22% 36% 26% 9% 1% -
95 NGUYEN Tallulah 15% 35% 32% 14% 3% - -
97 WEBER Nora 7% 27% 36% 23% 6% 1% -
98 MYERS Jeanelle Christina A. 15% 36% 33% 14% 3% - -
99 WEISS Talia L. 1% 7% 23% 36% 26% 8% -
100 EBRAHIM Ameera H. 11% 32% 35% 18% 4% - -
101 SMOTRITSKY Mia 18% 38% 31% 12% 2% - -
102 MILEWSKI Nicole 5% 23% 35% 26% 9% 1% -
103 AHUJA Arianna 12% 32% 34% 18% 5% 1% -
104 LAVERY Chloe K. 7% 31% 37% 19% 5% - -
105 CHIN Isabella - 1% 7% 24% 37% 25% 5%
106 BAJAJ Nikita K. 9% 30% 37% 20% 5% - -
107 MARTUS Cosima O. 1% 12% 32% 34% 17% 3% -
108 MESCHIA Maggie 39% 41% 17% 3% - - -
109 CHAN Cheri K. 6% 27% 38% 22% 6% -
110 SHAMSIAN Shaya 1% 11% 31% 37% 17% 2%
111 LIU Christina A. 3% 19% 36% 30% 10% 1%
112 PADHYE Tanishka 13% 36% 35% 14% 2% -
113 KORKIN Alice 55% 36% 8% 1% - -
114 LIN Elaine 22% 41% 28% 9% 1% - -
115 NELSON-LOVE Lily B. 2% 11% 26% 32% 21% 7% 1%
116 RASMUSSEN Ashelee 7% 23% 33% 25% 10% 2% -
116 CHENG Ava 7% 27% 36% 23% 7% 1% -
118 BOWIE Charlotta 50% 38% 11% 1% - - -
119 DAMRATOSKI Anna Z. 5% 23% 37% 26% 9% 1% -
120 SCHULTZ Michelle M. 1% 9% 26% 35% 22% 6% 1%
121 MALLAVARPU Aarthi C. 8% 28% 36% 21% 6% 1% -
122 ELSTON Sophia 7% 27% 38% 23% 6% 1% -
123 GITHENS Gracyn J. 4% 20% 35% 29% 10% 2% -
124 MCCUTCHEN Lauren (Lulu) 7% 26% 36% 23% 7% 1% -
125 CAREY Michele S. 25% 41% 26% 8% 1% - -
125 SAAL Anna 22% 40% 28% 9% 2% - -
127 ASHER Valerie 6% 23% 35% 26% 9% 1% -
128 JANOWSKI Madeline (Madeline Janowski) A. 23% 42% 27% 8% 1% -
129 ZHANG Victoria R. 8% 28% 36% 22% 6% 1% -
130 ZUHARS Renee A. 2% 12% 30% 34% 18% 4% -
131 ZAFFT Sharrie A. 4% 27% 41% 23% 5% -
132 PROKOP Jeannine A. 18% 38% 30% 11% 2% - -
133 SLACKMAN Valerie 11% 32% 34% 17% 5% 1% -
134 HESS Heidi J. 45% 40% 13% 2% - - -
135 DARANOUVONG Logan 7% 26% 37% 24% 7% 1% -
136 LONG Cindy 3% 15% 31% 31% 16% 4% -
136 MING Cynthia 18% 38% 30% 11% 2% - -
138 SWEET Ryleigh E. 31% 43% 21% 5% - -
138 KIM Erika S. 42% 43% 13% 1% - -
140 REID Anousheh 8% 33% 37% 18% 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.