December NAC

Div I Women's Épée

Friday, December 10, 2021 at 8:00 AM

Columbus, OH, USA

Probability density of pool victories

Reset

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 NIXON Catherine (Kasia) D. - - - - 3% 25% 72%
2 GRADY Miriam A. - - - 4% 17% 40% 38%
3 VERMEULE Emily - - - 2% 19% 54% 24%
3 HUSISIAN Hadley N. - - - 1% 7% 35% 58%
5 LIU Charlene (Kai) - - - 1% 8% 35% 56%
6 VAN BRUMMEN Anna C. - - - - 4% 26% 69%
7 JOYCE Michaela - - - 1% 11% 39% 49%
8 PARK Faith K. - - 1% 8% 25% 41% 25%
9 TYLER Syd - 5% 20% 37% 30% 9%
10 FALLON Kyle R. - - 5% 21% 39% 29% 6%
11 WU Amelia - 2% 12% 30% 36% 17% 2%
12 LEE Michelle J. - 4% 15% 31% 31% 16% 3%
13 CHORNIY Kateryna - 3% 15% 36% 35% 10%
14 PATURU Meghana - 2% 14% 34% 36% 14%
15 GU Sarah - 2% 11% 30% 39% 18%
16 WADE-CURRIE Ava S. 1% 8% 23% 33% 25% 9% 1%
17 HOLMES Katharine (Kat) W. - - - - 6% 39% 55%
18 CEBULA Anne - - - 4% 20% 43% 33%
19 DI TELLA Isabel - 1% 5% 20% 38% 30% 6%
20 JAKEL Sophia N. 1% 6% 20% 33% 28% 11% 2%
21 LEE Sumin - 3% 15% 31% 33% 15% 3%
22 TEMIRYAEV Anna M. 5% 24% 37% 25% 8% 1%
23 KETKAR Ketki - - - 2% 12% 40% 46%
24 KOMAR Sofia - - 4% 17% 35% 33% 11%
24 XUAN Nicole J. 3% 15% 30% 31% 17% 4% -
26 WANG Karen - - 2% 11% 29% 37% 19%
27 O'DONNELL Amanda A. - - 2% 12% 30% 38% 18%
28 XIAO Ruien 1% 11% 29% 34% 19% 5% -
29 SMOTRITSKY Mia 5% 22% 36% 27% 9% 1% -
30 NGUYEN Tallulah 8% 27% 35% 22% 7% 1% -
31 MAO Amy 1% 9% 26% 35% 23% 6% 1%
32 WASHINGTON Isis - - < 1% 1% 10% 37% 52%
33 GUZZI VINCENTI Margherita A. - - - 1% 11% 38% 49%
34 KHAMIS Yasmine A. - - - 3% 18% 46% 32%
35 GANDHI Sedna S. - - 1% 7% 24% 41% 27%
36 LU Junyao 2% 12% 28% 32% 19% 6% 1%
37 WATRALL Christina - - 4% 17% 37% 33% 8%
38 CHEN Zhengnan(Janet) - 2% 9% 24% 34% 24% 6%
39 DESAI Meera P. 1% 11% 29% 34% 19% 5% -
40 WEISS Talia L. 3% 21% 37% 28% 10% 1%
41 MYLER AnneMarie - 2% 11% 28% 35% 20% 4%
42 SEBASTIAN Felicity A. - 1% 8% 26% 39% 23% 4%
43 KHROL Jaclyn - - 1% 5% 22% 46% 27%
44 HU Grace - 3% 15% 37% 36% 8% -
45 SWEET Ryleigh E. 25% 41% 25% 7% 1% - -
46 GAJJALA Sharika R. 1% 6% 20% 34% 29% 10% 1%
47 GEBALA Natalie Brooke A. - 4% 16% 31% 31% 15% 2%
48 WANG anne 1% 10% 26% 34% 21% 7% 1%
49 ZHANG Tina Tianyi - 3% 14% 31% 35% 17% 1%
50 OXENREIDER Tierna A. - 4% 18% 37% 32% 9%
51 CHIN Isabella - 4% 15% 33% 34% 14%
52 BASSA Francesca A. - - 1% 11% 40% 48%
53 ZIGALO Elizabeth 1% 9% 25% 33% 23% 7% 1%
54 DYNER Karina 1% 7% 22% 34% 26% 9% 1%
55 LUO Ashley - 3% 15% 32% 33% 14% 2%
56 BEI Karen - 1% 5% 19% 37% 31% 7%
57 CHU Audrey - 3% 14% 31% 34% 16% 2%
57 PADHYE Tanishka 2% 13% 30% 33% 18% 4% -
59 MILEWSKI Nicole 3% 15% 32% 33% 15% 3% -
60 WANG Nora 2% 13% 30% 33% 17% 4% -
61 SEMIKIN Julia 8% 32% 39% 18% 3% -
62 MACHULSKY Leehi - - 2% 10% 28% 39% 21%
63 ISERT Sarah 1% 8% 23% 35% 25% 8% 1%
64 XU Grace (XinYi) 1% 5% 19% 33% 28% 12% 2%
65 PIRKOWSKI Amanda L. - - 1% 6% 23% 42% 29%
66 LIN Katie Y. - 1% 4% 17% 35% 32% 10%
67 WITTE Vera 8% 28% 36% 21% 6% 1% -
68 LIN Jessica Y. - - 3% 18% 42% 36%
69 KORFONTA Jolie 9% 29% 35% 21% 6% 1%
70 MILLETTE Marie Frederique - - 2% 12% 33% 39% 14%
71 WANG Elizabeth - 1% 5% 18% 34% 31% 10%
72 DOUGLAS Julia F. 1% 6% 22% 35% 26% 9% 1%
73 HENRY Asha S. 2% 12% 29% 33% 19% 5% -
74 AHUJA Arianna 7% 25% 35% 24% 8% 1% -
75 ZUHARS Renee A. 4% 20% 35% 28% 11% 2% -
76 MUELLER Emma M. 12% 35% 34% 15% 3% - -
77 LEUNG Natalie - 5% 20% 37% 30% 9%
78 KETKAR Mallika - 4% 18% 36% 31% 10%
79 MCLANE Lauren 3% 17% 36% 31% 11% 1%
80 HAMILTON Pauline S. 2% 12% 30% 34% 18% 4%
81 MONTOYA Kimberlee C. 1% 10% 29% 38% 19% 3%
82 CHEN Lefu 7% 31% 39% 19% 4% -
83 MAZUR Yeva 1% 7% 23% 36% 26% 7% 1%
84 DONDISCH Sophia 7% 26% 36% 23% 7% 1% -
84 LIN Waiyuk 3% 17% 33% 31% 14% 3% -
86 SCHMIDT Lori M. 1% 6% 21% 35% 28% 9% 1%
87 CALDERA Lexi I. 3% 17% 33% 30% 13% 3% -
87 LIN Elaine 7% 25% 35% 23% 8% 1% -
89 REID Anousheh 1% 10% 29% 35% 20% 4% -
89 LIU Christina A. - 1% 8% 24% 37% 25% 6%
91 SWENSON Nikita G. 23% 41% 26% 8% 1% - -
92 SAAL Anna 26% 40% 25% 8% 1% - -
93 PINNAMANENI Drithi 40% 42% 15% 2% - - -
94 DROVETSKY Alexandra M. 1% 7% 27% 42% 21% 3%
95 HUELLAS-BRUSKIEWICZ Marie-Rose R. - 4% 19% 36% 31% 10%
96 KUZNETSOV Victoria 1% 10% 27% 35% 21% 5%
97 LOMBARD Ella 2% 11% 29% 35% 19% 4%
98 WHITTEMORE Lucy K. 11% 36% 35% 15% 3% -
99 GUMAGAY Erika L. 11% 32% 35% 18% 4% - -
100 NING Emma 2% 11% 28% 34% 20% 5% 1%
101 ROBERTSON Lily 3% 15% 31% 31% 16% 4% -
102 YU Nicole J. 9% 28% 35% 22% 7% 1% -
103 LEE kyungmin 1% 6% 19% 33% 28% 11% 2%
103 LEE Olive 8% 26% 34% 23% 8% 1% -
105 RUNIONS Emersyn 2% 12% 31% 34% 17% 4% -
106 LEE Yedda 7% 27% 37% 23% 7% 1% -
107 MALDONADO Pilar I. 1% 6% 21% 34% 27% 10% 1%
107 ZHANG Victoria R. 2% 15% 32% 32% 15% 3% -
109 KIM Elizabeth Y. 3% 16% 32% 31% 14% 3% -
110 RAUSCH Ariana (Ari) M. - - 3% 15% 36% 37% 8%
111 CAPELLUA Mariasole 3% 17% 33% 31% 14% 3% -
112 YANG Alisa 10% 30% 35% 20% 6% 1% -
113 DOROSHKEVICH Victoriia 1% 6% 21% 33% 27% 11% 2%
114 REID Sobia 3% 18% 38% 31% 9% 1% -
114 WEBER Nora 3% 16% 33% 31% 14% 3% -
114 YAO Melinda 10% 31% 36% 19% 5% - -
117 IGOE Nirali B. 6% 22% 33% 26% 11% 2% -
118 DAMRATOSKI Anna Z. 10% 30% 35% 19% 5% 1% -
119 FURMAN Maria 10% 35% 37% 16% 3% - -
120 NEMETH Katherine 4% 21% 36% 28% 10% 2% -
121 KALE Anika A. 10% 29% 34% 20% 6% 1% -
121 MING Cynthia 17% 36% 31% 13% 3% - -
123 ASHER Valerie 3% 17% 35% 31% 12% 2% -
124 PAPADAKIS Lily 3% 17% 37% 32% 10% 1% -
125 SZEWC Alexandra 4% 20% 35% 29% 11% 2% -
126 BELAOUSSOFF Kira 16% 38% 32% 12% 2% -
127 DAVIS Jessica L. 4% 22% 37% 27% 9% 1%
128 WU Fan 15% 35% 32% 14% 3% -
129 SMUK Daria A. 36% 43% 18% 3% - -
130 PROKOP Jeannine A. 17% 38% 32% 11% 2% -
131 BALAKRISHNAN Monica S. - 3% 16% 33% 32% 14% 1%
132 LONADIER Keira 4% 20% 35% 29% 10% 2% -
133 LI Alisha 21% 39% 28% 10% 2% - -
134 KIM Zoe L. 1% 7% 23% 35% 25% 8% 1%
135 MEHROTRA Anya 2% 11% 27% 33% 21% 6% 1%
135 ZENG Katrina 26% 42% 24% 7% 1% - -
137 NORCONK Claire R. 5% 20% 34% 27% 12% 2% -
137 CHAN Elizabeth 7% 27% 35% 22% 7% 1% -
139 WONG Alexandra R. 24% 42% 26% 7% 1% - -
140 MCCUTCHEN Lauren (Lulu) 9% 29% 35% 20% 6% 1% -
141 NELSON-LOVE Lily B. 2% 15% 32% 31% 15% 3% -
141 BARON Sabina 21% 39% 28% 10% 2% - -
143 SCHAFF Marlene M. 16% 40% 32% 11% 1% - -
144 ZAFFT Sharrie A. - 6% 24% 38% 24% 6% 1%
145 MYERS Jeanelle Christina A. 3% 20% 38% 28% 9% 1% -
146 SCHULTZ Michelle M. 3% 16% 31% 30% 15% 4% -
147 PEELER Julia 44% 40% 14% 2% - -
148 STOECKEL Sofia I. 36% 41% 19% 4% - - -
149 MALLAVARPU Aarthi C. 10% 30% 35% 20% 5% 1% -
149 BAJAJ Nikita K. 17% 37% 31% 13% 2% - -
151 LAVERY Chloe K. 1% 11% 29% 35% 19% 4% -
152 YIN Julia 2% 13% 30% 33% 18% 4% -
153 ELSTON Sophia 14% 36% 33% 14% 3% - -
154 BOTNER Olivia 15% 37% 32% 13% 2% - -
155 SHEN Stephanie 33% 43% 19% 4% - -
156 GAO Judy 13% 33% 33% 16% 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.