December NAC

Div I Women's Foil

Sunday, December 12, 2021 at 8:00 AM

Columbus, OH, 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 KONG Chin-Yi - 2% 8% 24% 35% 25% 6%
2 KIM Rachael 1% 8% 26% 36% 23% 5%
3 BINDER Sylvie A. - - - - 4% 28% 67%
3 SCRUGGS Lauren S. - - - - 1% 16% 82%
5 FANG Sabrina - - 2% 11% 31% 41% 15%
6 RIVANO Camilla - - - 2% 20% 78%
7 CHO Sabrina N. - - 3% 17% 41% 39%
8 SHEN Sophia H. - 1% 7% 24% 36% 25% 6%
9 TAN Helen - - - 4% 28% 67%
10 CAO Arianna L. - 2% 11% 30% 39% 19%
11 ZHANG Yunjia - - 1% 9% 28% 41% 20%
12 HORSLEY Asherah - - 1% 8% 29% 43% 18%
13 ZHENG Vivian - - 3% 13% 32% 36% 15%
14 CONWAY Josephina (JoJo) J. - - 2% 12% 31% 38% 16%
15 SHEN Lydia - 3% 13% 29% 33% 18% 4%
16 SENIC Adeline - 5% 19% 33% 29% 12% 2%
17 KOENIG Charlotte R. - 5% 19% 34% 29% 12% 2%
18 KIM Katherine 1% 6% 23% 35% 26% 9% 1%
19 CHENG Evelyn - - 1% 4% 19% 41% 35%
20 LEE Brianna J. - 1% 7% 22% 36% 27% 8%
21 DAVIA Daniella V. - 4% 17% 33% 32% 13% 1%
22 ANDREYENKA Yana 1% 8% 25% 38% 24% 5%
23 ZHENG Ivy - 3% 15% 33% 34% 14%
24 LEE Allison (Allie) - 2% 13% 30% 34% 17% 3%
25 JING Emily - - 1% 9% 29% 40% 19%
26 JO Mia C. - 4% 18% 34% 30% 13% 2%
27 QIAN Crystal - 2% 9% 25% 35% 24% 6%
28 NOTT Adrienne (Adi) M. - - 3% 14% 32% 35% 15%
29 PARK Rowan M. 1% 10% 28% 35% 21% 5%
30 GEBALA Gabrielle Grace A. 1% 8% 25% 38% 24% 5%
31 FREEDMAN Miranda W. 1% 6% 24% 40% 26% 3%
32 DEBACK Greta I. 7% 27% 35% 22% 7% 1% -
33 KLINE Melissa C. - 6% 20% 34% 28% 11% 1%
34 CASTANEDA Erika L. - 3% 14% 32% 34% 16% 3%
35 EYER Hailey M. - 2% 12% 33% 37% 15% 2%
36 TSAI Xiao-Qing E. - - 1% 7% 26% 41% 25%
37 LEE Yejine - 2% 12% 28% 34% 19% 4%
38 LEE Alina - - 2% 10% 30% 40% 19%
39 KOO Rachel A. - - 2% 13% 33% 37% 14%
40 GAYDOS Sofia C. 3% 16% 33% 32% 14% 2%
41 CHO Rebecca H. 7% 31% 39% 19% 3% -
42 KOKES Gabrielle 1% 11% 31% 38% 17% 2%
43 LEE Annora Y. - - 2% 12% 30% 38% 18%
44 KNIGHT Skylar - 1% 6% 22% 38% 27% 7%
45 HE Elizabeth W. - - - 3% 17% 44% 36%
46 OH Erin H. 1% 6% 20% 33% 27% 11% 1%
47 RANDOLPH Piper 27% 41% 24% 7% 1% - -
48 LESLIE Ryanne T. - - 2% 10% 30% 40% 18%
49 LI Rachel Y. 3% 16% 33% 31% 14% 3% -
50 LUNG Katerina - - 1% 7% 25% 40% 26%
51 APELIAN Katherine - - 3% 14% 32% 35% 14%
51 LUU Shanon K. 20% 42% 28% 9% 1% - -
51 LIU Jaelyn A. 1% 5% 19% 33% 29% 12% 2%
54 LEVIN Eve A. 1% 9% 29% 36% 20% 5% -
55 MILLER Naomi E. 2% 12% 31% 35% 17% 3%
56 BREKER Anika 1% 6% 21% 37% 28% 7%
57 PEVZNER Victoria - 3% 16% 35% 34% 12%
58 BATRA Chaahat 7% 28% 38% 21% 5% -
59 CHEN Allison V. 1% 6% 22% 36% 26% 9% 1%
60 GALAVOTTI Claire Teresa - 5% 18% 35% 31% 11% 1%
60 ANDREYENKA Hanna - - 3% 13% 31% 37% 16%
62 ZHANG Alina C. - 5% 20% 33% 28% 11% 2%
63 XUE Alanna L. 5% 22% 36% 27% 9% 1% -
64 TAN Kaitlyn N. 1% 11% 32% 39% 16% 1%
65 GUERRA Sofia E. 4% 18% 34% 29% 12% 2% -
66 MCGILLION-MOORE Katie - 4% 19% 36% 29% 10% 1%
67 GRIFFIN Emma G. - 1% 7% 23% 39% 27% 4%
68 CHUSID Mikayla - 1% 9% 25% 35% 24% 6%
69 HALL Velma - 5% 19% 33% 29% 12% 2%
70 CHEN Jia P. - 2% 9% 27% 36% 21% 4%
71 CHEN Jessie S. 3% 14% 30% 32% 17% 4% -
72 LI Phoebe J. - 6% 26% 42% 24% 2%
73 SEAL Grace (Gracie) C. 10% 32% 36% 18% 4% -
74 SARTORI Taylor M. 1% 10% 27% 35% 22% 5% -
75 HO Brianna W. - 2% 11% 28% 35% 20% 4%
75 PAHLAVI Dahlia 7% 26% 36% 23% 8% 1% -
77 JANG Kimberley - 3% 14% 30% 32% 16% 3%
78 OUYANG Bridgette Z. 2% 11% 27% 33% 21% 6% 1%
79 DING Abigail 7% 27% 36% 22% 7% 1% -
80 TUCKER ALARCON Ariadna C. - 1% 6% 22% 36% 28% 8%
81 SUN Ruoxi 3% 17% 33% 30% 14% 3% -
82 KOROL Neta 1% 9% 31% 37% 18% 3% -
83 YAROSHENKO Karina - - 1% 7% 24% 40% 27%
84 HE Fenghuan 1% 5% 20% 34% 29% 10% -
85 YU Lauren C. 5% 21% 35% 27% 10% 2% -
86 LUO ZIWEN 3% 16% 32% 30% 15% 3% -
87 SHAW Kayla M. 9% 30% 37% 19% 4% -
88 HUNG Juliana K. 2% 12% 30% 34% 18% 4%
89 CHO Taylor S. 14% 36% 33% 14% 3% -
90 STAMOS Maria - 1% 8% 26% 41% 24%
91 KONG Olivia 15% 36% 33% 13% 3% -
91 SABATINI Isabella Ravenne 5% 22% 36% 27% 9% 1%
93 SERBAN Samantha M. 2% 13% 31% 34% 18% 3%
94 FERRETTI Anna Rebecca 17% 38% 31% 12% 2% -
95 WANG Ellen 1% 5% 19% 33% 28% 12% 2%
96 PERLMAN Talia 2% 15% 32% 32% 15% 3% -
97 CHO Cameron S. 1% 7% 27% 39% 22% 5% -
98 KOO Haley B. - - < 1% 3% 17% 42% 37%
99 LOCKE Savannah 1% 9% 27% 35% 22% 6% 1%
100 GU EMILY 21% 40% 28% 9% 1% - -
101 CHO Gracie L. 2% 14% 31% 33% 16% 3% -
102 DE LA CRUZ Eden 8% 28% 35% 21% 6% 1% -
103 SEAL Julie T. 2% 11% 29% 34% 19% 4% -
104 TALAVERA Daena 2% 14% 31% 32% 16% 4% -
105 ZHAO Sophie L. 4% 19% 33% 28% 13% 3% -
105 KHOO Lauren A. 1% 6% 21% 34% 27% 11% 2%
107 MORADI Raiyan N. 37% 45% 16% 2% - - -
108 BRADFORD Meeah 10% 30% 35% 19% 5% 1% -
109 SEO IRENE Y. 21% 39% 29% 10% 2% - -
110 ZHAO Aileen Y. 9% 31% 36% 19% 5% 1% -
111 MI Anning 18% 40% 30% 10% 1% - -
112 HUANG NATALIE 21% 41% 29% 9% 1% -
113 NEWHARD Zelia "Zizi" 2% 15% 33% 33% 14% 2%
114 PENG Amber L. 15% 37% 32% 13% 2% -
115 HE Xiangxin 3% 20% 39% 30% 8% -
116 PROCOPIO Lucia 30% 41% 22% 6% 1% -
117 ADAMS KIM Natalie 6% 24% 36% 25% 8% 1% -
118 WU Julianna Y. 14% 35% 33% 15% 3% - -
119 LIAO Lu Jia (Lucy) 5% 20% 33% 28% 12% 2% -
120 WANDJI Anais 4% 20% 35% 28% 11% 2% -
121 SANTOS Annika Beatrice I. 10% 33% 37% 17% 4% - -
122 LEE Ariana 16% 38% 33% 11% 2% - -
123 KOSTELNY Alexis 8% 27% 34% 22% 7% 1% -
124 UPTON Elizabeth 10% 30% 35% 20% 6% 1% -
124 LI Grace Q. - 4% 18% 34% 30% 12% 2%
126 BOLES Sophia 18% 37% 30% 12% 2% - -
127 XIANG Emma 22% 41% 27% 8% 1% - -
128 FERNANDES Thea 25% 44% 24% 6% 1% - -
129 DU Hannah 12% 35% 35% 15% 2% -
130 YEH Marissa E. 28% 43% 23% 6% 1% - -
131 SHITAMOTO Audrey F. 23% 40% 27% 9% 1% - -
132 GUO Kaitlyn S. 7% 26% 37% 23% 7% 1% -
133 ACHILOVA Feyza 16% 37% 32% 12% 2% -
134 TALWALKAR Apoorva 10% 30% 35% 19% 5% 1% -
135 OLIVEIRA Lavinia M. 45% 39% 13% 2% - - -
136 WONG Sophia M. 8% 29% 36% 20% 5% 1% -
137 DRAGNE Alexis D. 46% 40% 12% 2% - -
138 SLOWINSKI Maia A. 9% 30% 35% 20% 5% 1% -
138 WEBB Ella 25% 44% 24% 6% 1% - -
140 KOROL Dana 23% 40% 27% 9% 1% - -
141 YU Jaime L. 23% 47% 25% 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.