USA Fencing National Championships & July Challenge

Div I Women's Épée

Sunday, June 30, 2019 at 8:00 AM

Columbus, OH - 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 VERMEULE Emily - - - 1% 11% 38% 49%
2 GUZZI VINCENTI Margherita A. - - - 2% 11% 37% 50%
3 VIE Natalie J. - 1% 7% 25% 41% 25%
3 WANG Elizabeth 2% 10% 25% 32% 22% 7% 1%
5 LIANG Jessica - 1% 4% 15% 32% 34% 14%
6 PARK Faith K. - 1% 8% 27% 42% 22%
7 SCANLAN Susannah (Susie) 1% 7% 22% 33% 26% 10% 1%
8 KHROL Jaclyn - 1% 5% 19% 36% 31% 8%
9 BASSA Francesca A. - - 1% 7% 24% 40% 26%
10 CEBULA Anne - 4% 14% 28% 31% 19% 5%
11 BEDDINGFIELD Claire E. - 1% 5% 19% 35% 31% 10%
12 LURYE Sarah - 2% 9% 24% 34% 24% 7%
13 BULAVKO Sonia 4% 21% 37% 28% 9% 1%
14 WATRALL Christina - 4% 18% 38% 32% 7%
15 KOMAR Sofia - 2% 10% 29% 39% 20%
16 GRADY Miriam A. - 4% 19% 36% 31% 9%
17 WASHINGTON Isis - - - 1% 11% 41% 47%
18 DANIEL Chloe L. - 3% 14% 30% 33% 17% 2%
19 DING Jiahe (Heidi) - 1% 7% 22% 35% 27% 8%
20 TONCHEVA Victoria M. 1% 9% 26% 35% 22% 6% 1%
21 YAMANAKA Mina 1% 7% 24% 36% 25% 7% 1%
22 CANDREVA Greta H. - - - 1% 12% 40% 46%
23 KUKADIA Sancchi K. - 5% 17% 32% 30% 14% 2%
24 JOYCE Michaela - - 3% 15% 40% 42%
25 TOBY Natalia R. 4% 20% 35% 28% 11% 2%
26 SHEFFIELD Lake Mawu 1% 6% 21% 35% 28% 9%
27 KETKAR Ketki - 1% 8% 23% 34% 26% 8%
28 HUSISIAN Hadley N. - - 2% 10% 30% 41% 18%
29 CHOI Lyla 4% 18% 34% 30% 12% 2% -
30 WANG Karen - 5% 20% 34% 28% 11% 2%
31 HU Grace 4% 18% 31% 28% 15% 4% -
32 CONSTANTINO Lola - - 3% 15% 33% 35% 13%
33 ZAFFT Tatiana M. 1% 8% 24% 34% 24% 8% 1%
34 PIRKOWSKI Amanda L. - 1% 5% 18% 33% 31% 12%
34 LIN Jessica Y. - - - 1% 11% 39% 48%
36 BATES Cassandra L. - 1% 8% 22% 34% 26% 8%
36 RAUSCH Ariana (Ari) M. - 1% 8% 23% 34% 26% 8%
38 MCFADDEN Christa M. 1% 9% 25% 34% 23% 7% 1%
39 LEE Sumin 2% 15% 34% 32% 14% 2%
41 OXENREIDER Tierna A. 2% 13% 31% 33% 17% 3% -
42 GARINA Ania (Ganusia) 3% 15% 30% 30% 17% 5% 1%
43 CHIMAHUSKY Rebecca - - 4% 16% 33% 33% 13%
44 YEFREMENKO Dariya (Dasha) (Dasha) - 5% 17% 32% 30% 13% 2%
45 GANDHI Sedna S. - 3% 14% 30% 32% 17% 4%
46 CHOY LeeAnn 1% 9% 24% 32% 23% 9% 1%
47 GUO ZI SHAN - - - 1% 7% 34% 58%
49 ROBLES Elena 2% 11% 26% 32% 21% 7% 1%
50 KWON Athina 3% 14% 29% 31% 17% 5% 1%
51 MALDONADO Pilar I. 3% 16% 33% 31% 14% 3% -
52 TANIBAJEVA Rachel L. 1% 10% 28% 37% 21% 4%
52 ZUHARS Renee A. 4% 20% 36% 29% 10% 1%
54 GAO Emily L. 1% 6% 21% 36% 28% 8%
55 ZOZULYA Christina S. - 1% 4% 17% 36% 34% 9%
56 BOYS Nishta B. - 1% 6% 22% 39% 27% 6%
57 ROSS Naomi O. 1% 5% 18% 31% 29% 14% 3%
58 LEE Hanna Y. 3% 15% 29% 30% 17% 5% 1%
59 KHAMIS Yasmine A. - - 2% 11% 27% 38% 22%
60 BALAKRISHNAN Monica S. 3% 17% 34% 30% 13% 3% -
60 LU Junyao 1% 6% 20% 33% 27% 11% 2%
62 GAO Aretha R. 3% 15% 30% 31% 17% 4% -
63 MCLANE Lauren 1% 6% 19% 32% 28% 12% 2%
64 ENO Megan E. 1% 8% 24% 36% 25% 6%
65 KUNJAN Lena R. 16% 38% 32% 12% 2% - -
66 MANGANO Ariana J. - - 3% 14% 36% 38% 8%
67 HEDVAT Alexis S. 1% 10% 29% 35% 19% 4% -
68 GAO Cindy 1% 6% 19% 32% 28% 12% 2%
69 SHAMSIAN Shaya 5% 23% 36% 26% 9% 1% -
70 TYLER Syd 1% 8% 22% 32% 25% 10% 2%
71 SNIDER Margot (Maggie) 1% 9% 24% 34% 24% 8% 1%
72 O'REILLY Aeryn E. 2% 15% 33% 33% 15% 2% -
73 YEU Irene - 1% 5% 20% 37% 31% 7%
74 BARNA Isabella 3% 17% 35% 32% 12% 1%
75 WU Amelia 2% 15% 33% 33% 15% 2%
76 LEE Olive 28% 42% 23% 6% 1% -
77 MONTOYA Kimberlee C. 1% 7% 25% 38% 24% 5%
78 KIMURA Kimberley H. 6% 25% 38% 24% 6% 1%
79 BEITTEL Chloe F. 1% 6% 21% 35% 27% 9% 1%
80 KIM Diane E. 1% 9% 25% 32% 23% 8% 1%
81 NGUYEN Kaylin A. 4% 19% 33% 28% 13% 3% -
82 KULKARNI Diya 1% 9% 24% 33% 23% 8% 1%
83 PYO Yunice 4% 17% 31% 30% 15% 4% -
84 TAYLOR Audrey Y. 4% 18% 33% 29% 13% 3% -
84 LEE Michelle 7% 26% 35% 23% 8% 1% -
86 NIXON Caroline (Karolina) L. - 2% 11% 27% 34% 21% 5%
86 PROCTOR Sara J. 1% 5% 18% 31% 29% 14% 3%
88 CAMPBELL Anahit M. 6% 22% 34% 26% 10% 2% -
89 LEUNG Natalie - 3% 13% 28% 32% 19% 5%
90 KANG Dahyun 9% 28% 35% 21% 7% 1% -
91 DROVETSKY Alexandra M. 2% 14% 31% 32% 17% 4% -
92 MARTUS Cosima O. 4% 18% 31% 28% 14% 4% -
93 WANG anne 17% 36% 31% 13% 3% - -
94 WOLF Isabella A. 22% 40% 27% 9% 1% -
95 PROVENZA Hannah G. 1% 5% 20% 36% 29% 9%
97 LEANG Andrea K. 7% 26% 35% 23% 7% 1% -
98 O'DONNELL Amanda A. - 5% 19% 32% 28% 12% 2%
99 DESAMOURS Sabine I. 3% 15% 31% 31% 16% 4% -
100 FILIPPOV Nika D. 12% 34% 34% 16% 3% - -
101 RUNIONS Emersyn 4% 19% 33% 28% 12% 2% -
102 MO Victoria - 2% 9% 24% 34% 24% 7%
103 PATURU Meghana 1% 8% 22% 32% 26% 10% 2%
104 KETKAR Mallika 1% 10% 27% 35% 22% 5% -
105 DUNLAP-SMITH Azaline I. 1% 9% 26% 35% 23% 6% -
106 COBERT Helen G. 9% 29% 35% 21% 6% 1% -
107 MEHROTRA Anya 10% 30% 34% 19% 5% 1% -
108 YOON Julia J. 8% 26% 35% 22% 7% 1% -
109 WU Fan 22% 40% 28% 9% 1% - -
110 LEE kyungmin 3% 19% 36% 30% 11% 1%
111 BARRY Julia E. - 3% 16% 35% 34% 12%
112 LIN Katie Y. 13% 35% 34% 15% 3% -
113 LAANSOO Karen 34% 41% 20% 5% 1% -
113 DIB Vanessa 18% 40% 30% 10% 2% -
113 GREGORY Elizabeth 4% 20% 35% 28% 11% 2%
116 CHU Audrey 8% 28% 36% 21% 6% 1% -
117 WHITTEMORE Lucy K. 5% 22% 34% 27% 10% 2% -
118 GRESHAM Sarah L. 6% 23% 34% 25% 10% 2% -
120 WANG Nora 7% 24% 34% 24% 10% 2% -
121 MACHULSKY Leehi 1% 9% 27% 35% 21% 5% -
122 GRESHAM Rebekah L. 3% 16% 32% 30% 14% 3% -
122 RATZLAFF Jocelyn T. 1% 7% 23% 35% 25% 8% 1%
124 HILL Gabrielle (Gabby) M. 7% 26% 37% 23% 7% 1% -
125 LEANG Priscilla Y. 15% 34% 31% 15% 4% 1% -
126 ADAMS KIM Madeline 1% 7% 22% 32% 26% 10% 2%
127 MCNEILL Claire A. 4% 19% 33% 28% 13% 3% -
128 CHAN Cheri K. 6% 24% 36% 25% 8% 1% -
129 MYERS Helen Sophia A. 24% 40% 26% 9% 2% - -
130 BROOKS Tean R. 5% 20% 33% 28% 12% 2% -
131 BELSLEY Devon K. 3% 16% 33% 31% 14% 2% -
131 NI Emma 13% 33% 33% 16% 4% 1% -
133 MOHABIR Ariane 11% 35% 35% 15% 3% -
134 BINDAS Blodwen S. 6% 22% 33% 26% 11% 2% -
135 LIVERANT Jordan S. 11% 33% 36% 17% 3% -
136 BRILL Sophie 4% 20% 34% 28% 11% 2% -
137 LIN Anna F. 26% 41% 25% 7% 1% - -
138 DUNSEATH Lauren M. 3% 16% 30% 30% 16% 4% -
139 LAWSON Marie A. 7% 28% 36% 22% 6% 1% -
139 KIM Elizabeth Y. 36% 41% 18% 4% 1% - -
141 MYERS Jeanelle Christina A. 10% 32% 36% 18% 4% - -
142 WEISS Talia L. 4% 18% 31% 28% 14% 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.