November NAC

Cadet Women's Saber

Saturday, November 10, 2018 at 4:00 PM

Kansas City, MO - Kansas City, MO, 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 STRZALKOWSKI Aleksandra (Ola) M. - - - 3% 17% 43% 37%
2 KONG Vera - - - 2% 19% 53% 26%
3 MILLER Sky - - - 1% 10% 38% 50%
3 KIM Zoe - 1% 8% 25% 36% 24% 5%
5 AVAKIAN Mikaela - - 1% 6% 23% 42% 28%
5 MOYA Keona L. - - - 2% 13% 39% 45%
7 WILLIAMS Jadeyn E. - - 1% 8% 26% 40% 24%
8 CHEEMA Sophia - 1% 15% 39% 35% 10% 1%
9 GREENBAUM Atara R. - - 1% 9% 27% 40% 22%
9 SKARBONKIEWICZ Magda - 1% 8% 25% 36% 24% 6%
11 LEE Alexandra B. - - - 5% 32% 62%
12 HE Charlotte 5% 19% 32% 28% 13% 3% -
13 KOZAK Sonja A. - - 3% 16% 34% 34% 12%
14 GUTHIKONDA Nithya - - 2% 9% 26% 39% 24%
15 TAO Hannah J. 1% 6% 23% 36% 27% 7%
16 GORDON Tamar 2% 12% 27% 31% 20% 7% 1%
17 GOUHIN Chloe - - - - 3% 25% 73%
18 DI PERNA Chiara I. - - 3% 16% 34% 33% 13%
18 OISHI Megumi - - 1% 7% 27% 42% 22%
20 SULLIVAN Siobhan R. - - 5% 19% 36% 31% 9%
21 BERMAN Stella - 1% 5% 17% 33% 33% 13%
22 LIANG Megan - - 2% 10% 28% 39% 21%
22 KIM Catherine - 3% 16% 33% 32% 13% 2%
24 FREEDMAN Janna N. - - 2% 13% 34% 38% 13%
25 FAHRI Monir J. - - 1% 7% 32% 51% 10%
26 HARRISON Imogen N. - - - 4% 20% 43% 32%
27 KOVACS Sophia - - - 4% 24% 52% 18%
28 OLSEN Natalie J. 2% 12% 28% 33% 20% 6% 1%
29 TANG Catherine H. 2% 20% 37% 28% 10% 2% -
30 SUNGA Arabella Krystienne M. - 4% 15% 33% 34% 14%
31 FLOREZ Melissa - 4% 17% 34% 31% 12% 1%
32 MANUBAG Amanda R. - 5% 31% 42% 19% 3%
33 CHAN Leanne - - 1% 9% 33% 45% 11%
34 WHANG Rebecca - - 1% 8% 27% 41% 24%
35 KATZ Anat - - 4% 15% 32% 34% 14%
36 KALRA Himani V. - - 1% 7% 31% 52% 11%
37 ZIELINSKI Isabella G. 1% 6% 20% 34% 29% 10% 1%
38 TZOU Alexandra 2% 17% 36% 32% 11% 1%
39 ROH Rachel E. - 4% 18% 39% 31% 7%
40 GREENBAUM Ella K. - 2% 16% 40% 35% 7%
41 YANG Kaitlyn H. - 1% 12% 31% 35% 17% 3%
42 SECK Chejsa-Kaili F. - - - 2% 14% 43% 40%
43 CHING Sapphira S. - 1% 9% 26% 36% 23% 5%
44 PARKER Allegra H. 1% 8% 24% 34% 24% 8% 1%
45 CASHMAN Natalie 2% 12% 28% 33% 20% 5% -
46 POSSICK Lola P. - - 3% 14% 35% 36% 12%
47 BEALE Zoe M. - 4% 17% 32% 30% 14% 2%
48 CARVALHO Isabela A. - 2% 9% 24% 34% 24% 6%
49 MATAIEV Natalie S. 2% 16% 37% 32% 10% 1% -
50 HUNTER Nina B. 5% 21% 34% 26% 11% 2% -
51 LIM Isabel K. - 2% 13% 33% 36% 14% 2%
52 REDDY Shreya - 1% 9% 27% 36% 22% 4%
53 TANG Annie L. - 6% 22% 37% 28% 7%
54 BLUM Leah I. 1% 8% 26% 37% 23% 5%
55 LACSON Sarah 4% 23% 37% 26% 8% 1%
56 OXENSTIERNA Carolina 1% 36% 44% 17% 2% -
57 NOBREGA Carolina S. 3% 24% 41% 26% 6% -
58 LARIMER Katherine E. 1% 12% 34% 38% 14% 2% -
58 LU Vivian Y. - - 2% 10% 29% 40% 20%
60 TIMOFEYEV Nicole 3% 14% 29% 31% 18% 5% -
61 TONG Kunling - 1% 4% 17% 35% 33% 10%
62 SCALAMONI-GOLDSTEIN Charlotte S. 1% 8% 25% 34% 23% 7% 1%
63 KALRA Siya L. 1% 8% 27% 36% 22% 6% 1%
64 MARSEE Samantha 1% 6% 23% 38% 27% 6%
65 LI Anna M. - - 5% 24% 43% 24% 4%
66 LIU Rachel 1% 7% 23% 34% 25% 9% 1%
67 CODY Alexandra C. - - 4% 17% 33% 33% 13%
67 BUCHMANN Vivien - - 5% 25% 42% 23% 4%
69 CAO Stephanie X. - - 3% 17% 42% 38%
70 LAMOTHE Laurie-Ann - 6% 29% 39% 21% 5% -
71 CHAN Audrey - - 1% 6% 23% 41% 29%
72 HULSEBURG Kaitlyn - - 1% 7% 26% 43% 24%
73 PRIESTLEY Catherine (Cate) C. - 2% 9% 25% 35% 24% 6%
74 KOBERSTEIN Maggie - 2% 17% 39% 32% 8% 1%
75 HOOGENDOORN Sterre - 2% 11% 30% 36% 18% 3%
76 CHIN Erika J. - 1% 9% 25% 35% 23% 6%
77 WILLIAMS Chloe C. 4% 21% 37% 28% 9% 1%
78 HAN Jeanette X. 2% 12% 28% 32% 19% 6% 1%
78 SATHYANATH Kailing - 2% 9% 25% 34% 24% 6%
80 CANNON Sophia E. - 4% 17% 32% 31% 13% 2%
81 RIZKALA Joanna 4% 19% 34% 29% 12% 2% -
82 HOOGENDOORN Levi - 4% 16% 32% 32% 14% 2%
82 KIM Emily - 5% 20% 34% 28% 11% 2%
82 TUCKER Iman R. - 2% 11% 29% 35% 19% 4%
85 KONG Isabel - 3% 12% 27% 33% 20% 5%
86 SHAY-TANNAS Zoe 3% 15% 32% 31% 15% 3% -
87 YAP Madeline - - 1% 11% 36% 44% 7%
88 CHIOLDI Mina - 3% 18% 35% 30% 11% 2%
89 KALINICHENKO Alexandra (Sasha) - 4% 22% 40% 26% 6% -
90 XU Ellen - 2% 12% 31% 37% 17%
91 ATLURI Sara V. - 4% 18% 34% 30% 12% 2%
92 YONG Erika E. - 1% 5% 19% 38% 31% 6%
93 FEARNS Zara A. - 5% 17% 32% 30% 14% 2%
94 PAK Kaitlyn - - 6% 25% 40% 24% 5%
95 DELSOIN Chelsea C. 2% 11% 29% 34% 19% 5% -
96 JULIEN Michelle 1% 8% 27% 35% 22% 6% 1%
97 STONE Hava S. - - 1% 10% 34% 41% 14%
98 SHOMAN Jenna - - - 1% 10% 36% 53%
99 SZETO Chloe 7% 37% 39% 14% 2% - -
100 THROWER Lola S. - - 5% 20% 37% 30% 9%
100 KRYLOVA Valery - 4% 14% 29% 32% 17% 4%
103 GORMAN Victoria M. 1% 13% 32% 33% 17% 4% -
104 WEBER Juliana I. - 5% 21% 36% 27% 9% 1%
104 BOIS Adele 5% 21% 35% 27% 10% 2% -
106 GAJOWSKYJ Sophie K. - 4% 27% 45% 22% 3% -
107 SHIN Andrea Y. - 1% 9% 29% 39% 20% 3%
108 FOUR-GARCIA Madison - - - 1% 10% 40% 49%
109 MERRIAM Katherine I. 1% 13% 32% 33% 17% 4% -
110 ANDRES Katherine A. - 4% 28% 42% 22% 4% -
111 D'ORAZIO Isabella 7% 24% 34% 24% 9% 2% -
112 SADOVA Olga 4% 19% 34% 29% 12% 2% -
113 KOBOZEVA Tamara V. - 6% 24% 39% 24% 5% -
114 DARINGA Arianna - 2% 13% 31% 34% 17% 3%
115 SHOMAN Miriam 2% 14% 34% 33% 15% 2%
116 SCHMITT Alana P. 4% 19% 34% 28% 12% 2% -
117 CALVERT Sarah-Jane E. 1% 11% 30% 33% 19% 5% 1%
118 BUHAY Rachel T. 3% 19% 39% 29% 9% 1% -
119 BAWA Sanya 7% 25% 36% 24% 7% 1% -
120 YUN Maya - 1% 10% 28% 35% 21% 5%
120 NEWELL Alexia C. - 2% 12% 29% 34% 19% 4%
122 BAKER Audrey C. 2% 14% 34% 33% 14% 3% -
123 CHEN Erica - 4% 19% 36% 29% 10% 1%
124 BALMASEDA Sabrina F. - 4% 18% 33% 30% 13% 2%
125 FAY Zoe A. 32% 50% 16% 2% - - -
126 LIN Audrey J. - 4% 16% 31% 31% 15% 2%
127 LI Victoria J. 11% 32% 35% 17% 4% -
128 BOURGEOIS audreane 1% 10% 26% 33% 22% 7% 1%
129 ZINNI Kaylyn M. 1% 21% 45% 27% 6% -
130 LUKASHENKO Angelina 17% 38% 31% 12% 2% -
131 WIGGERS Susan Q. - 3% 14% 29% 32% 18% 4%
132 ABOUDAHER Janna A. - 3% 23% 41% 27% 5% -
133 BHATTACHARJEE Rhea 8% 27% 35% 22% 7% 1% -
134 ROGERS Pauline E. 11% 33% 35% 17% 4% - -
135 BROWN Emma 1% 7% 22% 33% 26% 10% 1%
136 LIN Zhiyin 35% 45% 17% 3% - - -
137 CHEN Jacqueline 13% 34% 34% 16% 4% - -
138 SPORN Melanie 13% 34% 34% 16% 4% - -
139 CALLAHAN Chase J. 10% 29% 34% 20% 6% 1% -
140 ANDRES Charmaine G. 12% 32% 33% 17% 4% 1% -
140 SUN Alyssa 4% 21% 39% 27% 8% 1% -
142 YURT Leyla 8% 27% 35% 22% 7% 1% -
143 BENOIT Adelaide L. 17% 36% 30% 13% 3% - -
144 BELTRAN Emilia M. 7% 26% 36% 23% 7% 1% -
145 SUBRAMANIAN Nitika - 2% 20% 47% 27% 3%
146 BENTOLILA Thalia 53% 36% 9% 1% - -
147 FERRARI-BRIDGERS Marinella O. 41% 40% 15% 3% - -
148 BAE EMMELINE 4% 23% 41% 25% 6% 1% -
149 YANG Ashley M. 4% 18% 33% 30% 13% 3% -
150 MCMAHON Byronie 27% 45% 22% 5% - - -
151 VAN ATTA Grace Y. 2% 13% 36% 35% 13% 1% -
151 CHEN Xinyan 7% 30% 40% 19% 3% - -
153 BENTOLILA Yedida 10% 40% 35% 13% 2% - -
154 GULATI Ria 13% 36% 35% 14% 2% - -
155 LU Amy 19% 38% 30% 11% 2% - -
156 ALFARACHE Gabriella C. 6% 24% 35% 25% 9% 2% -
157 KIM Sujin 24% 47% 24% 5% - - -
158 ULIBARRI Nevaeh L. 19% 39% 30% 11% 2% - -
159 CHEN Jane 4% 20% 34% 28% 12% 2% -
160 SLOBODSKY Sasha L. 7% 30% 40% 19% 4% - -
161 HURST Kennedy 1% 10% 26% 33% 22% 7% 1%
162 ZHANG Judy 10% 37% 36% 14% 2% - -
163 PRIEUR Lauren 3% 16% 32% 30% 15% 3% -
164 PANIGRAHI Sophia 21% 43% 28% 7% 1% - -
165 TODD Phoebe 33% 45% 18% 3% - - -
165 MUNGOVAN Cecilia C. 42% 46% 11% 1% - - -
167 PATEL Riya 1% 10% 28% 34% 21% 6% 1%
168 HUANG Tina 33% 50% 15% 2% - - -
169 WANG Jianning 8% 33% 38% 17% 3% - -
170 HOVERMAN Hannah A. 44% 40% 14% 2% - - -
170 PIERCE Marlene 24% 40% 26% 8% 1% - -
172 LIN Selena 9% 30% 35% 20% 5% 1% -
173 ENDO Miyuki N. 13% 39% 36% 11% 1% - -
174 HAYES Grace Y. < 1% 3% 16% 35% 32% 13% 2%
175 FU Linqian (Helen) 30% 41% 22% 6% 1% - -
175 NEIBART Fiona 2% 21% 38% 28% 10% 2% -
175 KITTLE Lauren 68% 31% 1% - - - -
175 ZENG Xiaoyi 45% 39% 13% 2% - - -
179 ALCEBAR Kayla 2% 12% 30% 33% 18% 4% -
180 CONGIUSTA Aelex 92% 8% - - - -
181 KOLL-BRAVMANN Ryder S. 35% 53% 12% 1% - - -
181 CUNNINGHAM Erin 47% 47% 6% - - - -
181 HOLMES Emma 75% 23% 3% - - - -
184 BAKER Amelia M. 46% 41% 12% 1% - - -
184 LIGH Karis 46% 41% 12% 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.