USA Fencing National Championships & July Challenge

Junior Women's Saber

Saturday, June 29, 2019 at 1:00 PM

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 BURKE Nora S. - - - 1% 9% 34% 56%
2 TARTAKOVSKY Elizabeth - - 1% 5% 23% 43% 28%
3 PARKER Abigale B. - 1% 6% 21% 36% 29% 8%
3 AVAKIAN Mikaela - - - - 3% 27% 70%
5 JOHNSON Honor B. - - - - 4% 28% 68%
6 SKARBONKIEWICZ Magda - - 1% 5% 21% 43% 31%
7 GREENBAUM Atara R. - - 3% 13% 34% 37% 12%
8 HARRILL Gillian N. - - 1% 8% 26% 40% 24%
9 FOX-GITOMER Chloe N. - - - 1% 11% 38% 50%
10 MILLER Sky - - - 1% 9% 37% 54%
11 JENKINS Morgan J. - - - 4% 17% 40% 38%
12 DI PERNA Chiara I. - - 1% 9% 39% 51%
13 JENKINS Ryan J. - - - 2% 12% 39% 47%
14 POSSICK Lola P. - 1% 6% 24% 44% 25%
15 STRZALKOWSKI Aleksandra (Ola) M. - - 1% 7% 26% 42% 25%
16 BUCHMANN Vivien - - 3% 14% 35% 37% 12%
17 TURNER Zoe Y. - 1% 8% 24% 35% 25% 7%
18 JOHNSON Edith (Tori) V. - - - 3% 16% 40% 40%
19 CHAN Casey - - 1% 8% 28% 41% 21%
20 GOUHIN Chloe - - 1% 6% 24% 43% 26%
21 ANGLADE Alexis C. - - - 1% 8% 35% 57%
22 THEODORE Maria A. - - - 2% 12% 42% 44%
23 TIMOFEYEV Daniella - - - 1% 8% 34% 57%
24 WILLIAMS Jadeyn E. - - 2% 11% 32% 40% 16%
25 DOHERTY Maverick L. - 3% 15% 33% 33% 13% 2%
26 HIRSCH Sydney R. - - - 4% 18% 43% 35%
27 SHEALY Maggie - - 3% 17% 39% 34% 6%
28 KOVACS Sophia - 2% 10% 28% 37% 19% 4%
29 FOUR-GARCIA Madison - - 4% 17% 36% 33% 10%
30 KIM Zoe - - 3% 14% 32% 35% 15%
31 HANADARI-LEVY Amit - 5% 19% 35% 30% 10% 1%
32 IZENSON Lark (Keli) (Lark) - - - 3% 15% 40% 43%
33 MOYA Keona L. - - - 3% 15% 41% 41%
34 SECK Chejsa-Kaili F. - 1% 8% 29% 39% 20% 3%
35 WALTER Zsofia R. 4% 20% 38% 28% 9% 1% -
36 ZEGERS Anneke E. - - 2% 10% 29% 40% 19%
37 TONG Kunling - - 4% 17% 36% 33% 9%
38 PRIESTLEY Catherine (Cate) C. - 5% 19% 34% 30% 11% 1%
39 LINDER Kara E. - - 3% 17% 45% 35%
40 WU Erica L. 1% 10% 32% 39% 15% 2%
41 KONG Vera - - - 4% 19% 41% 35%
42 SULLIVAN Caroline E. - 1% 6% 19% 34% 30% 10%
43 BLUM Leah I. - 3% 16% 32% 32% 14% 2%
44 CARVALHO Isabela A. - 1% 7% 24% 38% 25% 3%
45 FLOREZ Melissa 2% 16% 35% 32% 12% 2% -
45 KATZ Anat 3% 15% 31% 31% 16% 4% -
47 WILLIAMS Chloe C. - 1% 10% 28% 37% 20% 3%
48 DELSOIN Chelsea C. - 4% 15% 31% 33% 16% 2%
49 LU Vivian Y. - 2% 10% 29% 37% 19% 3%
49 CASHMAN Natalie - 4% 17% 32% 30% 14% 2%
51 CHANG Josephine S. - 1% 6% 24% 38% 25% 6%
51 YONG Annika A. - - 4% 18% 39% 34% 5%
53 BERMAN Stella 1% 8% 26% 36% 22% 6% 1%
53 HOOGENDOORN Levi 2% 13% 30% 32% 17% 4% -
55 PALMER Kristen E. - - 3% 14% 36% 38% 10%
56 KUZNETSOVA Nastassja 8% 27% 35% 22% 7% 1% -
57 KUDRIAVTSEVA Daria - 1% 8% 29% 43% 19%
58 HE Charlotte 8% 29% 38% 20% 4% -
59 OISHI Megumi - 2% 12% 30% 36% 18% 3%
60 YUN Joy - - 2% 12% 30% 38% 18%
61 CHEN Erica 1% 6% 20% 34% 28% 10% 1%
62 GUTHIKONDA Nithya - 2% 11% 27% 34% 21% 5%
63 ZHUANG Sophia 2% 14% 32% 33% 15% 3% -
64 CHAN Audrey 1% 8% 23% 33% 25% 9% 1%
65 LEE Alexandra B. - - 3% 14% 35% 36% 12%
66 DUNGEY Amelia S. 1% 7% 22% 34% 26% 10% 1%
67 CHIN Erika J. - 1% 6% 21% 36% 29% 7%
68 CANSECO Laura K. 2% 13% 32% 35% 16% 3% -
69 BROWN Emma 1% 8% 23% 34% 25% 8% 1%
70 BURCH Makana Y. 11% 31% 34% 19% 5% 1% -
71 KOZAK Sonja A. - 3% 16% 35% 33% 11% 1%
72 SONG Jenny - 1% 7% 23% 37% 26% 5%
73 TZOU Alexandra 1% 6% 22% 34% 26% 9% 1%
74 TUCKER Iman R. 2% 15% 32% 32% 16% 4% -
75 TIMOFEYEV Nicole - 5% 20% 36% 29% 10% 1%
76 MORAN Emma 2% 13% 30% 34% 17% 4% -
77 LIANG Megan - - 2% 13% 34% 37% 13%
78 WEINBERG Alexandra L. - 1% 5% 21% 38% 29% 6%
79 KALRA Siya L. 2% 17% 36% 31% 12% 2% -
79 SULLIVAN Siobhan R. - 1% 10% 32% 38% 17% 2%
79 TIBURCIO Diana 2% 12% 28% 32% 19% 5% 1%
82 CALLAHAN Chase J. 7% 28% 37% 22% 6% 1% -
83 ANDRES Katherine A. 2% 13% 29% 32% 19% 5% -
84 BOIS Adele 1% 12% 33% 34% 16% 3% -
85 KIM Catherine 2% 14% 35% 35% 13% 1%
86 WHANG Rebecca - 1% 10% 33% 43% 13%
87 HARRISON Imogen N. - - 4% 22% 45% 28%
88 LIM Isabel K. 12% 35% 36% 15% 2% -
89 TANG Annie L. 5% 23% 39% 26% 7% 1%
90 SCHMITT Alana P. 14% 39% 33% 12% 2% - -
91 WITEK Sophie B. - - 2% 11% 32% 40% 14%
92 HILADO Sarah 1% 8% 25% 34% 23% 7% 1%
93 BENOIT Adelaide L. 2% 15% 35% 33% 13% 2% -
94 GORMAN Victoria M. 10% 31% 36% 18% 4% - -
95 FAHRI Monir J. - - 4% 15% 32% 35% 14%
96 HUNTER Nina B. - 1% 9% 29% 39% 19% 2%
96 SHEA Erin - 3% 14% 31% 33% 16% 2%
96 SHOMAN Jenna - 1% 6% 23% 38% 26% 6%
99 CHEEMA Sophia 1% 8% 26% 35% 23% 6% 1%
99 YANG Ashley M. 1% 8% 24% 35% 24% 7% 1%
101 WHITE Amber L. - 1% 6% 23% 39% 26% 6%
102 LACSON Sarah - 2% 16% 35% 32% 13% 2%
102 KOO Samantha - 4% 15% 32% 32% 15% 2%
104 BUSTAMANTE Evie I. 1% 7% 22% 34% 26% 9% 1%
104 GULATI Ria 4% 19% 33% 29% 13% 3% -
104 CANNON Sophia E. 6% 24% 37% 25% 8% 1% -
107 LIMB Madeline I. - 5% 23% 39% 26% 6% -
108 SHOMAN Miriam 2% 15% 33% 32% 14% 2% -
109 GREENBAUM Ella K. 1% 12% 32% 34% 17% 4% -
110 KIM Emily 4% 19% 33% 29% 13% 3% -
111 VALADEZ Emily T. 14% 38% 34% 12% 2% -
112 MARSEE Samantha 5% 22% 35% 26% 10% 2% -
113 KALRA Himani V. 1% 11% 29% 35% 19% 5% -
114 NAZLYMOV Tatiana F. 2% 13% 32% 35% 16% 3% -
114 REDDY Shreya - 3% 15% 34% 35% 12% 1%
116 KOBOZEVA Tamara V. 2% 17% 36% 31% 12% 2% -
116 ROH Rachel E. - 5% 20% 36% 29% 9% 1%
118 WU Zoe 26% 43% 24% 6% 1% - -
119 BECCHINA Bridget F. 8% 29% 36% 20% 5% 1% -
120 BEALE Zoe M. 2% 16% 34% 32% 13% 2% -
121 FERRARI-BRIDGERS Marinella O. 12% 35% 35% 15% 3% - -
122 PAK Kaitlyn - 1% 8% 28% 40% 22% 3%
123 CHEN Xinyan 14% 45% 31% 8% 1% - -
124 SATHYANATH Kailing - 4% 18% 34% 31% 12% 2%
125 ALLUM Isabel (Izzy) T. 3% 17% 36% 32% 11% 1%
125 TAO Hannah J. 12% 37% 35% 13% 2% -
127 ZINNI Kaylyn M. 18% 40% 31% 10% 1% -
128 MATAIEV Natalie S. 28% 43% 23% 5% - -
129 VAN ATTA Grace Y. 2% 17% 40% 30% 9% 1% -
130 TURNOF Kayla M. 8% 26% 35% 23% 7% 1% -
130 O'HARA Eimile J. 36% 43% 18% 3% - - -
130 EDGINGTON Grace 3% 17% 33% 30% 13% 3% -
133 LIU Rachel 2% 11% 28% 34% 19% 5% -
134 CHING Sapphira S. 1% 12% 33% 35% 16% 3% -
135 DAHLKEMPER Audrey G. 28% 45% 22% 4% - - -
136 MEIEROVICH Sophie 9% 28% 34% 21% 7% 1% -
137 PINCUS Emma Y. 7% 28% 37% 22% 6% 1% -
138 DEPEW Charlotte R. 20% 43% 28% 8% 1% - -
139 LU Yi Lin 25% 41% 25% 8% 1% - -
140 BAE EMMELINE 22% 42% 27% 8% 1% - -
141 HOOGENDOORN Sterre 1% 7% 24% 37% 24% 7% 1%
141 RHIE Lena 36% 43% 18% 3% - - -
143 DODRILL Brooke 10% 30% 35% 19% 5% 1% -
144 GEYER Carolina M. 18% 37% 30% 13% 3% - -
145 ABOUDAHER Janna A. 17% 40% 31% 11% 2% - -
146 SATHE Mehek S. 24% 41% 26% 8% 1% - -
147 BAKER Audrey C. 15% 36% 33% 13% 3% - -
148 YURT Leyla 23% 43% 27% 7% 1% -
149 STONE Hava S. 1% 9% 27% 36% 21% 5% -
150 PINCUS Lucy Y. 4% 20% 34% 28% 11% 2% -
151 YANG Kaitlyn H. 3% 18% 35% 30% 12% 2% -
152 WEBER Juliana I. 5% 28% 39% 22% 6% 1% -
153 ZHANG Judy 20% 40% 29% 10% 2% - -
154 YUN Maya 6% 24% 36% 25% 9% 1% -
154 BHATTACHARJEE Rhea 1% 14% 38% 33% 12% 2% -
156 MANUBAG Amanda R. 7% 29% 37% 21% 5% 1% -
157 HAN Jeanette X. 11% 33% 35% 16% 4% - -
157 KOBERSTEIN Maggie 3% 17% 33% 30% 14% 3% -
159 GIRARDI Aemilia 53% 38% 8% 1% - - -
160 NEWELL Alexia C. 1% 14% 34% 33% 14% 2% -
161 MILLER Mattea K. 16% 36% 32% 13% 3% - -
162 HULSEBURG Kaitlyn - 1% 9% 27% 37% 21% 3%
163 WANG Caroline Y. 2% 13% 30% 32% 18% 4% -
164 KALINICHENKO Alexandra (Sasha) 3% 21% 40% 27% 7% 1% -
165 SHIN Andrea Y. 3% 17% 33% 30% 13% 3% -
165 LI Anna M. - 1% 8% 25% 38% 24% 5%
165 SHAY-TANNAS Zoe 12% 33% 35% 16% 4% - -
168 NOBREGA Carolina S. 23% 40% 27% 9% 1% - -
169 PRAXL Alexa R. 33% 42% 20% 4% - - -
170 DARINGA Arianna 9% 29% 35% 20% 6% 1% -
171 SUNGA Arabella Krystienne M. 3% 16% 33% 31% 14% 3% -
172 OXENSTIERNA Carolina 4% 19% 34% 28% 12% 3% -
172 D'ORAZIO Isabella 18% 39% 31% 11% 2% - -
174 LU Amy 57% 35% 8% 1% - - -
175 BAWA Sanya 9% 28% 35% 21% 7% 1% -
176 MACKEY Deveraux S. 10% 30% 35% 19% 5% 1% -
177 JULIEN Michelle 6% 24% 36% 24% 8% 1% -
179 IYER Mohini R. 9% 33% 39% 17% 3% -
180 BENTOLILA Thalia 58% 34% 7% 1% - - -
180 ROGERS Pauline E. 32% 48% 18% 2% - - -
180 ZIELINSKI Isabella G. 2% 14% 30% 32% 18% 4% -
180 NI Sharon 9% 31% 37% 19% 4% - -
180 WU Cici 25% 41% 26% 7% 1% - -
185 NEIBART Fiona 36% 41% 19% 4% - - -
185 BENTOLILA Yedida 38% 41% 17% 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.