Capitol Clash SYC/RCC & Y8

Y-14 Women's Foil

Sunday, January 14, 2024 at 8:00 AM

Gaylord National Resort and Convention Center - National Harbor, MD, 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 PARK Lina - - - 1% 14% 49% 36%
2 DAVIS Logan - - - 4% 20% 45% 30%
3 SHIM Grace J. - - - - 2% 20% 78%
3 TANG Melody Fujiao - - 1% 7% 24% 41% 27%
5 ZOU Ella - - - 1% 12% 41% 45%
6 PEVZNER Nicole - - - - 2% 22% 77%
7 FENG Grace - - - - 3% 27% 70%
8 BORGES Valeryn - - 1% 5% 23% 43% 28%
9 MCSHERRY Ava - - - - 2% 20% 78%
9 WANG CAROL - - 1% 5% 21% 42% 32%
11 WANG Joanna - - - 1% 9% 38% 51%
12 HAFEZ Tahiyah - - - 2% 17% 48% 33%
13 WANG SIQI - - - 1% 13% 48% 37%
14 OH Ceana - - 1% 5% 24% 45% 25%
15 LI Alice - - 3% 20% 44% 30% 3%
16 SHMUKLER Maria - - - 4% 29% 46% 20%
17 JOO Natalie - - - 5% 32% 45% 18%
18 ZELDIN Nadia - - - 1% 13% 49% 37%
19 PAULUS Sloane E. - - - - 2% 21% 77%
20 WANG Amabel - - - 3% 17% 42% 38%
21 LI Han (Helina) - - 1% 6% 26% 43% 24%
22 KRAHE Annika - 1% 9% 28% 38% 20% 3%
23 SIROTA Francis - 3% 17% 36% 33% 10%
24 DONG Angela - - - 3% 24% 47% 26%
25 KAPRAN Anastasia - - - 3% 19% 45% 33%
26 ZHANG Lian - 1% 7% 26% 39% 23% 4%
27 PARK Zena - 1% 7% 24% 37% 25% 6%
28 SHTEPA Rada - 5% 23% 40% 25% 6% -
29 HARRIS Julia - - 1% 6% 27% 45% 22%
30 LI Joy - 1% 10% 28% 37% 20% 4%
31 SHENG Katherine - 1% 10% 31% 39% 18%
32 WANG Sophia - 5% 22% 38% 28% 7%
33 FIELD Elizabeth - - - 1% 11% 40% 48%
34 BERGEL Daphne - 2% 11% 30% 35% 18% 3%
34 DIMATULAC Elise Ann - - 3% 15% 34% 35% 12%
36 MCSHERRY Kayla - 4% 18% 37% 30% 9% 1%
37 BROWN Lola - - 1% 5% 21% 42% 31%
38 HUSSIAN Annabelle - 3% 16% 35% 33% 11% 1%
39 JIANG Chloe - 3% 13% 31% 36% 16% 1%
40 LI Savannah 1% 6% 21% 35% 28% 9% -
41 CHERNYKH Elina - - 1% 8% 34% 49% 8%
42 ZOLDAN Gweniveve A. - - 2% 11% 33% 42% 13%
43 YU Jane - - 2% 11% 32% 40% 16%
44 LIN Yunong - 1% 5% 19% 39% 32% 4%
45 HUANG Sophie - 2% 13% 37% 34% 13% 2%
46 ZAMLYNNY Maya - 1% 7% 29% 46% 16% 2%
47 ORRINGER Lottie - 1% 8% 28% 38% 21% 4%
48 TSIMIKLIS Aphrodite - 1% 5% 19% 35% 31% 9%
49 BADLANI Diya 1% 5% 19% 33% 29% 12% 2%
50 LEE Jeemin - 1% 11% 31% 38% 17% 2%
51 EYER Brooke 1% 9% 27% 36% 21% 5% -
52 MUMMANENI Samyuta - - 1% 12% 35% 38% 14%
53 XIE Lillian - - 1% 7% 25% 42% 25%
54 WANG DINA C. - 2% 11% 30% 37% 18% 1%
55 ORBE-AUSTIN Nia 5% 24% 38% 25% 8% 1% -
56 MCFARLANE Asha - 2% 13% 34% 36% 13% 1%
57 SONG Erin 1% 6% 23% 37% 25% 7% 1%
58 LI Xiang (Shining) - 4% 24% 44% 24% 4% -
59 LI Azalea 2% 14% 34% 34% 14% 2% -
60 YACOBUCCI Nadia - 2% 11% 30% 36% 18% 3%
61 ORBÉ-AUSTIN Maya - 4% 21% 41% 29% 6% -
62 MONTANO Victoria 12% 35% 34% 15% 3% - -
63 ZHANG Zoey 1% 9% 29% 37% 19% 4% -
64 CULLIVAN Sienna - - 1% 11% 35% 41% 11%
65 MAGALLANES GABRIELA - - 2% 12% 34% 40% 12%
66 VENZON Makena Jane 1% 16% 40% 32% 10% 1% -
67 CHUNG Stella 8% 28% 37% 22% 6% 1% -
68 FENG Audrey - - 2% 16% 42% 34% 5%
69 SHIN Elizabeth 1% 8% 26% 37% 23% 6% -
70 KIM Claire 3% 19% 37% 30% 10% 1% -
71 HOROWITZ Shuli 6% 23% 35% 26% 9% 2% -
72 CUI alivia - 2% 11% 29% 36% 19% 3%
73 TEPMAN Alexandra D. 3% 16% 32% 32% 15% 3% -
74 BING Charlotte - - 3% 18% 39% 32% 8%
75 FRASER Morgan - 3% 17% 39% 33% 8% -
76 MARTIN Mila - 1% 9% 29% 39% 18% 3%
77 SHAOOLIAN Maya 1% 7% 23% 36% 27% 7% -
78 KIM Lauren 5% 23% 38% 25% 8% 1% -
79 HU Sophie 2% 20% 43% 30% 4% - -
80 KIM Natalie 5% 31% 41% 19% 3% - -
81 YIN Chloe 1% 13% 35% 35% 14% 2% -
82 PUTHOFF Olivia 1% 12% 32% 34% 17% 4% -
83 SAMALA Reese 19% 39% 30% 10% 2% - -
84 BERTOLINI Mia 15% 39% 34% 11% 2% - -
85 CANO Sofia 2% 19% 40% 30% 8% - -
86 TAN Isabella 2% 13% 37% 36% 11% 1% -
86 LU Zoe 13% 38% 34% 13% 2% - -
88 VIJAYAKUMAR Diya 1% 10% 31% 36% 18% 3%
89 LEE Allison 5% 30% 43% 19% 3% - -
90 CAO Kayla 1% 5% 19% 34% 29% 10% 1%
91 WU Maggie Lei 1% 7% 23% 35% 26% 8% -
92 LIU Caydence 1% 7% 23% 34% 25% 8% 1%
93 WU Lorena - 1% 6% 25% 39% 24% 5%
94 RAFFAELE Nancy 17% 44% 30% 8% 1% - -
95 OLAWOYE Jadesola 4% 25% 42% 23% 5% 1% -
95 HUFFMAN Yunia 8% 46% 36% 9% 1% - -
97 DONG Iris - 1% 8% 25% 37% 24% 5%
97 FU Pui Lam (Paisley) 2% 11% 29% 35% 20% 4% -
99 BAULIN Zoya 11% 41% 36% 11% 1% - -
100 PEVZNER Sophia 58% 34% 7% 1% - - -
101 WATSON Evelyn 4% 26% 43% 24% 3% - -
101 JUVVADI Aanika 1% 12% 35% 36% 14% 2% -
103 MEITZEN Havah 17% 40% 31% 10% 1% - -
104 KATS Ekaterina 6% 27% 38% 22% 6% 1% -
105 LEO Jenna 12% 42% 35% 10% 1% - -
106 ZOLDAN Nolabelle 6% 25% 37% 24% 7% 1% -
107 BALIN Sophia 26% 45% 24% 5% - - -
108 DE CASTRO Kai 14% 40% 33% 11% 2% -
109 BO Iris 4% 22% 41% 27% 6% - -
110 RIVERA Leahy 1% 19% 45% 28% 6% - -
111 SELSER Ella 1% 12% 32% 34% 17% 4% -
112 NWODO Naila 23% 44% 26% 6% 1% - -
113 OCAMPO Emily 16% 42% 32% 9% 1% - -
114 BOIKE Lucille - 6% 26% 39% 23% 5% -
115 KNAPP Isabella 8% 28% 35% 22% 7% 1% -
116 SINGH Evangelina 20% 41% 29% 9% 1% - -
117 FEDER Acadia 16% 36% 32% 14% 3% - -
118 ELNAGGAR lily - 3% 15% 34% 32% 13% 2%
119 LICHTENSTEIGER Megan - 2% 12% 33% 37% 14% 2%
120 ALLEN Sophia 6% 32% 42% 18% 2% - -
121 CAVANAGH Emma 40% 42% 15% 2% - -
122 EPSTEIN Naomi 19% 41% 30% 9% 1% - -
123 BRADSHAW Tamira 40% 41% 16% 3% - - -
123 CHOI Cara 42% 43% 13% 2% - - -
125 DINAR Julia 10% 31% 35% 18% 4% - -
126 BARCZAK Rebekah < 1% 1% 11% 34% 40% 12% 1%
126 YOUM Amelia 22% 43% 27% 7% 1% - -
128 BLANKS Campbell 2% 13% 34% 34% 14% 2% -
129 KOSCIK-AQUINO Emily 9% 30% 35% 20% 5% 1% -
130 SHEBL Nadia 5% 24% 41% 25% 6% 1% -
130 DZIWULSKI Elisabeth Claire 12% 33% 34% 17% 4% - -
132 OWEN Alexandra 12% 43% 34% 10% 1% - -
132 GOMEZ Sofia 38% 44% 16% 2% - - -
134 BRUNDIN Olivia 36% 43% 18% 3% - - -
135 MUNOZ Isabella 22% 39% 28% 9% 2% - -
136 MACKINTOSH Quinn 28% 44% 22% 5% 1% - -
137 KUTATELADZE Anna 35% 44% 18% 3% - - -
138 KIM Alison 14% 37% 34% 13% 2% - -
139 YUE SHANNON 20% 42% 29% 9% 1% - -
140 BERGMANN Beatrix 8% 30% 37% 20% 5% - -
141 KIM Sophia 15% 35% 32% 14% 3% - -
142 GANESH Vanshi 58% 35% 6% - - - -
143 LENZ Phoebe 55% 36% 8% 1% - - -
143 GUSTAFSSON Anna 72% 26% 3% - - - -
143 PHAN Logan 50% 40% 10% 1% - - -
146 KAUFFMAN Kyler Tatum 41% 42% 15% 2% - - -

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.