October NAC

Cadet Women's Saber

Friday, October 27, 2023 at 3:00 PM

Orange County Convention Center - Orlando, FL, 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 XIAO julie - - - 2% 14% 41% 43%
2 MCKEE Brynnley - - - 3% 17% 41% 38%
3 HWANG Gabriela M. - - - 2% 15% 41% 42%
3 ANDRES Charmaine G. - - - - 6% 32% 62%
5 NATH Trisha - - - 4% 20% 43% 33%
6 YOUNG Charlotte G. - 1% 6% 20% 34% 29% 9%
7 TSUI Natalie - - 1% 6% 22% 42% 30%
8 LIN Nicole 1% 6% 21% 36% 29% 8%
9 KER Grace - - - - 5% 30% 64%
10 TSE Angelina - - 1% 8% 25% 40% 26%
11 PAUL Lila - - - - 5% 31% 63%
12 LU Elaine - - - 3% 16% 41% 40%
13 LEE Hannah - - - 1% 7% 33% 60%
14 ANTHONY Alexia B. - - 2% 11% 29% 38% 19%
15 BEVACQUA Aria F. - - - 1% 7% 34% 59%
16 GHAYALOD reya - - - 1% 7% 34% 58%
17 FEIG Sela - - 4% 18% 35% 32% 11%
18 BOYNTON Ainsley - 3% 15% 32% 33% 15% 2%
19 MANKOVA Varvara - 2% 9% 27% 37% 21% 4%
20 SCHIMINOVICH Sophia I. - - 1% 5% 20% 41% 33%
21 YANG Lea - 2% 14% 36% 36% 12%
22 LAURI Keira 3% 18% 36% 31% 11% 1%
23 CHAVAN Arya 2% 16% 37% 32% 12% 1%
24 ZENG Sarah - 1% 9% 28% 36% 21% 4%
25 DANTULURI Shalini - 5% 20% 36% 29% 9% 1%
26 CHIARELLI Valentina - - 2% 11% 30% 39% 18%
27 SHI Julia - 5% 20% 36% 29% 10% 1%
28 BERMAN greta - 2% 14% 32% 34% 16% 2%
29 TABANGAY Heartlyn - 1% 6% 22% 38% 28% 6%
30 MARYASH Samantha - 1% 8% 27% 42% 22%
31 ZHANG XUANYI - 1% 6% 23% 43% 28%
32 WU Helen - 1% 8% 27% 41% 23%
33 MUND Ruth - 4% 17% 37% 33% 9%
34 MANN Sophia J. - 2% 11% 29% 36% 19% 4%
35 WEI JoyAnn - 1% 10% 28% 37% 21% 3%
36 YAO Rainie - 4% 14% 29% 32% 17% 3%
37 ATTIA Jasmine 1% 6% 22% 35% 26% 9% 1%
38 FERNANDEZ Martina - 3% 15% 33% 33% 14% 2%
39 LITTLE Avery 1% 8% 27% 37% 22% 5%
40 STONE Coral 3% 18% 39% 30% 9% 1%
41 CHUNG Hailey - 1% 8% 24% 36% 24% 5%
42 VINOGOROVA Sofiia - 1% 8% 27% 38% 22% 4%
43 SAYSON Andrea - 3% 16% 33% 32% 14% 2%
44 GOMERMAN Sophia - 1% 9% 27% 38% 21% 3%
45 MAKLIN Sofia - 1% 6% 21% 38% 28% 7%
46 FESTA Carina - - 2% 10% 29% 40% 21%
47 ZHANG Sophie - 1% 6% 23% 39% 26% 4%
48 HUANG Rachael - 1% 6% 22% 38% 28% 6%
49 ZHANG Chenfei - 1% 9% 29% 39% 20% 2%
50 CHRISTOTHOULOU Olympia C. - - 2% 11% 30% 38% 19%
51 KHAN Alissa - 2% 12% 32% 37% 16%
52 KURAEVA Vasilisa 1% 10% 28% 36% 21% 4%
53 YU Zhiang - 3% 16% 36% 34% 11%
54 LUKER Sophia - 1% 9% 29% 41% 20%
55 DHAR Layla - 6% 25% 37% 24% 7% 1%
56 BERNARD Kathryn 3% 15% 30% 31% 16% 4% -
57 DAVIDOVA Kira 8% 27% 34% 22% 8% 1% -
58 HALPERIN Elizabeth H. 5% 20% 33% 27% 12% 3% -
59 PABIAN Emilia - 2% 12% 31% 36% 17% 2%
60 SCHAIBLE Sofia L. 1% 7% 21% 33% 26% 10% 2%
61 HAMBAZAZA Liisa - - 4% 15% 33% 34% 13%
62 HUANG Doris 1% 14% 34% 33% 14% 3% -
63 VINOKUR Anita 2% 17% 38% 31% 11% 1% -
64 MERCHANT Aishwarya 4% 21% 37% 28% 9% 1%
65 LIU Sydney - 1% 10% 29% 36% 20% 4%
66 FAVO Isabella - 3% 17% 35% 33% 11%
67 SENOGLU Irmak - - 2% 14% 36% 39% 8%
68 LIU Yifei - - 4% 16% 35% 34% 11%
69 WANG Zidan - 3% 16% 32% 32% 14% 2%
70 NEUMAN Ella 4% 24% 38% 25% 8% 1% -
70 HU Anna - 4% 19% 35% 30% 10% 1%
72 WANG Gloria Ruoyan - 1% 7% 24% 39% 26% 4%
73 JEONG Katie - - 2% 11% 31% 39% 17%
74 WANG Callie 1% 10% 31% 37% 18% 3%
75 JOHNSON Dagny L. - - 3% 16% 42% 39%
76 CAO Sophie 15% 39% 32% 12% 2% -
77 LO Chloe 3% 17% 33% 31% 14% 3% -
78 RAMIREZ Mirka A. - 2% 10% 29% 37% 20% 3%
79 NICHOLAS Eva 9% 31% 36% 19% 5% 1% -
80 MEDVINSKY Alexandra - 3% 16% 34% 33% 12% 1%
81 NAYAK Esha - 3% 16% 34% 33% 13% 1%
82 XIE Nora 2% 12% 30% 33% 18% 5% -
83 KONDEV Elizabeth - 1% 7% 25% 40% 25% 3%
84 GUGALA Hanna - 5% 22% 37% 26% 8% 1%
85 HENRY Soraya S. - 2% 11% 30% 36% 18% 3%
86 LEMUS-IAKOVIDOU ALEXANDRA - 4% 16% 32% 31% 14% 2%
87 MALEK Zolie - 2% 13% 31% 34% 17% 3%
88 ELLIS-FURLONG Ava 24% 44% 25% 6% 1% - -
89 HUAI Delilah - - 3% 17% 42% 38%
90 SO Catelyn - 1% 8% 29% 42% 21%
91 KNOBEL Sophia 9% 30% 36% 20% 5% -
92 LIU Hannah 9% 31% 36% 19% 4% -
93 DAI Olivia - 5% 22% 39% 28% 6%
94 LOO Kaitlyn 3% 18% 36% 31% 11% 1%
95 MUNGUIA Mila 20% 39% 29% 10% 2% -
96 PADANILAM Lily 3% 19% 36% 30% 11% 2% -
97 HU Michelle - 2% 14% 35% 33% 13% 2%
98 TENG EMMA - 5% 20% 34% 28% 11% 1%
99 CROOKS Riley 4% 24% 39% 25% 7% 1% -
100 LEE Lauren 1% 11% 31% 35% 18% 4% -
101 DONG Angel - 4% 20% 37% 29% 9% 1%
101 GOLDIN Nina - 2% 12% 31% 35% 17% 3%
103 HAMMERSTROM Aria 1% 11% 31% 35% 17% 3% -
104 NGUYEN Siena - - 2% 10% 29% 39% 20%
105 LI Alexis 1% 11% 30% 35% 18% 4% -
106 BUHAY Kirsten M. 1% 9% 28% 37% 21% 4%
107 WANG yining - 3% 15% 37% 34% 11%
108 XU Emily T. 3% 17% 36% 31% 12% 1%
109 LATYSHAVA Stephanie 22% 41% 27% 8% 1% -
110 HSU Leah 5% 24% 38% 25% 7% 1%
111 GRULICH Rayaana 1% 11% 30% 36% 19% 4%
112 BAINS Nandini 27% 43% 24% 6% 1% -
113 GUVEN Coco - 4% 20% 36% 29% 10% 1%
114 LIM Jaslene - - 3% 16% 37% 35% 10%
115 LEE Alyson 4% 20% 37% 28% 10% 1% -
116 MARGULIAN Maria 2% 13% 32% 33% 16% 3% -
117 PROBASCO Leila 2% 15% 33% 33% 14% 2% -
117 GOLOVITSER Maya - 5% 21% 36% 28% 10% 1%
119 DIECK Miranda P. 5% 20% 33% 28% 12% 3% -
120 DAMBAL Sasha 1% 6% 22% 35% 26% 9% 1%
121 LOMOTAN Addison 6% 29% 38% 21% 6% 1% -
122 XU Kaylyn 7% 27% 36% 22% 6% 1% -
123 FREEMAN Armine 6% 25% 36% 24% 8% 1% -
124 LI Sonia 11% 35% 35% 16% 3% - -
125 CHIANG Melissa 2% 15% 34% 32% 14% 3% -
126 LEOU Korina - 5% 18% 33% 29% 12% 2%
127 KRIVOSHEEV Alexandra 1% 9% 27% 36% 21% 6% 1%
128 BUSH Bethany 5% 22% 37% 27% 9% 1%
129 BROWN Olivia 1% 7% 22% 33% 26% 10% 1%
130 TURIANO Nadelle 6% 39% 37% 15% 3% - -
131 TA-ZHOU Emma 5% 21% 36% 27% 10% 1% -
132 WANG Jiayi 3% 19% 36% 29% 11% 2% -
133 MONTORIO Lily M. 1% 11% 29% 34% 20% 5% 1%
134 KIM Audrey 27% 45% 23% 5% - - -
135 JEFFORDS Sophia 3% 20% 37% 29% 10% 1% -
136 TAN Kylie 3% 16% 33% 31% 14% 3% -
137 RIFKIN Lielle 49% 39% 11% 1% - - -
138 BLAKE Anna 7% 24% 34% 24% 9% 2% -
139 LUKER Hannah 4% 28% 39% 23% 6% 1% -
140 LOPEZ-ONA Mia 1% 12% 31% 35% 17% 3% -
141 SADANI Jyotika 22% 44% 26% 6% 1% -
142 OU Yixuan 31% 42% 21% 5% - -
143 BORGUETA Madison 28% 42% 23% 6% 1% -
143 HO Sophia 64% 30% 5% - - -
145 MAGITSKY Leila 29% 45% 22% 4% - -
146 BAIREDDY Maya 4% 21% 37% 28% 9% 1% -
147 GARRETT Madrid 5% 21% 33% 27% 11% 2% -
147 WALLER London 5% 28% 38% 22% 6% 1% -
149 DANTULURI Shivani 50% 39% 10% 1% - - -
150 DE SILVA Augusta 3% 20% 37% 28% 10% 1% -
151 CHI Claire 5% 30% 39% 21% 5% 1% -
151 ZOLLER Noelle 3% 14% 29% 31% 18% 5% 1%
153 PANTALEON-MAZOLA Amari 1% 8% 26% 36% 23% 6% 1%
154 ALAMI Amira 33% 42% 20% 5% 1% - -
154 ONG Lauren 33% 42% 20% 4% - - -
156 BROWN Aria 28% 43% 23% 6% 1% - -
157 CHEN Kevy 3% 16% 31% 30% 15% 4% -
158 CUTLER Juliet 56% 35% 8% 1% - - -
159 NAYAK Antara 50% 38% 11% 1% - - -
159 XU Demi 63% 31% 5% - - - -
161 SYED Azra 61% 32% 6% 1% - - -
161 SHEN Emily 29% 42% 22% 6% 1% - -
163 YOUNG Audrey 2% 21% 39% 29% 9% 1%
164 FAN Alexandria 15% 38% 32% 12% 2% -
164 DUDNICK Morgan 4% 21% 38% 28% 8% 1%
166 ELNATAN Mica A. 10% 34% 35% 17% 4% - -
166 PICO DIB Clemance Cristina 47% 39% 12% 2% - - -
168 PROZUMENT Elizabeth 20% 39% 29% 10% 2% - -
168 NGUYEN Madeleine 16% 39% 32% 12% 2% - -
170 DONDERIS Katherine 4% 22% 40% 26% 7% 1% -
171 UEMOTO Lynn 10% 37% 36% 14% 2% - -
171 SVENSSON Siri Lin 73% 24% 3% - - - -
173 KHOST Maeve 30% 41% 22% 6% 1% - -
173 BANGALORE Shriya 54% 36% 9% 1% - - -
173 TISSONE Veronica 32% 43% 20% 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.