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Ko-soto-gari

Based on fight data from 2016 onward.

All scores
1291
High-impact
75.7%
Fight win
92.8%
Avg ELO
1148
Ippon
427
Waza-ari
550
Yuko
314

Common setup techniques

Earlier tagged techniques by the same athlete in fights where this technique scored.

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Men vs women

Where this technique is credited — high-impact % and win % by sex.

Sex Fights High-impact Fight win
Men 770 80.9% 91.5%
Women 521 67.9% 94.9%

Weight divisions

Which divisions use this technique most; compare effectiveness by weight.

Division Fights High-impact Fight win
Men -73 kg
166 76.5% 90.7%
Men -66 kg
130 79.2% 92.9%
Men -81 kg
122 79.5% 92.4%
Men -90 kg
112 83.9% 89.9%
Men -60 kg
105 78.1% 91.3%
Women -57 kg
100 74.0% 95.9%
Women -52 kg
91 70.3% 98.9%
Women -48 kg
85 61.2% 92.6%
Women -63 kg
84 64.3% 91.2%
Men -100 kg
77 89.6% 90.5%
Women -70 kg
71 64.8% 93.0%
Women -78 kg
56 66.1% 98.2%

Average pre-fight ELO when credited with this technique (min 3 fights).

Judoka Avg ELO Fights
MURAO Sanshiro JPN
1472 6
ADAMIAN Arman RUS
1449 3
GRIGALASHVILI Tato GEO
1420 5
IGOLNIKOV Mikhail RUS
1396 5
AUCHECORNE Melkia FRA
1376 3
SHISHIME Ai JPN
1361 4
KOHARA Kenya JPN
1341 3
LUTFILLAEV Sharafuddin UZB
1333 4
YOSHIDA Tsukasa JPN
1330 3
LIMA Ronald BRA
1328 3
PRIMO Gefen ISR
1322 4
CYSIQUE Sarah Leonie FRA
1302 5
AGUIAR Mayra BRA
1289 4
KRASNIQI Distria KOS
1289 4
ORUJOV Rustam AZE
1286 3

Judoka with the most credited fights using this technique.

Judoka Fights Fight win
MACIAS Tommy SWE
8 87.5%
GJAKOVA Nora KOS
8 100.0%
VERSTRAETEN Jorre BEL
7 100.0%
MAISURADZE Luka GEO
7 100.0%
LIPARTELIANI Eteri GEO
7 100.0%
PUPP Reka HUN
7 100.0%
IARTCEV Denis RUS
7 100.0%
SCVORTOV Victor UAE
7 100.0%
MURAO Sanshiro JPN
6 83.3%
GVINIASHVILI Beka GEO
6 100.0%
NAGAYAMA Ryuju JPN
6 100.0%
TORO SOLER Ariane ESP
6 100.0%
GHIGLIONE Giulia ITA
6 100.0%
STARTSEVA Elis RUS
6 100.0%
KRSSAKOVA Magdalena AUT
6 100.0%

Countries

Where credited scorers are from (one count per fight).

Country Fights Share
JPN 147
11.7%
RUS 109
8.7%
FRA 67
5.3%
GEO 56
4.5%
MGL 53
4.2%
ITA 51
4.1%
BRA 49
3.9%
AZE 48
3.8%
GER 42
3.3%
KAZ 40
3.2%
NED 37
2.9%
HUN 36
2.9%

Statistics count IJF-tagged scoring only. Archive grows as more competitions are scraped from 2016 onward.