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Sumi-gaeshi

Based on fight data from 2016 onward.

All scores
1159
High-impact
81.4%
Fight win
89.2%
Avg ELO
1143
Ippon
269
Waza-ari
675
Yuko
215

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 840 83.0% 89.0%
Women 319 77.4% 89.9%

Weight divisions

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

Division Fights High-impact Fight win
Men -73 kg
203 89.7% 91.7%
Men -66 kg
153 75.8% 93.8%
Men -81 kg
128 82.8% 87.3%
Men -60 kg
123 82.9% 87.5%
Men -90 kg
118 78.8% 82.9%
Men -100 kg
77 84.4% 88.0%
Women -48 kg
67 80.6% 95.4%
Women -63 kg
57 68.4% 88.9%
Women -70 kg
57 77.2% 93.0%
Women -57 kg
52 82.7% 84.3%
Women -52 kg
41 95.1% 90.0%
Women -78 kg
40 65.0% 86.1%

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

Judoka Avg ELO Fights
BEKAURI Lasha GEO
1543 3
GVINIASHVILI Beka GEO
1373 3
BOUKLI Shirine FRA
1357 7
TAMAOKI Momo JPN
1327 5
TOMA Sergiu UAE
1312 3
UNGVARI Miklos HUN
1312 3
MKHEIDZE Luka FRA
1297 3
DE WIT Frank NED
1293 8
ABULADZE Iago RUS
1291 7
KOTSOIEV Zelym AZE
1289 5
CARGNIN Daniel BRA
1289 3
CVJETKO Lara CRO
1277 5
KRPALEK Lukas CZE
1275 7
BAVUUDORJ Baasankhuu MGL
1275 5
RINER Teddy FRA
1274 3

Judoka with the most credited fights using this technique.

Judoka Fights Fight win
STEVENSON Karen NED
14 85.7%
GOMBOC Adrian SLO
13 92.3%
IVANOV Ivaylo BUL
12 100.0%
SHEROV Abubakr TJK
11 100.0%
PELIVAN Petru MDA
10 100.0%
MACIAS Tommy SWE
10 90.0%
GILIAZOVA Sabina RUS
9 88.9%
ISSOUFI Kaila FRA
9 100.0%
NYMAN Marcus SWE
9 100.0%
DE WIT Frank NED
8 87.5%
NIANG Assmaa MAR
8 87.5%
KHYAR Walide FRA
8 100.0%
MUKETE Daniel RUS
8 87.5%
BOUKLI Shirine FRA
7 100.0%
ABULADZE Iago RUS
7 100.0%

Countries

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

Country Fights Share
FRA 102
9.1%
RUS 87
7.8%
AZE 55
4.9%
KAZ 52
4.7%
ESP 41
3.7%
MGL 40
3.6%
GEO 33
3.0%
NED 33
3.0%
GER 31
2.8%
HUN 31
2.8%
SLO 29
2.6%
CZE 27
2.4%

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