Stats

Player Stats

Updated at: Dec 10, 2019, 7:45 PM (UTC)

Filter stats by Games played

0
0
5
5
Player
Team
GP
PTS
PPG
P-VAL
P-VALPG
S-EFF
S-VAL
S-VALPG
HGL
HGLPG
D5
T5
1PTM
1PTA
1PT%
2PTM
2PTA
2PT%
FTM
FTA
FT%
DNK
BS
KAS
BZR
DRV
REB
REBPG
OREB
DREB
TO
TOPG
1Aurelijus PukelisŠakiai5397.828.15.60.7228.15.681.640273871%1520%101191%21302357.0102581.6
2Steve SirEdmonton5377.429.65.90.8029.65.940.8004667%143441%5683%0030191.82720.4
3Marijus UzupisŠakiai5316.220.54.10.6620.54.130.610132162%72232%44100%01101204.061420.4
4Dusan BulutNovi Sad3299.723.57.80.8123.57.872.300121771%51242%77100%00502124.021020.7
5Jordan BakerEdmonton5285.616.03.20.5716.03.291.811213954%3933%11100%01305255.071871.4
6Nauris MiezisRiga4266.513.53.40.5213.53.4174.30091850%82928%1333%0080971.81630.8
7Aleksandar RatkovLiman4256.314.53.60.5814.53.651.300131968%21020%81457%01301164.07941.0
8Edgars KruminsRiga4256.313.53.40.5413.53.410.32051242%72627%6875%00001205.011941.0
9Kidani BrutusNY Harlem3227.316.15.40.7316.15.451.70061155%61540%44100%00302103.35541.3
10Dominique JonesNY Harlem3217.012.24.10.5812.24.1103.300102245%41040%3475%0050582.74451.7
11Dušan PopovićUtsunomiya3196.313.94.60.7313.94.662.000172471%000%22100%0020472.33441.3
12Daisuke KobayashiUtsunomiya3186.014.84.90.8214.84.920.7002367%51242%6786%0020020.70220.7
13Mihailo VasicLiman4184.512.13.00.6712.13.041.020182669%010%000%01201164.08871.8
14Cameron d ForteChongming2178.510.75.30.6310.75.363.020172763%000%000%00006136.56742.0
15Šarūnas VingelisŠakiai5173.413.82.80.8113.82.891.80091275%2540%44100%0050451.01420.4
16Jordan Jensen-WhyteEdmonton5173.410.02.00.5910.02.0112.210132259%1520%22100%11405132.66740.8
17Kyle LandryEdmonton5173.48.31.70.498.31.761.220132846%020%4580%01401275.491851.0
18Dimeo van der HorstAmsterdam3175.78.32.80.498.32.872.30091947%31323%2367%00403124.04831.0
19Stefan KojicLiman4164.08.32.10.528.32.1133.3003933%62030%1250%0290292.34551.3
20Dejan MajstorovicNovi Sad3165.310.23.40.6410.23.441.30081457%41136%000%0020282.71720.7
21Aron RoijéAmsterdam3155.09.83.30.659.83.382.71041040%51145%1250%00503155.041162.0
22Maksim KovacevicLiman4153.86.81.70.456.81.730.8104757%32114%55100%00003153.831210.3
23Paulius BeliaviciusŠakiai5142.85.61.10.405.61.1183.60031127%52223%1250%00150361.22440.8
24Goran VidovicShanghai2147.011.55.80.8211.55.873.50044100%51338%000%0030463.02421.0
25Jesper JobseAmsterdam3134.37.72.60.597.72.610.30061155%31030%11100%0010072.34310.3
26Wang JiayiShanghai2136.59.44.70.729.44.752.5005683%41233%000%0000531.50331.5
27Artūrs StrēlnieksRiga4123.06.21.60.526.21.651.31071547%2729%11100%04001256.3101541.0
28Roy KnutsonNew York City2126.09.64.80.809.64.831.5007888%1425%33100%0010231.52121.0
29Emmanuel QuezadaNew York City2126.06.63.30.556.63.394.5007978%21118%1250%0020752.53242.0
30Yuan Bo ZhuWujin2115.55.12.50.465.12.510.51071258%21217%000%0010094.53600
31Agnis ČavarsRiga4112.85.31.30.485.31.351.30091275%090%22100%01202225.571510.3
32Yosuke SaitoUtsunomiya3103.35.31.80.535.31.872.3004580%1714%4757%0040351.71410.3
33Dongyang FengWujin294.54.82.40.534.82.421.00041040%1425%33100%0000231.52142.0
34Sjoerd van VilsterenAmsterdam393.05.41.80.605.41.841.3104944%010%55100%10201103.37331.0
35Marko SavićNovi Sad393.05.01.70.565.01.7103.30071164%1520%000%0280082.72610.3
36Pawel BuczakNew York City294.56.23.10.696.23.152.5104850%2367%1250%1120163.02400
37Marcel EsonwuneNY Harlem393.05.41.80.605.41.882.71091464%000%010%35000206.781210.3
38Marko MilakovićUtsunomiya362.01.70.60.291.70.641.3004757%0120%22100%0040072.32510.3
39Marko ZderoNovi Sad351.72.20.70.452.20.731.0003560%1617%000%0120093.04510.3
40Antoinne MorganoNY Harlem341.31.80.60.441.80.620.7004757%010%010%0020082.71720.7
41Zengjie WangChongming231.50.80.40.250.80.410.5001333%070%22100%0000142.01321.0
42Wang XuefengShanghai231.51.00.50.331.00.531.5002540%000%1425%0210073.51621.0
43Xiaoheng LiuChongming221.00.40.20.220.40.20000010%1813%000%0000021.01100
44Zhenduo LengShanghai221.01.30.70.671.30.742.00022100%010%000%0400094.53642.0
45Shengjie GuChongming210.50.20.10.250.20.110.5001250%020%000%0010021.01100
46Nate BrownNew York City210.50.20.10.200.20.121.0001250%030%000%0020052.52300
47Lu Yi SangWujin210.50.30.10.330.30.110.5001333%000%000%0000163.02452.5
48Nikola PesicWujin1000000011.000000%010%000%00100000011.0

Legend

GP
Games played
PTS
Points scored
PPG
Points per game
P-VAL
Player value
P-VALPG
Player value per game
S-EFF
Shooting efficiency
S-VAL
Shooting value
S-VALPG
Shooting value per game
HGL
Highlights
HGLPG
Highlights per game
D5
Double-fives
T5
Triple-fives
1PTM
One point shots made
1PTA
One point shot attempts
1PT%
One point shot percentage
2PTM
Two point shot made
2PTA
Two point shot attempts
2PT%
Two point shot percentage
FTM
Free throws made
FTA
Free throw attempts
FT%
Free throw percentage
DNK
Dunks
BS
Blocked shots
KAS
Key assists
BZR
Buzzerbeaters
DRV
Drives
REB
Rebounds
REBPG
Rebounds per game
OREB
Offensive rebounds
DREB
Defensive rebounds
TO
Turnovers
TOPG
Turnovers per game

Calculations

P-VAL (Player value)
S-VAL + BS + KAS + BZR - TO + (REB/2)
S-EFF (Shooting efficiency)
PTS / number of shots attempted
S-VAL (Shooting value)
PTS * S-EFF
HGL (Highlights)
DNK + BS + KAS + BZR
D5 (Double-fives)
5 or more in 2 of these 3 categories: PTS-HGL-REB
T5 (Triple-fives)
5 or more in all 3 categories: PTS-HGL-REB

For more information, check the FIBA 3x3 Statisticians' Manual (PDF).