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NBA-PLAYERS--2016-2019

NBA-PLAYERS--2016-2019

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Stewart
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Context This Dataset was created for an University project in Milan. The goal of the project was to create a Robust Model to predict the All Star Game score for each player. The score is calculated by dividing the players by conference and position held in the field (external or internal), the athletes are ranked in descending order depending on the number of votes taken for each category voter, so as to obtain three different rankings. From these for each player the rank is calculated (1st Position involves Rank = 1, 2nd Position Rank = 2 etc. . . ). With the values obtained then an average is calculated weighed, with weight 0.50 to that of the votes of the fans and 0.25 to the two remaining. Doing this work we have merged some datasets from kaggle (https://www.kaggle.com/noahgift/social-power-nba), basketball-reference.com and hoopshype.com. Obviously for our work we didn't use all of the variables and for a problem of indipendent observations we took only the last seasons' observation for each player. Other analysis could be performed using salary as a target but also a cluster analysis for players or a PCA. We wouldn't be here without the help of others. Thank you Riccardo,Alfredo and Daniel. Some variables: POS1= Main position (some players have a second position called POS2) G= Games played GS= Games started MP= Minutes played FG =Field Goals Per Game FGA=Field Goal Attempts Per Game FG.= Field Goal Percentage X3P= 3-Point Field Goals Per Game X3PA= 3-Point Field Goal Attempts Per Game X3P.= FG on 3-Pt FGAs. X2P =2-Point Field Goals Per Game X2PA =2-Point Field Goal Attempts Per Game X2P.= FG on 2-Pt FGAs. eFG. = Effective Field Goal Percentage FT=Free Throws Per Game FTA = Free Throw Attempts Per Game FT.= Free Throw Percentage ORB = Offensive Rebounds Per Game DRB = Defensive Rebounds Per Game TRB = Total Rebounds Per Game AST = Assists Per Game STL= Steals Per Game BLK = Blocks Per Game TOV = Turnovers Per Game PF = Personal Fouls Per Game PTS =Points Per Game MEAN_VIEWS= Daily views on wikipedia PLAY= If the player played in the all star game

45 features

Seasonstring3 unique values
0 missing
ORBnumeric46 unique values
0 missing
DRBnumeric96 unique values
0 missing
TRBnumeric122 unique values
0 missing
ASTnumeric91 unique values
0 missing
STLnumeric24 unique values
0 missing
BLKnumeric28 unique values
0 missing
TOVnumeric47 unique values
0 missing
PFnumeric41 unique values
0 missing
PTSnumeric248 unique values
0 missing
Salarynumeric832 unique values
62 missing
mean_viewsnumeric1084 unique values
138 missing
FT.numeric370 unique values
47 missing
Conferencestring2 unique values
0 missing
Rolestring2 unique values
0 missing
Fvotnumeric1357 unique values
0 missing
FRanknumeric145 unique values
0 missing
Pvotnumeric85 unique values
159 missing
PRanknumeric51 unique values
159 missing
Mvotnumeric38 unique values
404 missing
MRanknumeric9 unique values
404 missing
Scorenumeric572 unique values
0 missing
Playstring2 unique values
0 missing
FGAnumeric200 unique values
0 missing
Player.xstring660 unique values
0 missing
Player_IDstring660 unique values
0 missing
Pos1string5 unique values
0 missing
Pos2string4 unique values
1396 missing
Agenumeric24 unique values
0 missing
Tmstring30 unique values
0 missing
Gnumeric82 unique values
0 missing
GSnumeric83 unique values
0 missing
MPnumeric344 unique values
0 missing
FGnumeric104 unique values
0 missing
Rknumeric539 unique values
0 missing
FG.numeric331 unique values
4 missing
X3Pnumeric41 unique values
0 missing
X3PAnumeric90 unique values
0 missing
X3P.numeric260 unique values
99 missing
X2Pnumeric85 unique values
0 missing
X2PAnumeric154 unique values
0 missing
X2P.numeric337 unique values
15 missing
eFG.numeric311 unique values
4 missing
FTnumeric76 unique values
0 missing
FTAnumeric89 unique values
0 missing
Show all 45 features

19 properties

NumberOfInstances
1408
Number of instances (rows) of the dataset.
NumberOfFeatures
45
Number of attributes (columns) of the dataset.
NumberOfClasses
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
2891
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
1398
Number of instances with at least one value missing.
NumberOfNumericFeatures
36
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
AutoCorrelation
Average class difference between consecutive instances.
PercentageOfNumericFeatures
80
Percentage of numeric attributes.
PercentageOfMissingValues
4.56
Percentage of missing values.
PercentageOfInstancesWithMissingValues
99.29
Percentage of instances having missing values.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
NumberOfBinaryFeatures
0
Number of binary attributes.
MinorityClassSize
Number of instances belonging to the least frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
Dimensionality
0.03
Number of attributes divided by the number of instances.
Show all 19 properties

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