Data
fifa

fifa

active ARFF CC0: Public Domain Visibility: public Uploaded 02-01-2023 by Sebastian Fischer
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Data Description The datasets provided include the players data for the Career Mode from FIFA 22. It only includes male football players with known wage. The goal is to predict the wage of the player based on his attributes. Attribute Description The features describe self-explanatory properties and skills of the player.

29 features

wage_eur (target)numeric133 unique values
0 missing
agenumeric29 unique values
0 missing
height_cmnumeric49 unique values
0 missing
weight_kgnumeric58 unique values
0 missing
nationality_namenominal163 unique values
0 missing
overallnumeric47 unique values
0 missing
potentialnumeric46 unique values
0 missing
attacking_crossingnumeric88 unique values
0 missing
attacking_finishingnumeric94 unique values
0 missing
attacking_heading_accuracynumeric89 unique values
0 missing
attacking_short_passingnumeric86 unique values
0 missing
attacking_volleysnumeric88 unique values
0 missing
skill_dribblingnumeric92 unique values
0 missing
skill_curvenumeric89 unique values
0 missing
skill_fk_accuracynumeric90 unique values
0 missing
skill_long_passingnumeric85 unique values
0 missing
skill_ball_controlnumeric88 unique values
0 missing
movement_accelerationnumeric84 unique values
0 missing
movement_sprint_speednumeric83 unique values
0 missing
movement_agilitynumeric79 unique values
0 missing
movement_reactionsnumeric67 unique values
0 missing
movement_balancenumeric79 unique values
0 missing
defending_standing_tacklenumeric88 unique values
0 missing
defending_sliding_tacklenumeric88 unique values
0 missing
goalkeeping_divingnumeric71 unique values
0 missing
goalkeeping_handlingnumeric69 unique values
0 missing
goalkeeping_kickingnumeric79 unique values
0 missing
goalkeeping_positioningnumeric77 unique values
0 missing
goalkeeping_reflexesnumeric70 unique values
0 missing
Show all 29 features

19 properties

NumberOfInstances
19178
Number of instances (rows) of the dataset.
NumberOfFeatures
29
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
28
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
AutoCorrelation
-5714.89
Average class difference between consecutive instances.
PercentageOfMissingValues
0
Percentage of missing values.
Dimensionality
0
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
96.55
Percentage of numeric attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
3.45
Percentage of nominal attributes.
Show all 19 properties

1 tasks

Supervised Regression on fifa
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: wage_eur
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