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nflpass

nflpass

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Author: Roger W. Johnson Source: [StatLib](http://lib.stat.cmu.edu/datasets/) Please cite: National Football League Passes Dataset listing all-time NFL passers through 1994 by the NFL passing efficiency rating. Associated passing statistics from which this rating is computed are included. The dataset lists statistics for 26 players. The first 25 are the top 25 all-time career best rating leaders recognized by the NFL. The 26th player, Otto Graham, has statistics which include his performance in the All-America Football Conference (1946-1949) which is not recognized by the NFL. The statistics given are current through the 1994 regular season. Only passers with a minimum of 1,500 career passing attempts are included. The NFL describes how to compute its rating in its 1977 document "National Football League Passer Rating System" (410 Park Avenue, New York, NY 10022-4444, (212) 758-1500) through the use of tables. No formula is explicitly stated for rating. But, examining the tables in the "National Football League Passer Rating System" one can infer that NFL passer rating is [5(Completion Percentage-30)/6] + [10(Touchdown Percentage)/3] + [25(19-2(Interception Percentage))/12] + [25(Yards/Attempts-3)/6] where it is understood that the values within each set of square brackets are truncated to be no smaller than zero and no larger than 475/12. This implies a minimal rating of 0 and a maximal rating of 475/3 or about 158.3. If 30% < Completion Percentage < 77.5% 0% < Touchdown Percentage < 11.875% 0% < Interception Percentage < 9.5% 3 < Yards per Attempt < 12.5, which is true of most passers having a reasonable number of passing attempts, then the rating formula simplifies to [25 + 10(Completion Percentage) + 40(Touchdown Percentage) - 50(Interception Percentage) + 50(Yards/Attempt)]/12 (see Johnson (1993, 1994). Note that the weights on interception percentage and yards per attempt are greatest in magnitude, closely followed by touchdown percentage. The weight on completion percentage is a distant fourth in magnitude. ### Classroom Use of this Data Using the NFL data from Meserole (1995), for which the above inequalities hold, one can uncover (at least approximately) the simplified rating formula using multiple regression. Students can be told that NFL rating is "based on performance standards established for completion percentage, average gain, touchdown percentage and interception percentage" (Meserole (1995)), but the actual formula for rating is not widely publicized. Once the rating formula is uncovered, one can see the relative weights that the NFL assigns to these four performance standards (see Barra and Neyer (1995) for an alternative). Also, by citing unusual passers who don't satisfy the above inequalities an instructor can remind students of the dangers of extrapolation when building regression models. Here are a few such unusual passers: Name Attempts Completions Yards Touchdowns Interceptions Rating Rypien 3 3 15 0 0 87.5 Marshall 1 1 81 1 0 158.3 Muster 1 0 0 0 1 0.0 The data for Arthur Marshall, a wide-receiver for Denver, and for Brad Muster, a full-back for Chicago are from the 1992 season. The data for quarterback Mark Rypien is for his performance at one point during the 1995 season (see _USA Today_, Thursday September 28, 1995, 9C). One might also try tracking down the passing (not receiving!) records of Jerry Rice for the 1995 season as he apparently threw for a touchdown in the regular season finale. ### Variables (from left to right) Passing Attempts Passing Completions Passing Yards Touchdowns by Passing Interceptions NFL Rating (usually to the nearest tenth, sometimes to the nearest hundredth to eliminate ties that would result when only given to the nearest tenth) Name of NFL Player ### References Barra, A. and Neyer, R. (1995), "When rating quarterbacks, yards per throw matters", _The Wall Street Journal_, Friday, November 24, B5. Johnson, R. (1994), "Rating quarterbacks: An amplification", _The College Mathematics Journal_, vol. 25, no. 4, p. 340. Johnson, R. (1993), "How does the NFL rate the passing ability of quarterbacks?", _The College Mathematics Journal_, vol. 24, no. 5, pp. 451-453. Meserole, M., editor, (1995), "The 1996 Information Please Sports Almanac", p. 265.

7 features

NFL_Rating (target)numeric26 unique values
0 missing
Passing_Attemptsnumeric26 unique values
0 missing
Passing_Completionsnumeric26 unique values
0 missing
Passing_Yardsnumeric26 unique values
0 missing
Touchdowns_by_Passingnumeric26 unique values
0 missing
Interceptionsnumeric24 unique values
0 missing
Name_of_NFL_Player (ignore)nominal26 unique values
0 missing

107 properties

26
Number of instances (rows) of the dataset.
7
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
6
Number of numeric attributes.
1
Number of nominal attributes.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .001
Average number of distinct values among the attributes of the nominal type.
0.35
First quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Standard deviation of the number of distinct values among attributes of the nominal type.
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .001
0.68
Mean skewness among attributes of the numeric type.
44.17
First quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Error rate achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.lazy.IBk
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .001
2080.95
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.lazy.IBk
Percentage of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.36
Second quartile (Median) of kurtosis among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 2
Entropy of the target attribute values.
Kappa coefficient achieved by the landmarker weka.classifiers.lazy.IBk
Number of instances belonging to the most frequent class.
-0.52
Minimum kurtosis among attributes of the numeric type.
1149.48
Second quartile (Median) of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump
Maximum entropy among attributes.
82.92
Minimum of means among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump
4.89
Maximum kurtosis among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0.41
Second quartile (Median) of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.REPTree -L 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump
26901.62
Maximum of means among attributes of the numeric type.
The minimal number of distinct values among attributes of the nominal type.
0
Percentage of binary attributes.
440.14
Second quartile (Median) of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
0.27
Number of attributes divided by the number of instances.
Maximum mutual information between the nominal attributes and the target attribute.
0.3
Minimum skewness among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
The maximum number of distinct values among attributes of the nominal type.
4.12
Minimum standard deviation of attributes of the numeric type.
0
Percentage of missing values.
1.18
Third quartile of kurtosis among attributes of the numeric type.
-0.02
Average class difference between consecutive instances.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 1
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .00001
2.14
Maximum skewness among attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
85.71
Percentage of numeric attributes.
9441.96
Third quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .00001
10185.97
Maximum standard deviation of attributes of the numeric type.
Number of instances belonging to the least frequent class.
14.29
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
Error rate achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .00001
Average entropy of the attributes.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes
First quartile of entropy among attributes.
0.88
Third quartile of skewness among attributes of the numeric type.
Kappa coefficient achieved by the landmarker weka.classifiers.trees.DecisionStump -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Kappa coefficient achieved by the landmarker weka.classifiers.trees.RandomTree -depth 2
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.J48 -C .0001
0.53
Mean kurtosis among attributes of the numeric type.
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes
-0.47
First quartile of kurtosis among attributes of the numeric type.
3564.87
Third quartile of standard deviation of attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Error rate achieved by the landmarker weka.classifiers.trees.J48 -C .0001
5506.07
Mean of means among attributes of the numeric type.
Average mutual information between the nominal attributes and the target attribute.
Kappa coefficient achieved by the landmarker weka.classifiers.bayes.NaiveBayes
118.86
First quartile of means among attributes of the numeric type.
Area Under the ROC Curve achieved by the landmarker weka.classifiers.trees.REPTree -L 1
Error rate achieved by the landmarker weka.classifiers.bayes.NaiveBayes -E "weka.attributeSelection.CfsSubsetEval -P 1 -E 1" -S "weka.attributeSelection.BestFirst -D 1 -N 5" -W
Error rate achieved by the landmarker weka.classifiers.trees.RandomTree -depth 3
Kappa coefficient achieved by the landmarker weka.classifiers.trees.J48 -C .0001

5 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: NFL_Rating
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: NFL_Rating
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task