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# Regression Analysis: National Football League (NFL)

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Case Problem 4: Predicting Winning Percentage for the NFL

The National Football League (NFL) records a variety of performance data for individuals and teams (http://www.nfl.com). Some of the year end performance data for the 2005 season appear on the data disk in the file named NFL Stats. Each row of the data set corresponds to an NFL team, and the teams are ranked by winning percentage. Descriptions for the data follows:

WinPct Percentage of games won

DefYds/G Average number of yards per game given up on defense

RushYds/G Average number of rushing yards per game

PassYds/G Average number of passing yards per game

FGPct Percentage of field goals

TakeInt Takeaway interceptions; the total number of interceptions made by the team's defense

TakeFum Takeaway fumbles; the total number of fumbles recovered by the team's defense

GiveInt Giveaway interceptions; the total number of interceptions thrown by the team's defense

GiveFum Giveaway fumbles; the total number of fumbles lost by the team's defense

Managerial Report

1. Use method of descriptive statistics to summarize the data. Comment on the findings.

2. Develop an estimated regression equation that can be used to predict WinPict using DefYds/G, RushYds/G, PassYds/G and FGPct. Discuss your findings.

3. Starting with the estimated regression equation developed in part (2), delete any independent variables that are not significant and develop a new estimated regression equation that can be used to predict WinPct. Use alpha = 0.05.

4. Some football analysts believe that turnovers are one of the most important factors in determining a team's success. With Takeaways = TakeInt + TakeFum and Giveaways = GiveInt + GiveFum, let NetDiff = Takeaways - Giveaways. Develop an estimated regression equation that can be used to predict WinPct using NetDiff. Compare your results with the estimated regression equation developed in part (3).

5. Develop an estimated regression equation that can be used to predict WinPct using all the data provided.

The data set is given below.

Team Division WinPct TakeInt TakeFum GiveInt GiveFum DefYds/G RushYds/G PassYds/G FGPct
Indianapolis AFC SOUTH 0.875 18 13 11 8 307.1 106.4 256 88.5
Denver AFC WEST 0.813 20 16 7 9 312.9 158.7 201.7 75
Seattle NFC WEST 0.813 16 11 10 7 316.8 153.6 216.1 72
Jacksonville AFC SOUTH 0.75 19 9 6 11 290.9 122.4 199.4 76.7
Carolina NFC SOUTH 0.688 23 19 16 10 282.6 104.9 204.4 76.5
Chicago NFC NORTH 0.688 24 10 15 13 281.8 131.2 125.1 71
Cincinnati AFC NORTH 0.688 31 13 14 6 338.7 119.4 238.8 87.5
New York (A) NFC EAST 0.688 21 7 15 19 308.8 83 165.1 78.6
Pittsburgh AFC NORTH 0.688 15 15 14 9 284 138.9 182.9 82.8
Tampa Bay NFC SOUTH 0.688 17 13 14 9 277.8 114.1 180.6 81.5
Kansas City AFC WEST 0.625 16 15 10 13 328.1 148.9 238.1 81.8
New England AFC EAST 0.625 10 8 15 9 330.2 94.5 257.5 80
Washington NFC EAST 0.625 16 12 11 16 297.9 136.4 194.1 81
Dallas NFC EAST 0.563 15 11 17 14 300.9 116.3 208.8 71.4
Miami AFC EAST 0.563 14 17 16 14 317.4 118.6 206.2 83.3
Minnesota NFC NORTH 0.563 24 11 16 14 323.3 91.7 196.6 73.5
San Diego AFC WEST 0.563 10 10 16 12 309.2 129.5 218.4 87.5
Atlanta NFC SOUTH 0.5 16 13 13 16 325 159.1 167.4 88.9
Baltimore AFC NORTH 0.375 12 14 21 15 284.7 100.3 193 85.7
Cleveland AFC NORTH 0.375 15 8 18 12 316.8 93.9 190.8 93.1
Philadelphia NFC EAST 0.375 17 10 20 14 325.4 89.5 229.8 75.9
St. Louis NFC WEST 0.375 13 14 24 13 350.1 95.9 252.2 87.1
Arizona NFC WEST 0.313 15 11 21 16 295.6 71.1 277.3 95.6
Buffalo AFC EAST 0.313 17 13 16 10 343.5 100.4 157.2 82.9
Detroit NFC NORTH 0.313 19 12 18 12 322.4 91.9 178 79.2
Green Bay NFC NORTH 0.25 10 11 30 15 293.1 84.5 235.4 74.1
New York (N) AFC EAST 0.25 17 19 17 8 327.5 138.1 223.6 83.3
Oakland AFC WEST 0.25 5 14 14 9 330.8 85.6 223.9 66.7
San Francisco NFC WEST 0.25 16 10 21 14 391.2 105.6 118.6 89.7
Tennessee AFC SOUTH 0.25 9 11 14 12 319.4 95.3 224.8 79.3
New Orleans NFC SOUTH 0.188 10 9 24 19 312.1 105.5 208.9 78.1
Houston AFC SOUTH 0.125 7 9 13 11 364 113.5 139.8 76.5

See attached files.

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#### Solution Summary

The solution provides step by step method for the calculation of descriptive statistics and multiple regression model for National Football League (NFL). Formula for the calculation and Interpretations of the results are also included.

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## Regression Equation Questions

The National Football League rates prospects by position on a scale that ranges from 5 to 9. The ratings are interpreted as follows: 8-9 should start the first year; 7.0-7.9 should start; 6.0-6.9 will make the team as backup; and 5.0-5.9 can make the club and contribute. The following table shows the position, weight, time in seconds to run 40 yards, and ratings for 25 NFL prospects (USA Today, April 14, 2000).

a. Develop a dummy variable that will account for the player's position.

b. Develop an estimated regression equation to show how rating is related to position, weight, and time to run 40 yards.

C. At the .05 level of significance, test whether the estimated regression equation developed in part (b) indicates a significant relationship between the independent variables and the dependent variable.

D. Is position a significant factor in the player's rating? Use = .05

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