Part 3: Soccer Data

This dataset contains several variables for soccer players who have been traded from one club to another. The Trading Value data is in millions of dollars and was obtained in the Year noted. Players are numbered to protect their identities. We have information about players' Playing Percentage across five years, the total Goals scored and number of total game Appearances. A new variable, G/A, divides Goals by Appearance to put all players on the same metric and to account for players who have been playing longer. We also have Age data, information about the primary Foot the player uses, and their Position (whether they primarily play offense or in the midfield). Please answer the following questions about these soccer players.

11. Is there a significant difference in Percentage Playing Time across the 5 years? Perform the appropriate test (and any follow-ups) and report your findings.

12. Is there a significant difference in players' Percentage Playing Time across the 5 years, and also by whether the player is a Midfielder versus a purely Offensive player? Explain your findings.

13a. Do goals by appearance (G/A) and Age predict players' Trading Value? Please run the appropriate test and report your findings.

13b. If we have a new player to this dataset with a G/A ratio of .75 who is 26 years old, how much do we predict her/his Trading Value to be?

14. What happens if you control for whether a player is Left- and/or Both-footed (i.e., NOT Right-footed) in this model?

15. What is the probability of a new player Trading for less than $20 million? $40 million or greater? What is the corresponding Trading Value of a player at a 90% probability level?

(Please zoom in to see data)

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