Transcribed Text
Your assignment is to collect salary and performance data for the players on your NHL team.
Collect your player data for the 2014/15 season and assemble it in an excel file as follows (as
before, any data that you collect will need tobe documented with respect to your source(s))
Column
Category:
A
Player Name
B
Player Salary
C
Games
D
Goals
E
Assists
F
Defence (Dummy variable)
G
Penalty Minutes
H
Leadership (Dummy variable)
Once you r have acquired and assembled your data, you will need to performthe following two
regressions with "Salary" as the dependent variable:
NHL (only use players with at least 20 games played)
Salary ß1 Goals ß2 Assists 3 Defence ß4 Penalty Minutes
Salary ß Goals ß2 Assists ß3 Defence ß4 Penalty Minutes ßs Leadership
Problem #1 (40 points 30 for data and 10 for result presentation)
What are your regression results? Present your team specific set of regression results as in
the examples below:
NHL Regression Results
Salary = $645 198.07 $46,987 02 Goals $67,018 24 Assists $622,819. 75 Defence $788. 62 PIM
(0.000)
(0.000)
(0.000)
.000)
(0.687)
o-value
Salary $756,607 94 $37,798.22 $48, 151.24A+ $592 896 80 D $1,332.97 PIM $1,842 607.82 Leader
(0.000)
(0.000)
(0.000)
(0.000)
(0.462)
(0.000)
Problem #2 (15 points)
Given your results for your NHL team is there variable in these team specific regressions that
you performed which you expected to have a greater/differen impact on salaries? Why?
Problem #3 (25 points)
Suppose that
Salary
$756,607 94- $37,798. $48. 151.24A $592 896.80 D $1,332.97 PIM . $1 ,842,607.82 Leader
(0.000)
(0.000)
(0.000)
(0.000)
(0.462)
(0.000)
continues to represent the 2014/2015 NHL as whole. Calculate (in your excel file) each of
your players estimated salary based on their 2014/2015 performance. Which players on your
team were overpaid? Which players on your team were underpaid.
For example, for the Buffalo Sabres (partial numbers from different season)
Name
2011 Salary
Estimated Salary
Difference (actual est
Effect
Jason Pominville
5500000
5787670
-287670
underpaid
Thomas Vanek
6400000
5197948
1202052
overpaid
Drew Stafford
4000000
4738401
738401
underpaid
Tyler Ennis
875000
2219793
-1344793
underpaid
ChristianEhrhoff
10000000
2775930
7224070
overpaid
Ville Leino
6000000
1856237
4143763
overpaid
Brad Boyes
4000000
1773264
2226736
overpaid
Tyler Myers
875000
2330171
-1455171
underpaid
Luke Adam
737500
1597441
859941
underpaid
Paul Gaustad
2500000
3252008
-752008
underpaid
Andrej Sekera
4250000
1920418
2329582
overpaid
Marc-Andre Gragnani
550000
1890307
1340307
underpaid
Problem #4 (20 points)
Can you think of variable that we might have left out that could help explain the variation in
salary? What variable did youthink of and why might it be related to how players are paid in
the NHL?
These solutions may offer step-by-step problem-solving explanations or good writing examples that include modern styles of formatting and construction
of bibliographies out of text citations and references. Students may use these solutions for personal skill-building and practice.
Unethical use is strictly forbidden.
Problem #1
NHL Regression Results
The relationship between dependent variable Salary and independent variables Goals, Assists, Defence, and Penalty Minutes (Defence is Dummy Variable) can be described by the linear equation:
Salary = -$1119560 + $97931.26 Goals + $53788.06 Assists + $2096591.00 Defence + $24015.14 PIM...