Term Project - Predictive and Classification Models for Wins and Playoffs

Term Project Prepared by Dong Ye
Enter your Student ID in the Keywords Properties of this document
Prepared for Dong Ye
CMIS2250 Section XXX
Date of Submission: Wednesday, January 18, 2023
Northern Alberta Institute of Technology

Explanation of the Process
The miscellaneous data for each year between 2010 and 2018 was downloaded and compiled under one
excel workbook. The data for 2010 to 2017 was put in the worksheet source data while the data for
2017-2018 season was placed in the subject worksheet. Arena, L, PW, PL, MOV, SOS, and SRS data was
remove from both worksheets. The age and win columns were interchanged to allow the independent
variables to be placed together in a continuous manner. The playoffs column was inserted before the
win column in both worksheets. The assessment column provided in this document were copied and
pasted in the final predictive model and classification model worksheet. The playoffs data was gather
from the same website as the source and subject data using the following link Playoffs Data Source. The
data for playoffs was entered manually into source worksheet and the final classification model
worksheet.
Justification of Model Choice
Three models were created for predictive assessment as well as for classification assessment. The
models were assessed individuals with regard to (adjusted) R-squared, and the significance of the model
and coefficients at alpha =0.05. The first model format for both predictive and classification assessment
was a simple linear regression with a single independent variable age i.e. y=β0 + β1 x . Hence the two
models can be presented as follows:
Playoffs ( y)=β0+ β1 Age
Wins( y)= β0 + β1 Age
The second model format for both predictive and classification assessment was a multiple-linear
regression model with several independent variables i.e. y=β0 + βi xi where i=1,2 ,... . Hence the two
models can be presented as follows:
Playoffs ( y ) =β0 + β1 Age+ β2 ORtg+ β3 DRtg+ β4 NRtg+ β5 Pace+ β6 Ftrr+ β7 3 PAr
Wins ( y )=β0 + β1 Age+ β2 ORtg+ β3 DRtg+ β4 NRtg+ β5 Pace+ β6 Ftrr+ β7 3 PAr
The third model format for both predictive and classification assessment was also a multiple-linear
regression model with several independent variables associated with TS%, defensive and offensive
statistics i.e. y=β0 + βi xi where i=1,2 ,... . Hence the two models can be presented as follows:
Where the subscripts O=offensive and D=Defensive
Playoffs ( y ) =β0 + β1 TS %+ β2 eFG %O + β3 TOV %O + β 4 ORB %O + β5
FT
FGA O
+ β6 eF G %D + β7 TOV %D + β8 DRB %D
Wins ( y )=β0 + β1 TS %+ β2 eFG%O + β3 TOV %O + β4 ORB %O + β5
FT
FGA O
+ β6 eFG %D + β7 TOV %D + β8 DRB %D + β9
The third model was select to be final mode because it was superior to the other two model formats
with regard to r-squared value, and number of significant coefficients. The model was further modified
Dong Ye