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Development of a prediction model fo...

Long, Joseph Charles.

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Development of a prediction model for the NCAA Division-I Football Championship Subdivision.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Development of a prediction model for the NCAA Division-I Football Championship Subdivision./
Author:	Long, Joseph Charles.
Description:	35 p.
Notes:	Source: Masters Abstracts International, Volume: 51-06.
Contained By:	Masters Abstracts International51-06(E).
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1536350
ISBN:	9781303045745

Development of a prediction model for the NCAA Division-I Football Championship Subdivision.
Long, Joseph Charles.

Development of a prediction model for the NCAA Division-I Football Championship Subdivision. - 35 p.

Source: Masters Abstracts International, Volume: 51-06.

Thesis (M.S.)--North Dakota State University, 2013.

This thesis investigates which in-game team statistics are most significant in determining the outcome in a NCAA Division-I Football Championship Subdivision (FCS) game. The data was analyzed using logistic and ordinary least squares regression techniques to create models that explained the outcome of the past games. The models were then used to predict games where the actual in-game statistics were unknown. A random sample of games from the 2012 NCAA Division-I Football Championship Subdivision regular season was used to test the accuracy of the models when used to predict future games. Various techniques were used to estimate the in-game statistics in the models for each individual team in order to predict future games. The most accurate technique consisted of using three game medians with respect to total yards gained by the teams in consideration. This technique correctly predicted 78.85% of the games in the sample data set when used with the logistic regression model.

ISBN: 9781303045745Subjects--Topical Terms:

517247
Statistics.

Development of a prediction model for the NCAA Division-I Football Championship Subdivision.
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020 $a 9781303045745
035 $a (MiAaPQ)AAI1536350
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100 1 $a Long, Joseph Charles. $3 2095057
245 1 0 $a Development of a prediction model for the NCAA Division-I Football Championship Subdivision.
300 $a 35 p.
500 $a Source: Masters Abstracts International, Volume: 51-06.
500 $a Adviser: Rhonda C. Magel.
502 $a Thesis (M.S.)--North Dakota State University, 2013.
520 $a This thesis investigates which in-game team statistics are most significant in determining the outcome in a NCAA Division-I Football Championship Subdivision (FCS) game. The data was analyzed using logistic and ordinary least squares regression techniques to create models that explained the outcome of the past games. The models were then used to predict games where the actual in-game statistics were unknown. A random sample of games from the 2012 NCAA Division-I Football Championship Subdivision regular season was used to test the accuracy of the models when used to predict future games. Various techniques were used to estimate the in-game statistics in the models for each individual team in order to predict future games. The most accurate technique consisted of using three game medians with respect to total yards gained by the teams in consideration. This technique correctly predicted 78.85% of the games in the sample data set when used with the logistic regression model.
590 $a School code: 0157.
650 4 $a Statistics. $3 517247
650 4 $a Business Administration, Sports Management. $3 1669318
690 $a 0463
690 $a 0430
710 2 $a North Dakota State University. $b Statistics. $3 2095058
773 0 $t Masters Abstracts International $g 51-06(E).
790 $a 0157
791 $a M.S.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1536350