| dc.contributor.author | Zhang, Deling | |
| dc.description.abstract | Volleyball has become a well-known and competitive sport with physical and technical performances over the years. The game results are determined by some important factors such as players, and the team’s skills to succeed in a championship. In this research, we propose to analyze volleyball data by using a multiple linear regression model and a logistic regression model. We develop a multiple regression model using in-game statistics that explain the point spread of a volleyball game. We also develop a logistic regression model that estimates the probability of a team winning the game based on the in-game statistics. Both of the models are validated and then the point spread model is used to predict the results of a volleyball game replacing the in-game statistics with the averages of the in-game statistics based on the past two previous matches of both teams. Results are given. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Forecasting Point Spread for Women’s Volleyball | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2016-12-23T17:50:17Z | |
| dc.date.available | 2016-12-23T17:50:17Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | http://hdl.handle.net/10365/25890 | |
| dc.subject.lcsh | Volleyball -- Statistical methods. | en_US |
| dc.subject.lcsh | Volleyball for women -- Statistical methods. | en_US |
| dc.subject.lcsh | Logistic regression analysis. | en_US |
| dc.subject.lcsh | Regression analysis. | en_US |
| dc.subject.lcsh | National Collegiate Athletic Association. | en_US |
| dc.subject.lcsh | Volleyball -- Forecasting. | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Science and Mathematics | en_US |
| ndsu.department | Statistics | en_US |
| ndsu.program | Applied Statistics | en_US |
| ndsu.advisor | Magel, Rhonda | |
