Probability models for the Philippine Tennis Association tournaments

Date of Publication

2000

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Mathematics

College

College of Science

Department/Unit

Mathematics and Statistics

Abstract/Summary

Five probability models namely, the Bradley and Terry Type model, Uniform-Strength Assumption model, Normal-Strength Assumption model and two logistic regression models (using a linear and non-linear function of the player's strength) were compared to determine the best model that will predict the champion in a tournament or the winner in a match of the Philippine Tennis Association (PHILTA) seeded single-elimination tournaments having a balanced structure with a (1, 4, 2, 3) draw. If the players are strictly the ones in the top four seeds, then the logistic regression model using a linear function of the player's strength was proven to be the best model for predicting the champion in the tournament whereas no model was seen appropriate for predicting a winner in a match. On the other hand, if the players are not restricted to the top four seeded players but are paired in such a way that the strongest player competes the weakest, and the second strongest competes with the second weakest, then the logistic regression model using a linear function of the player's strength is still the best one for predicting the champion in the tournament while the Uniform-Strength Assumption model is a good model for the prediction of the winner in a match.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU10033

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

[64] leaves

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