Probability models for the Philippine Tennis Association tournaments
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...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2000
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| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/17005 |
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| Institution: | De La Salle University |
| Language: | English |
| 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. |
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