دانلود رایگان مقاله پیش بینی احتمال پیروزی در کریکت بین المللی مدل رگرسیون لجستیک پویا

abstract

The paper presents a model for forecasting the outcomes of One-Day International cricket matches whilst the game is in progress. Our ‘in-play’ model is dynamic, in the sense that the parameters of the underlying logistic regression model are allowed to evolve smoothly as the match progresses. The use of this dynamic logistic regression approach reduces the number of parameters required dramatically, produces stable and intuitive forecast probabilities, and has a minimal effect on the explanatory power. Cross-validation techniques are used to identify the variables to be included in the model. We demonstrate the use of our model using two matches as examples, and compare the match result probabilities generated using our model with those from the betting market. The forecasts are similar quantitatively, a result that we take to be evidence that our modelling approach is appropriate. © 2015 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

6. Conclusions

In this paper, we present an in-play model for forecasting the winner of One-Day International cricket matches at any point through the game. The modelling approach that we take is one in which the estimated coefficients on covariates are allowed to evolve smoothly as a match progresses. We call this model a dynamic logistic regression (DLR) model. Cross-Validation techniques are used for model identification and the assessment of the forecast accuracy. Furthermore, in two examples, our model produces forecasts similar to those of the betting market.