Aydemir, Ayşe Elvan
Performance evaluation is a challenging, multidimensional and multi-criteria assessment problem. One application area is the player transfers in football (soccer), where player performance must be evaluated in-line with their responsibilities on the field. In this area of study, raw player performance statistics are not representative because of the external factors impacting the performance such as time-played, injuries, competition difficulty and characteristics, strength of the opponent, impact of actions in the game as well as the positions played. In addition, transfer market has unique financial dynamics in terms of transfer fees and player valuation. Some of the factors that affect transfer fees are athletic performance, properties of clubs and competitions and player popularity. The rich set of factors makes modelling transfer fees a challenging machine learning problem. This thesis provides a dynamic, context-dependent, probabilistic and hierarchical bottom-up approach for evaluating performance under uncertainty for custom requirements. Furthermore, the proposed framework links the performance metrics and various data sources to model transfer fees using machine learning ensembling methods. The proposed framework is generic and it can be adapted to other team sports.


A Dimension Reduction Approach to Player Rankings in European Football
Aydemir, Ayşe Elvan; Taşkaya Temizel, Tuğba; Temizel, Alptekin; Preshlenov, Kliment; Strahinov, Daniel (2021-08-24)
Player performance evaluation is a challenging problem with multiple dimensions. Football (soccer) is the largest sports industry in terms of monetary value and it is paramount that teams can assess the performance of players for both financial and operational reasons. However, this is a difficult task, not only because performance differs from position to position, but also it is based on competition, time played and team play-styles. Because of this, raw player statistics are not comparable across players...
A metamodeling methodology involving both qualitative and quantitative input factors
Tunali, S; Batmaz, I (Elsevier BV, 2003-10-16)
This paper suggests a methodology for developing a simulation metamodel involving both quantitative and qualitative factors. The methodology mainly deals with various strategic issues involved in metamodel estimation, analysis, comparison, and validation. To illustrate how to apply the methodology, a regression metamodel is developed for a client-server computer system. In particular, we studied how the response time is affected by the quantum interval, the buffer size. and the total number of terminals whe...
Development of the WorkKeys Talent Assessment scales and indices.
Oh, Insue; Toker, Yonca; Ferreter, Jennifer; Whitman, Daniel; Mckinniss, Tamara; Casillas, Alex; Robbins, Steven (null; 2008-04-10)
This paper describes the development and validation of a facet-level personality assessment designed for workplace applications. The first portion of the paper details development of the facet-level scales, whereas the second portion of the paper details the development of “compound” scales for predicting job criteria (e.g., teamwork).
A reformulation of the ant colony optimization algorithm for large scale structural optimization
Hasançebi, Oğuzhan; Saka, M.p. (2011-01-01)
This study intends to improve performance of ant colony optimization (ACO) method for structural optimization problems particularly with many design variables or when design variables are chosen from large discrete sets. The algorithm developed with ACO method employs the so-called pheromone scaling approach to overcome entrapment of the search in a poor local optimum and thus to recover efficiency of the method for large-scale optimization problems. Besides, a new formulation is proposed for the local upda...
An adaptive simulated annealing algorithm-based approach for assembly line balancing and a real-life case study
Guden, H.; Meral, Fatma Sedef (2016-05-01)
In this study, we address the deterministic assembly line balancing problem (ALBP) in a multiple product-models environment with multiple objectives. We have been motivated by the assembly line balancing problem of a white goods product production line that is a multi-model type line with 68 stations through which four product-models are assembled, each with approximately 400 precedence relations and 300 tasks. In the plant, to cope with the increasing demand in the medium term, the efficiency of the line i...
Citation Formats
A. E. Aydemir, “A DATA DRIVEN PERFORMANCE EVALUATION FRAMEWORK FOR SPORTS ANALYTICS,” Ph.D. - Doctoral Program, Middle East Technical University, 2021.