The objective was to build a ranking of football players based on multivariate methods. evaluated were the winners FIFA; UEFA; Ballon D'Or; FIFPro; World Soccer; Golden Ball Cup and King América awards. A total 95 variables: games played, wins, draws, losses, goals scored, yellow/red cards, awards, dream team, title in national leagues/ continental championships club, world cups/ championship O...

Ranking systems are becoming increasingly important in many areas, in the Web environment and academic life for instance. Presumably a ranking helps individuals to make decisions by providing them with relevant information. In a world with a tremendous amount of choices, a ranking plays also the crucial role of influencing the attention that is devoted to the various alternatives. In recurrent ...

We present a cross-benchmark comparison of learning-to-rank methods using two evaluation measures: the Normalized Winning Number and the Ideal Winning Number. Evaluation results of 87 learning-to-rank methods on 20 datasets show that ListNet, SmoothRank, FenchelRank, FSMRank, LRUF and LARF are Pareto optimal learning-to-rank methods, listed in increasing order of Normalized Winning Number and d...