The recruitment of athletes with limited resources is a global problem in professional sports. In US Major League Baseball, the experience of the Oakland Athletics’ general manager in the last decade turned his “Moneyball” model into a synonym of quantitative analysis in the transfer market of baseball players. His strategy focused on hiring players with outstanding technical skills but relatively low market value. This study adapted this model to the framework of a multiple criteria decision aid (MCDA), by selecting undervalued players who have complementary abilities. The novelty here refers to the joint use of four algorithms explored by the composition of probabilistic preferences (CPP) (i.e., ranking, classification, dynamic evaluation and regularity analysis) and their application to soccer player performance evaluation. The new model analysed the recent transfer of a left-back soccer player to Europe. The results indicated 12 opportunities for better investment, among 32 left and right-back players considered. Two years later, the value of the same player was considerably lower. He played only five matches in the 2018–2019 season, without scoring or providing any assists. On the other hand, the players better classified by the CPP-MB model presented higher performances and market values.

Airlift operations are vital to support contingency plans during the major humanitarian and disaster relief (HDR) events. The access to disaster zones is often limited by unsafe conditions, poor road infrastructure, and lack of commercial air services. To overcome these limitations, the development of larger planes has allowed bulkier equipment and larger quantities of supplies to be transported by fewer flights. Embraer developed the KC-390 airplane to carry out logistics support and HDR missions. Multinational HDR events usually call for a wide variety of aircraft. The comparison between the KC-390 and the C-130 gains relevance under these circumstances, where the two will be competing for use in emergency support. This article aims to provide support for the allocation of the appropriate aircraft to each mission, by quantifying the advantages (and possible disadvantages) of the KC-390 compared with the C-130 based on the relative difference of their technical performance. Consolidated scores are established through the probabilistic composition of preferences by combining preference probabilities using weighted sums. The weights are calculated based on the experience of pilots applying the analytical hierarchical process. Among the types of missions analyzed, search and rescue present the highest difference in technical performance, in favor of the KC-390.