Spartan Daily, February 21, 1955

Volume 42, Issue 92https://scholarworks.sjsu.edu/spartandaily/12142/thumbnail.jp

Biological maturation and match running performance: A national football (soccer) federation perspective

© 2019 Sports Medicine Australia Objectives: To examine the influence of maturation and its interaction with playing position upon physical match performances in U15 footballers from a national federation. Design: Observational study. Methods: 278 male outfield players competing in a national tournament were assessed for somatic maturity and match physical performances according to playing position. Stature, sitting height, and body mass were measured and entered into an algorithm to estimate the age at peak height velocity (APHV). Players match movements were recorded by Global Positioning System devices (10 Hz), to determine peak speed, and total- (TD), low-speed running (LSR; ≤13.0 km h−1), high-speed running (HSR; 13.1–16.0 km h−1), very high-speed running (VHSR; 16.1–20.0 km h−1) and sprint distances (SPR; >20.0 km h−1) expressed relative to match exposure (m min−1). Results: Linear-mixed models using log transformed response variables revealed a significant contribution of estimated APHV upon TD (1.01; 95% CI: 0.99–1.02 m·min−1; p < 0.001), HSR (1.05; 95% CI: 0.98–1.13 m min−1; p < 0.001) and VHSR (1.07; 95% CI: 1.00–1.14 m min−1; p = 0.047). An increase by one year in APHV was associated with an increase of 0.6, 5.4 and 6.9% in TD, HSR and VHSR respectively. No effects of APHV were observed for LSR, SPR, and peak speed. Further, no APHV effects were observed relative to players’ field position. Conclusions: Later maturing players covered substantially more higher-intensity (HSR and VHSR) running in matches, irrespective of playing position. The greater match intensity of later maturing players may inform talent identification and athletic development processes within a national federation

PlayeRank: data-driven performance evaluation and player ranking in soccer via a machine learning approach

The problem of evaluating the performance of soccer players is attracting the interest of many companies and the scientific community, thanks to the availability of massive data capturing all the events generated during a match (e.g., tackles, passes, shots, etc.). Unfortunately, there is no consolidated and widely accepted metric for measuring performance quality in all of its facets. In this paper, we design and implement PlayeRank, a data-driven framework that offers a principled multi-dimensional and role-aware evaluation of the performance of soccer players. We build our framework by deploying a massive dataset of soccer-logs and consisting of millions of match events pertaining to four seasons of 18 prominent soccer competitions. By comparing PlayeRank to known algorithms for performance evaluation in soccer, and by exploiting a dataset of players' evaluations made by professional soccer scouts, we show that PlayeRank significantly outperforms the competitors. We also explore the ratings produced by {\sf PlayeRank} and discover interesting patterns about the nature of excellent performances and what distinguishes the top players from the others. At the end, we explore some applications of PlayeRank -- i.e. searching players and player versatility --- showing its flexibility and efficiency, which makes it worth to be used in the design of a scalable platform for soccer analytics

From Manifesta to Krypta: The Relevance of Categories for Trusting Others

In this paper we consider the special abilities needed by agents for assessing trust based on inference and reasoning. We analyze the case in which it is possible to infer trust towards unknown counterparts by reasoning on abstract classes or categories of agents shaped in a concrete application domain. We present a scenario of interacting agents providing a computational model implementing different strategies to assess trust. Assuming a medical domain, categories, including both competencies and dispositions of possible trustees, are exploited to infer trust towards possibly unknown counterparts. The proposed approach for the cognitive assessment of trust relies on agents' abilities to analyze heterogeneous information sources along different dimensions. Trust is inferred based on specific observable properties (Manifesta), namely explicitly readable signals indicating internal features (Krypta) regulating agents' behavior and effectiveness on specific tasks. Simulative experiments evaluate the performance of trusting agents adopting different strategies to delegate tasks to possibly unknown trustees, while experimental results show the relevance of this kind of cognitive ability in the case of open Multi Agent Systems

Spartan Daily, February 5, 1935

Volume 23, Issue 77https://scholarworks.sjsu.edu/spartandaily/2256/thumbnail.jp