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

Carrier-envelope offset frequency measurement by means of an external optical resonator

A general-purpose method based on the implementation of the asymmetric Pound-Drever-Hall (PDH) technique is proposed to measure the carrier-envelope offset (CEO) frequency of a mode-locked laser using an external optical cavity. By analyzing the synchronously demodulated signal of the spectrally filtered cavity reflection when the optical resonator is locked to the mode-locked laser, a discriminating signal depending on the relative frequency offset between the mode-locked and optical cavity comb-like spectra is obtained. For a given geometry and group delay dispersion (GDD) of the cavity parameters (i.e., a known cavity mode offset), this signal can be used to retrieve the laser CEO. This approach turns out to be advantageous in terms of setup complexity with respect to other well-known techniques that rely on non-linear frequency generation, such as f-2f interferometers. In addition, this method can be used to precisely determine the laser-cavity spectral coupling, which is an important topic in cavity-enhanced spectroscopy and non-linear optics applications. After the theoretical description of the generalized asymmetric PDH signal, an experimental validation of the proposed method is reported using an Er-doped fiber frequency comb source centered at 1,550 nm, with a repetition rate of 250 MHz, locked to a linear optical cavity with a 1 GHz free spectral range. The theoretical effect of the GDD is confirmed experimentally using different cavity configurations. Moreover, the comparison with the CEO frequency values measured using an f-2f interferometer demonstrates the feasibility of the proposed method

Data science: a game changer for science and innovation

AbstractThis paper shows data science's potential for disruptive innovation in science, industry, policy, and people's lives. We present how data science impacts science and society at large in the coming years, including ethical problems in managing human behavior data and considering the quantitative expectations of data science economic impact. We introduce concepts such as open science and e-infrastructure as useful tools for supporting ethical data science and training new generations of data scientists. Finally, this work outlines SoBigData Research Infrastructure as an easy-to-access platform for executing complex data science processes. The services proposed by SoBigData are aimed at using data science to understand the complexity of our contemporary, globally interconnected society

Who is polluting Italian honey? A filth test survey

Honey is largely considered a natural and healthy product. Investigation on foreign matter in honey provides useful information to evaluate honey quality standards in apiary, honey extraction and packaging phases. Indeed, toxic substances (antibiotics, pesticides and heavy metals) as well as foreign matter (e.g. arthropods, hairs) can contaminate honey, acting as allergens or vectors of human pathogens. We used the filth test to evaluate the presence of foreign matter in samples of Italian honeys, mainly from Tuscany. We revealed a high number of carbon particles and other inorganic fragments, followed by fragments of animal origin. This latter included whole small insects, their cuticular fragments, mites and mammal hairs. The kind of contamination allowed us to evidence uncorrected apicultural practices and to suggest the appropriate corrective measures. The filth test method is an excellent and cheap tool to check honey quality, requiring minimal instrumental equipment and giving results that can be interpreted quickly