@book {1225, title = {Sar{\`o} Franco - Vita di Franco Turini, executive chef dell{\textquoteright}Universit{\`a} di Pisa}, year = {2019}, pages = {20}, publisher = {Pisa University Press}, organization = {Pisa University Press}, address = {Pisa, Italy}, abstract = {Chi {\`e} Franco Turini? Come molti sanno, uno dei pionieri dell{\textquoteright}informatica italiana. Ma non {\`e} questa la domanda che ci interessa. Quella a cui questo breve saggio si propone di rispondere {\`e} una questione molto pi{\`u} importante: chi avrebbe voluto essere Franco Turini? In questo scritto, la vita e la carriera di Turini vengono ripercorse alla luce della sua vera, unica e irredimibile passione: la cucina. In un intreccio romanzesco, denso di colpi di scena e assolutamente falso e tendenzioso, il contributo di Franco Turini all{\textquoteright}informatica e all{\textquoteright}intelligenza artificiale si dipana, indissolubilmente intrecciato alla sua passione per i fornelli, attraverso le molte intuizioni geniali che lo hanno colpito mentre cucinava.}, issn = {978-88-3339-252-3}, url = {https://store.streetlib.com/it/marco-malvaldi/saro-franco-9788833392523/}, author = {Marco Malvaldi} } @proceedings {770, title = {The harsh rule of the goals: data-driven performance indicators for football teams}, year = {2015}, abstract = {{\textemdash}Sports analytics in general, and football (soccer in USA) analytics in particular, have evolved in recent years in an amazing way, thanks to automated or semi-automated sensing technologies that provide high-fidelity data streams extracted from every game. In this paper we propose a data-driven approach and show that there is a large potential to boost the understanding of football team performance. From observational data of football games we extract a set of pass-based performance indicators and summarize them in the H indicator. We observe a strong correlation among the proposed indicator and the success of a team, and therefore perform a simulation on the four major European championships (78 teams, almost 1500 games). The outcome of each game in the championship was replaced by a synthetic outcome (win, loss or draw) based on the performance indicators computed for each team. We found that the final rankings in the simulated championships are very close to the actual rankings in the real championships, and show that teams with high ranking error show extreme values of a defense/attack efficiency measure, the Pezzali score. Our results are surprising given the simplicity of the proposed indicators, suggesting that a complex systems{\textquoteright} view on football data has the potential of revealing hidden patterns and behavior of superior quality.}, url = {https://www.researchgate.net/profile/Luca_Pappalardo/publication/281318318_The_harsh_rule_of_the_goals_data-driven_performance_indicators_for_football_teams/links/561668e308ae37cfe4090a5d.pdf}, author = {Paolo Cintia and Luca Pappalardo and Dino Pedreschi and Fosca Giannotti and Marco Malvaldi} }