01233nam a2200133   4500008004100000022002200041245008400063210007100147260003900218300000700257520073800264100002001002856007701022       2019                        eng d  a978-88-3339-252-300aSarò Franco - Vita di Franco Turini, executive chef dell’Università di Pisa0 aSarò Franco Vita di Franco Turini executive chef dell Università  aPisa, ItalybPisa University Press  a203 aChi è Franco Turini? Come molti sanno, uno dei pionieri dell’informatica italiana. Ma non è questa la domanda che ci interessa. Quella a cui questo breve saggio si propone di rispondere è una questione molto più 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’informatica e all’intelligenza artiﬁciale si dipana, indissolubilmente intrecciato alla sua passione per i fornelli, attraverso le molte intuizioni geniali che lo hanno colpito mentre cucinava.1 aMalvaldi, Marco  uhttps://store.streetlib.com/it/marco-malvaldi/saro-franco-9788833392523/02029nas a2200145   4500008004100000245008700041210006900128520139000197100001801587700002101605700002001626700002101646700002001667856019601687       2015                        eng d00aThe harsh rule of the goals: data-driven performance indicators for football teams0 aharsh rule of the goals datadriven performance indicators for fo3 a—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’ view on football data has the potential of
revealing hidden patterns and behavior of superior quality.1 aCintia, Paolo1 aPappalardo, Luca1 aPedreschi, Dino1 aGiannotti, Fosca1 aMalvaldi, Marco  uhttps://www.researchgate.net/profile/Luca_Pappalardo/publication/281318318_The_harsh_rule_of_the_goals_data-driven_performance_indicators_for_football_teams/links/561668e308ae37cfe4090a5d.pdf