ABSTRACT
To discover patterns in data is about using Data Science to reveal the hidden mechanisms governing the analyzed phenomena. Data Science is able to uncover lots of different patterns such as distributions, associations, similarities, interactions, classifications and trends, that can be described, measured and modelled. There are only patterns, patterns on top of patterns, and patterns that affect other patterns. This chapter discusses some examples of patterns that can be revealed and many statistical tools that can be exploited to analyze data. It is concerned with the identification of the factors determining high-pressure game situations and affecting the scoring probability. An important issue for the analysis of games is to determine the frequency of occurrence of some events with respect to some other concurrent variable. A broad set of extremely powerful tools to discover hidden structures and patterns in data comes from machine learning techniques that make a large number of algorithms available for both supervised and unsupervised learning.
