The use of data and statistics to understand a situation is growing rapidly in sports. This is especially true in soccer, in some regions also known as football, where most successful teams are frequently dedicated to analytics. According to Soccer Analytics 101, in MLS (USA), Toronto FC and the Seattle Sounders are the teams that are most dedicated to analytics.
Sensing technologies provide high-fidelity data streams extracted from every match, have made soccer analytics possible (Pappalardo et al., 2019b). However, according to figshare, detailed data are rarely made public for scientific research. Thumbs up to wyscout, who collected soccer logs containing all the passes, shots, fouls, etc. of an entire soccer season, that occur during all matches. Since these data are the largest open collection made to the public, this calls for as many researchers as possible to take a look at what happens during a football match (Pappalardo et al., 2019a). Hence the need to draw out some patterns, if any, to answer different hypotheses and possibly to infer the outcomes of future matches.
One would ask, why do we need to analyze or visualize the patterns in these data? This is a broad question, which can be broken down into the following:
How are different events in a soccer match different between competitions?
How does the position on the field where fouls are committed to indicate whether a team is winning or losing? One would say better teams keep opponents away from their own goal and have no need to tackle close to their own goal.
Do substitutes have an effect on the score line?
From which parts of the world do most of the players in a particular soccer league come from? One can be really specific and ask for example, from which part of the world do we get most strikers on a professional level, or which country provides most top-level defenders?
How many open play vs penalty goals have been scored in the first half of the soccer season?
There are several answers to the above question, which will all be addressed in this project through visualization of soccer event match data.
