Through this analytics project, we hope to understand more about the game of football through statistics and data, instead of seeing the matches in a traditional way. We are interested in this dataset because we all like football, and wanted to interact with a dataset in which we all have an interest in. In addition to that, we never see football matches from a statistical viewpoint, so we were interested in analyzing the game from this perspective. Specifically, we wanted to focus on injuries and yellow/red cards, and how that would affect the performance and results of the team. Furthermore, we were also interested in how that changed the excitement of the fans that are watching the game live in the stadium.

We believe that this dataset could be a user-facing dashboard because it has precise data observations that can be put into various graphs and charts. Through deeper analysis, we will be able to extract more data, and make connections between each one.

This data was created by the public using information from the Premier League matches. The owner of the dataset is Sanjeet Singh Naik, who is interested in analyzing the data of Premier League matches to see the tendency and trends within the game of football. This dataset was made for the public interest, and the owner is willing to add more information to this dataset with suggestions if necessary. The owner also believes that it is a fun way to analyze the game through statistics and datasets.

The dataset contains information about all the Premier League football matches played from the 2014/2015 season to the 2019/2020 season. The data includes information such as the date of the match, teams involved, scoreline, and various statistics for each team. This dataset contains a total of 2,640 observations. The data was collected between August 2014 and July 2020, covering six seasons of the Premier League.

In the Provenance section of the dataset, it mentions that the dataset was collected using Scraping with scrappy, selenium, and beautifulsoup. Therefore, the owner scraped the data from a bigger database, and included the necessary information that was needed for this specific one.

• Person 1: Omar Hemed I love watching football games.
• Person 2: Makoto Kitamura I play Intramural soccer.
• Person 3: Takara Nishizaki Playing soccer cannot be seperated from my life!

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The URL of the data that we used is https://www.kaggle.com/datasets/sanjeetsinghnaik/premier-league-matches-20142020