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Processed Premier League data sets using Python libraries. Generated regression models, informative graphs, and published article which seeks to predict domestic success based on transfer statistics such as net balance, age, and position.

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donnyr5/PL-transfers

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Premier League Transfer Spending Analysis

Overview

Last summer, Premier League clubs made headlines by collectively spending a staggering 2.9 billion euros during a single transfer window, setting a new record in the world of football. This substantial expenditure was notably influenced by contributions from the burgeoning Saudi Pro league, solidifying the English Premier League's (EPL) position as the leading spender in global football. This GitHub repository hosts a comprehensive research project dedicated to examining the consequences of this lavish spending spree on the performance of EPL clubs.

Published Article

I'm excited to share that this research project has been published as an article on Bruin Sports Analytics. You can read the full article here: Spending Predicts Domestic Success.

Project Objectives

The primary objective of this research project is to investigate whether the substantial transfer spending by Premier League clubs correlates with improved on-field performances. Specifically, I aim to assess whether lavish expenditures are associated with better outcomes in key areas, including goal difference, table position, and total points achieved over the past five seasons.

Methodology

To achieve our research goals, I have conducted a thorough analysis of the net transfer spending (balance) of each Premier League club over the last five transfer windows. I meticulously scrutinized the financial data in relation to each club's subsequent performance metrics. By examining these critical factors, I seek to answer a fundamental question: Can the analysis of incoming Premier League transfers accurately predict domestic success?

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Processed Premier League data sets using Python libraries. Generated regression models, informative graphs, and published article which seeks to predict domestic success based on transfer statistics such as net balance, age, and position.

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