2022 Football Summer Transfers

Introduction

Football transfers are a multi-billion-dollar industry, and the value of players can vary greatly depending on their age, position, and skill level. In this report, I will analyze a dataset of football transfers from 2022 to assess the value of players worldwide and determine the total income generated from player sales across different leagues and clubs.

Data Overview

The dataset used for this analysis consists of over 33,000 rows and 12 columns. The data was obtained from GitHub and contains information about football transfers in 2022. The columns include player names, club names, transfer fees, player values, positions, ages, and more. The data was initially in Excel format and was further processed and visualized using Microsoft Power BI.

Findings

Our analysis revealed the following key findings:

• Chelsea spent the highest cost in 2022 transfer, with a total of €0.3 billion.
• The total cost of transfer in 2022 was €5.97 billion and the players recorded in the whole world was valued at €15.91 billion
• The Premier League was the top league in terms of cost spent on players, with a total of €1.6 billion. From the data, it showed that 99% of the transfer was done on Premier League.
• England led all countries in terms of the cost from player transfers, with a total of €1.6 billion.
• The defense position had the highest number of players in the dataset, with approximate 10,000 players.
• The group of attack generated the highest cost, with a total of €2.4 billion and the centre-forward of the attack group cost €1.3 billion, it’s the highest cost.
• Players between the ages of 18 and 30 brought in the highest cost in the transfer, with a total of €5.8 billion.
• The majority of player transfers took place in July 2022, with over 24,000 transfers occurring during this month and a cost of €3.9 billion.
• Players with No Age are 148 players and they attack zero cost from the transfer in 2022.

Data Cleaning and Transformation

The data cleaning process involved the following steps:

• Removing duplicate data
• Converting strings columns to integer columns
• Grouping data by the players’ age and the players’ position

Conclusion

In conclusion, my analysis of the 2022 football transfer dataset revealed several key insights into the value of players and the total income generated from player sales. These insights can be used by clubs, players, and other stakeholders in the football industry to make informed decisions about player recruitment and transfer strategy.

Recommendations

Based on the insights gained from our analysis, I recommend the following:

• Clubs should focus on recruiting young, talented players in the attack position.
• Players should be aware of the value of their services and negotiate accordingly when considering a transfer.
• Clubs should ensure they publish players age because attach other clubs to buy their players.
• Football governing bodies should work to create a more transparent and fair transfer market for all.

Behind the Scenes

I used Microsoft Excel and Power BI to analyze the data. I started with Excel through removing the non-standard symbols, such as "th." and "m" from the player_value column and the cost column. I first convert the “th.” to “K”, then converted these columns to integer (numbers) values using the formula [=IFNA(LEFT(A80,LEN(A80)-1)*CHOOSE(MATCH(RIGHT(A80,1),{"K","M"},0),1000,1000000),A80)].

I also removed duplicate data and grouped the data by age and position using the formula [=IFS…]. In Power BI, I used Power Query to change the headings, clean the columns, and delete unnecessary columns. I also changed the data types of the columns to the most appropriate type.

We believe that this report provides a comprehensive and informative overview of the football transfer market in 2022. I hope that this report will be useful to clubs, players, and other stakeholders in the football industry.

for more visit: https://github.com/Star-cj/2022summerTransfers.git/