⚽⚽ Football Performance Analysis ⚽⚽

✔️ Project Overview

This project explores the relationship between my physical activity, measured by steps tracked through a step counter app (Padometer), and my performance in football matches. I track my football performance weekly and combine this data with my daily step count data imported from Google Fit.

✔️ Data Sources:

Step Counter App:

• I use a step counter app called Padometer on my phone, which syncs data to Google Fit. From Google Fit, I export my daily step counts in JSON format.

Football Performance Data:

• I maintain a CSV file that tracks my weekly football performance. This file includes metrics such as goals scored, assists, team wins, and whether it was a football day.

✔️ Questions Explored:

Correlation Analysis:

❔ 1 - Is there a relationship between the weekly steps total and the week's football performance? If so, how strong is it?

• I found a strong positive correlation between weekly steps and metrics like goals scored and team wins.

❔ 2 - Is there a relationship between the total steps on the football day and the football performance? If so, how strong is it?

• There is a moderate to strong positive correlation between steps on football days and metrics like goals scored, assists, and team wins.

❔ 3 - Which has a stronger correlation to my football performance: total steps on football days or total steps per week?

• Total steps per week generally showed stronger correlations with metrics like goals scored and team wins. However, for assists, total steps on football days exhibited a stronger correlation.

✔️ Methodology

1 - Data Import and Preprocessing:

• Imported daily step count data from JSON files downloaded from Google Fit.
• Merged this data with my weekly football performance CSV file using Python and pandas.

2 - Exploratory Data Analysis:

• Conducted correlation analyses to understand relationships between step counts and football performance metrics.
• Visualized these relationships using scatter plots to identify trends and correlations.

✔️ Conclusion

This project highlights the impact of physical activity, measured through daily steps, on my football performance. By analyzing correlations between steps and performance metrics, I gain insights into how my physical activity levels influence my gameplay.