Alright folks, let me tell you about my deep dive into Fulham FC stats. It was a bit of a rabbit hole, but hey, someone’s gotta do it, right?
It all started with me wanting to win my fantasy league. I figured, what better way to get an edge than to really dig into the numbers behind Fulham? So, I fired up my laptop and started with the basics. I went straight to the official Premier League website. Easy peasy, right?
First things first, I needed the raw data. I was after things like goals scored, assists, shots on target, passes completed, tackles, interceptions – the whole shebang. The Premier League site gave me a decent overview, but it wasn’t quite detailed enough. I wanted granular data, stuff I could really sink my teeth into.
So, I then turned to some of the popular football stats sites, you know the ones. They had more in-depth stats, breaking down the data by player and by match. I was starting to get somewhere!
Next, I decided to try and do my own data analysis. I exported the data from the football stats sites into a CSV file. Messy? Oh yeah, super messy. Data cleaning was a pain. Dates in different formats, player names sometimes abbreviated, sometimes not. Ugh. I spent a good chunk of time just cleaning things up in a spreadsheet. Find and replace became my best friend.
Then, I fired up Python and Pandas, my go-to tools for data analysis. I loaded the CSV, finally clean, into a DataFrame. Time to crunch some numbers!
- I started with simple stuff, like calculating the average goals scored per game, the pass completion rate, and the most frequent tacklers.
- Then I wanted to see the correlations between different stats. Does more possession lead to more shots on target? Does a higher number of tackles mean a lower chance of conceding a goal?
It wasn’t just about the numbers, though. I also wanted to visualize the data. I used Matplotlib and Seaborn to create charts and graphs. A scatter plot of shots vs goals was a good start.
But here’s where things got interesting. I decided to look at Fulham’s performance against different types of teams. Did they struggle more against defensively solid teams? Were they better at exploiting teams with a high defensive line?
I grouped teams into different categories based on their playing style (a bit subjective, I admit, but hey, gotta make some calls). Then, I compared Fulham’s stats against each category. This gave me some insights into their strengths and weaknesses.
I also tracked Fulham’s form over the season. I looked at their rolling average of goals scored, shots on target, and possession. This helped me to identify trends and patterns in their performance. Were they peaking at the right time? Were they experiencing a mid-season slump?
Finally, I compiled all my findings into a report with my conclusions. Was it enough to win my fantasy league? We shall see… But at least I know more about Fulham than most other folks out there.
