This is my first time posting a project on Skillshare so be gentle.

I didn't have a newspaper to hand when I started this project so, with it being an FA Cup weekend (Soccer/Football), I decided to gather my data set from the weekend's results. I limited myself to drawing information from the section on the FA's official website dedicated to the third round of the cup. This way I'd be working with a more contained data set similar to what I would have found in the paper.

What sets the FA Cup aside from league football is that it involves teams from all levels of English football, meaning a small town club can be drawn with one of the multimillion pound clubs from the Premier League.

With this in mind I wanted to come up with an infographic that showed the scope of the cup and highlighted some of the underdog stories that the third round always seems to throw up. I wasn't sure how to define my question at first but settled on:

How many upset were there in the FA Cup Third Round?

I played around with a few different ways of presenting the information I had in my spreadsheet but none of them seemed to answer the question until I came up with this graphic:

It takes into account the overall positions of the two teams playing in each fixture and shows the size of the gap between them, the shortest lines showing teams on similar levels and the longest lines showing the biggest mismatches. This first iteration was a little light on information and so it was difficult to understand so with a little more work i was able to come up with this:

I was able to add more information in and around the graph to give it more depth and add more context. The colour coding makes it easier to understand and helps not only to answer the question (there were 4 major upsets) but also give a more general overview of the weekend's events.

So that's where I am at the moment, any and all feedback is welcome!

Thanks, great class.

Sun 17 January

Following feedback from Nicholas I will be revisiting these initial experiments where I tried to integrate team names and scores into the main graph:

Mon 18 January

With a little work I was able to incorporate the scores into the main graph:

I feel like it's now a more comprehensive representation of my data set. I made the overall ranking of the teams more apparent on the left hand side to greater emphasize some of the mismatches. I also added the question as a subheading to provide a little more context.

Tue 19 January

Nicholas pointed out that the league names were colliding with some of the scores and affecting their ledgibility, so I made the league names larger and dropped the opacity to make them more subtle. This way the league names fade into the background and have more contrast with the scores in the foreground. This should now make the overlapping type more ledgible.