The pursuit of wisdom in any walk of life quickly reveals that what you think you know is not nearly enough to get you to where you want to go. As I'm starting out in my football scouting journey I challenged myself to reach out to those already working in various roles in football to answer a short list of questions. My goal wasn't to get answers but relevant perspectives on the game within the game.
Here is Ravi Mistry:
Here is Ravi Mistry:
How did your first opportunity in analytics come about?
My first opportunity I found using analytics was simply by doing my own work around the subject. After starting my own blog, and tweeting analysis on football/soccer, a series of what I refer to as chance accidents lead me to follow Neil Charles - he was active in the Football Analytics community, and he'd written this blog (http://www.wallpaperingfog.
What attracted you to data/analytics?
I studied Economics at University, so I'd used 'data' in the loosest term - I actually despised and never really was excited by statistics/econometrics. However, I understood numbers. Between my second and third year, I opted to take a placement year, or year in industry. I worked at BASF as a 'Market Analysis & Business Services Assistant' - which translated to getting data using Google, chucking it in Excel and doing some analysis, and the presenting it in PowerPoint. I think that's where my interest started - during this year I watched Moneyball, discovered Football Analytics Twitter, and started my blog. So I started there, and realised I just enjoyed it.
What data language or concepts do you believe are crucial for understanding how to apply data?
Data Literacy has been a hot topic for the last two years. I think what's happened is the explosion of the term Big Data has had it's time, and folks who have been banging the data drum have slowly begun to realise that a key factor in adoption of data & analytics, is the understanding of what it is they're looking at. A study had data literacy at around 20%, which highlights why this is such a key concept. Beyond this, the challenges of being visualisation literate (being able to read, understand and explain a chart or dashboard) and the ability to understand the fields that you are looking at... there's a lot of challenges to overcome.
However, I believe in the next 10-15 years, this will become such a basic necessity of working in business, that data will become a central piece of both classroom and business education.
What is a misconception about data/sports analytics that is mainstream?
Man, I hate it when data is related to statistics - yes there is a statistical element, but saying 'the stats say..' make it seem like factoids or trivia. Making analytics mainstream won't be a thing - it'll just start to happen. The discourse in which we talk about analytics in sport, will mean we stop talking about it as a topic - and just talk about it. The conception that sports analytics is about who's model is more accurate is false - all models will have some level of inaccuracy, but the fact it enables a different level of conversation is often mistaken.
If you could start over what skill would you build on first?
Probably coding... The reason I fell in love with Tableau and then Alteryx was that I didn't need to learn how to use R or Python. At this stage, I can use both, and read both codebases to a basic level - but I wouldn't be able to bash out a script of any description, like I'd be able to build a Tableau dashboard or an Alteryx workflow. I think for anyone getting into data and analytics, choosing something like Python and using that as a base to learn how data, tables and packages are built is a great starter - then move to something like Tableau to build out visualisation best practice. I still believe Tableau has the lowest barrier to entry when learning data visualisation - but your viz is only as good as the data that drives it.
A handful of leagues I scout for don’t have a lot of data past general metrics; how would you go about sorting and leveraging that data?
I think there's still value in general metrics. You can get more insight with 'some' data then 'no' data - and to standardise across the different leagues to have the same level of aggregation. I also thing for some more detailed metrics, there are folks who manually collect it (for example, I recall a member of the analytics community watching goalkeeper goal kicks and manually noting the length and success)
What is your favorite sports moment? Why?
Ha! There's a few... the most recent was the Cricket World Cup final which went to a Super Over. Historically... Istanbul, Richard Chaplow's goal against Watford for Ipswich in the 2014-15 season, Martijn Reuser's goal in the play-off final in 1999/2000... 93:20, Aguero. Moments which you just can't recreate or re-live.
What is there a language or platform that inspires you? Why?
Tableau is my gateway drug to data visualisation, and I stand by it. The barrier to entry is low, and the resources are a-plenty. I'm also a purveyor of Alteryx, but appreciate there's a high cost involved - but the value gained (in my opinion) does make sure it's correct.
What advice would you give to someone wanting to get into analytics?
Don't undervalue the value of copying and pasting. Always be curious. Always ask for help. Share what you're working on, and build your skills. Focus on stuff you're interested in, not just what's hot.
What is your favorite app/tool to use (for work or fun)?
Tableau for sure. I also use Notion as my personal Wiki, Todoist as my to do list/one inbox. Atom as my text editor. RStudio and PyCharm for the respective.
But Tableau is great. Notion is great. Todoist is great.
Work out a system that works for you, and augment it with apps which are a pleasure to use.
What other sport/hobby/discipline do you feel improves your work as an analyst? Why?
Ha, good question! Watching football, understanding the game better - there's loads of great content online which helps to funnel and make sense of what folks are actually looking for. Academic papers for cutting edge stuff.
What improves my work? Probably looking at what else is out there. I also try and understand what stops people using work.. so there's a behavioural side too.
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