FM19 | Moneyball | Part 4

After my first full season in the Premier League, we are back with another instalment of Moneyball. Last season we finished 15th, with data driven signings making a bit of an impact. This time around we’ll be taking a quick look at my scouting process, as well as all the ins and outs this summer, and preview the upcoming season.

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FM19 | Moneyball | Part 3

Welcome back to the third post in my Moneyball series. If you’re new you can check out Part 1 Here.

My first full season at Crystal Palace draws to a close, and with the end in sight, there’s time to reflect on a successful season in the Premier League. We’re going to take a look at how my signings performed in the second half of the season compared with other players in the squad, my results as a whole and a look at inventive ways I’m keeping my expenditure down.

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FM Stats Lab: Decisions, Decisons, Decisions

Welcome back to the FM Stats Lab. In our first post we covered how we set up our lab environment to give is as much control as possible over our variables, and we also dipped our toes into the statistical water by investigating what sort of impact the professionalism attribute can have on overall team performance. If you’ve not had a chance to read it you can find it here – spoiler alert though, professionalism can have a huge impact.

Our first post was a light introduction, and the statistics were kept on a leash, but now (for all you fellow nerds) we are going to delve a little bit deeper. If stats aren’t you thing that’s fine, you can still find out our headline results from each of our experiments and there’ll be a little glossary at the end of any statistical terms that get thrown around.

There have been some great suggestions in the comments so in this post we planned to cover two experiments:

  • The Impact of Decision Making
  • Physically, Mentally, or Technically good Strikers?

However we went down a stats rabbit hole with the investigation of Decision Making. One that had originally been looked at by another blogger back in FM18 with their original version of an FM Lab. So the striker based experiments will have to wait until next time…

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Welcome to the FM Lab! Where statistics and FM collide

Welcome to the FM Lab!

Statistics and myth-busting are the aim of the game in our FM Lab. We have set up a database and league to let us test what impact changing certain variables have on the actual game, to gather lots of data, and then test it statistically at the end. If like me you like seeing simulations and experiments, but also like me you want more hard figures then this is the experiment series for you.

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FM19 | Moneyball | Part 2

First I want to start out by saying thank you to everyone who read Part 1. The response was really overwhelming and while I tried to respond to most comments, there are undoubtedly a few I missed. As promised, in this post we will be looking at my January Transfer Window activity, the stats for the players I signed, and a closer look at my KPIs and statistical setup.

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FM19 | Moneyball | Part 1

I start a Masters Degree in Data Analytics this September, and recently I’ve been looking at how I can use Analytics to impact my favourite game, Football Manager. Cleon recently tweeted about Moneyball, and how no one has replicated it correctly when it comes to FM.

Now, I had heard of Moneyball, and knew it involved using Analytics to scout players, but I didn’t know the true extent of Moneyball, or where the definition came from. So, I watched the film.

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