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.

Results

We finished 15th in the end, 5 points clear of the drop with a pretty respectable goal difference, only a 4 point improvement on last year.

Whilst pretty low in terms of chances created (14th) and shots on target (18th), we actually came top for chance conversion at 12%. We also came 2nd in terms of Tackles Won Ratio. We might not be doing things a lot, but we’re doing them well.

With the 17th biggest net spend, and the 18th biggest wage budget, I was pretty happy with the season overall. Hopefully next year we can build on this, and push towards a mid table finish. Form towards the end might look terrible, but we played all of the top 4 in our last four games.

Signings

I looked at my January signings in the last post, so now let’s take a look at how they settled into life in the Premier League.

Sebastian Burghelea

Sebastian has done okay since joining in January, scoring 3 and assisting 4 goals in 11 starts.

Jaime Ortiz really hit the ground running, scoring 8 goals in 16 games in the second half of the season.

Striker Comparison

You can see that Jaime Ortiz (red) has kept up his very impressive stats since joining. In his 16 appearances, he took 44 shots, just 5 short of Kalanic, who played almost double the game time. He is the real test for the moneyball hypothesis, so it’s great to see him performing well.

I was impressed with Burghelea’s assist record, managing an assist every 4 games, which isn’t bad for a bottom half PL striker. Otherwise he was pretty average, similar to Antun Kalinic, who I signed before I started the moneyball experiment.

Reducing Expenses

Moneyball is all about using the statistics available to find undervalued and overlooked players in a competitive market. However, it doesn’t help to keep our finances as healthy as possible, and find new and inventive ways to reduce our expenses, in the pursuit of a financially viable club.

With that being said, let’s take a look at some of the ways I have been reducing the clubs expenditure.

I have to be honest, the clauses tab is something I have never even noticed, let alone looked at in any great depth, but it can be a great way to reduce expenditure at a club working on a low budget, such as we are at Crystal Palace. A few players missing out on starts towards the end of the season saved me in the long run.

  • Asmir Begovic: One more game meant an extra fee of £130K
  • Tom Cairney: One more game meant a contract extension ~£40K p/w
  • Mohamed Elneny: One more game meant an extra fee of £1.9M

With Begovic and Cairney leaving this summer, contract extensions and fees could have been awful financially, so it was important to avoid giving them new contracts. If we sell Elneny in the summer, we can avoid paying that £1.9M fee to Lazio. All these little gains add up, especially when trying to keep a club solvent.

Downloadable Spreadsheet

Lastly, I have created a downloadable spreadsheet, for you to use in your own saves. I’ve included 7 different positions, each with 10 KPIs, but you can add more if you wish. If you’re interested, the details of how to do this will be in the spreadsheet which you can download here.

Thanks very much for checking out my article, you can find previous editions here:

The next post should be more substantial, covering my first Moneyball summer, and watching the movement of players, in and out.


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7 thoughts on “FM19 | Moneyball | Part 3

  1. Anders says:

    Hi, having read and re-read all of your Moneyball posts, I think you just might be on to something 🙂 I’ll have a look at the spreadsheets after the holidays and see if I can implement them into my current save. I usually follow an attribute threshold for #fibra along the lines of FM_ Grasshopper (but expanded). Also I would like to ask you to write a bit more about how you rely on scout reports (if at all).

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    • fmvars says:

      Thank you for the feedback much appreciated!! It’s a different way of approaching scouting definitely and it’s really interesting to see it producing results, such as in the case of Jaime Ortiz. I will try and include how I go about scouting in my next post but basically I use it to see how viable a transfer would be, look for release clauses, estimated wages and fee, star rating and so on. I definitely don’t use attributes at all, I could basically be playing with attribute masking. But playing with attributes on allows me to see if the players are outperforming their perceived ability

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  2. Anders says:

    BTW working systematically on improving the fibra/dna in the team often makes it easier to succeed in implementing a certain style of play (knowing your players can pull it off). Like when you search for high tackling %, the player might have played vs lesser opponents. I recruit based on dna higher than league average. Comments please?

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    • fmvars says:

      Yeah it’s important to take into account who the player plays for and what kind of opponents they’re facing definitely. That’s something I’ve accounted for when choosing which player to sign. As a lower mid table side I’m looking for players in similar predicaments or players who can adjust to that

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    • fmvars says:

      Have you got appearances as your KPI1? Apps will need editing from 16(8) to 24 in order for the spreadsheet to calculate correctly. You can tweet me a screenshot @FM_Vars and I’ll take a look either

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