Adam's formula re-writes transfer history

A bunch of spreadsheets and equations can't get right what real people got wrong...right?

I can’t have been much older than 8 or 9 when my fascination with player movement really took off. I remember I used to take the time to meticulously write down and then implement every single trade, free agent signing, retirement and release in whatever MLB, NBA or NFL game I happened to be playing on my console of choice at the time — all before I played a single game, or started a career mode.

This would take hours. Sometimes days. But I loved it. I even created the rookies who’d joined the league between when the roster file was created and whatever year it was was in real life. I loved seeing the 16- (and eventually 64-) bit athletes in their new uniforms.

Eventually my fascinations and a global pandemic led me to start posting about football player movement, using stats, market analysis and the good-old eye test to give my two cents on whatever player I could absorb information on. The rest is history.

At some point in generating all the formulas, posting the threads on Twitter (and eventually the blogs), re-tweaking the formulas, tweaking some more and where we are today, years later, I started to wonder: Is what I’m producing actually any good? Could I, for instance, help someone avoid a bad signing, or am I just a Football Manager wannabe moving numbers around a spreadsheet, as some would tell you?

That’s not something that’s actually very easy to decide. After all, every list I’ve ever posted here comes with a disclaimer that you should watch games, too. You’ll see things that way that you couldn’t in one of my formulas, and heaven knows I’ve disagreed with my rankings plenty.

But I’ve worked like hell to find the reasons I disagree with my formula and patch those up. It’s not always so easy, but I think I’m finally ready to put it to the test. So, here’s the project:

We’re going to go back to 2017-2018 and use my formulas as a guide to see whether certain signings should have been made. And I’m bringing you along for the journey, year by year.

In order to get the most authentic and valuable experience for myself, I had to set some ground rules:

• You absolutely must use the formulas exactly as you use them today. Even if you hate who they spit out. Even if that player has completely busted. Tough.

• We’re going to ignore the eye-test element of all this. Maybe the me of today would’ve had a scouting-related thing to say back then, but it’s too easy to “speculate” my way to a signing I know is the right one. No giving myself hints.

• One season at a time. No re-running results or changing needs based on turning flops into hits, just sign whatever position was signed then.

A few other things that are less rules and more things to note as you read:

• There are going to be times when the formula doesn’t particularly like a signing and recommends going another direction. In those cases, I’m going to try to avoid signing just anyone at the position, but will instead attempt to find the best “similar” player. That could mean a similar profile, age, from the same league, whatever. The reasoning will be there in the narrative, and it will be someone I deem “gettable” for the signing club. So, like, Everton can’t sign Toni Kroos.

• For your reference: We’re starting in 2017-2018 because it is the first season for which we have data advanced enough for my formulas (and that’s just the big five leagues). Starting in 18-19, we add Portugal, Belgium, the Eredivisie, and the Championship.

• Ooh! Also: It would take me forever to do charts for everyone, so I’m going to sit that out this time. Please understand.

• I’m also gonna use some hastily generated AI slop. Please forgive me for that, and hire real artists when you have a budget :)

Alright, let’s see just how good or bad I am at this…

We’re starting with midfielders.