I’ve had numerous attempts at recreating the fabled Moneyball, and never really got anywhere with it. Different things got in the way but the main issue was it takes a while to see the results, and I usually got bored or sacked before those results came to fruition. This year I’ve spent much more time planning my choice of club, and feel that I can really make a go of it. Plus, the recent addition and changes to the Data…
In a previous article I focused on the impact of one specific member of the Medical Team, the Physio. Some experiments were run using out special league and we were able to see what sort of impact a good physio (or not) can have on things like the amount of injuries, injury length and overall performance. But the Physio is but one member of the Medical Team. From the Premiership down to the lower leagues it is common for there…
Let me introduce you to the little brother of xG, Expected Assists (xG). Whereas xG tells you the likelihood of a goal being scored from a certain position Expected Assists tells you the likelihood of a goal being scored after receiving a pass. The two go hand in hand in real world football metrics, and there’s no reason why you can’t use them in FM20. We also add another metric to look at. There’s something to be learnt about where…
FM20 has a huge range of player traits to change, improve or occasionally disrupt your players behaviour on the pitch. In our last article we ran an experiment to see what impact ability had on certain striker traits like lobbing or rounding the keeper, and placing or powering in shots. It was a bit of a bust as we found that ability alone didn’t seem to have an effect. It was useful for partly busting myths about certain player traits…
The Goalkeeper. We need them, but I am terrible at working out whether mine are actually any good. With us being deep into our FM20 saves, whether we are in the Premier League with high fliers like Liverpool or in the lower leagues fighting against relegation, were are all probably looking at how to improve out teams. This could be through the transfer market, via training, or even tactically. However we plan on making changes we have to work out…
Last time in the lab, we worked out the attributes that formed the DNA of my hoofball side. In this post, we’ll be comparing FM19 tactics. To do that, we’ll compare that hoofball tactic against a range of others from Dictate the Game in a tactical showdown. We discovered, as a result of the analysis, that for my angry hoofballing side the (common sense) attribute of aggression was not the only key for success. So were surprise attributes like positioning…
As mentioned in our previous post we are going to take a step away from the sterile lab setting (though we will be back) and look at some more natural data. Data that has been occurring in my saves. As a result we will be able to use statistics around key performance indicators (KPI’s) to actually determine what our club DNA should be for for each of our units: defence and attack. Recruiting players FM19. There are some great articles,…
