I’ll also be using Key Performance Indicators (KPIs) to analyse and compare potential signings, similar to my 2019 save. My assistant manager will be tasked with coaching the team and organising the squad on a match day. My responsibilities will align more with a Director of Football, deciding which players to buy and sell, hiring staff, etc. I will be taking the role of a General Manager. I’ve also added something different this year, which will hopefully lower my workload when it comes to running the club. 49) – Limit of three transfers per season. 47) – Avoid expensive, high scoring centre-forwards. 45) – Try to sign players who are 20-25, no players under 19. 29) – No players signed over the age of 27. 29) – If an offer comes in for a player which is over what I deem their “market value”, I will accept. Be as eager to sell good players as to buy them (pg.24) – I won’t be buying players from England, Spain, Brazil, Holland etc. Some of these are taken from the book Soccernomics by Simon Kuper & Stefan Szymanski, another great read. I’ve decided to set myself some rules, which include the type of signings I will be allowed to make. I’m seeking to find more nuanced statistics which may be overlooked by some teams. In football, the obvious statistics to buy are goals and clean sheets after all, these win games. I’m aiming to conduct a regression analysis of salary and points scored, which will give me an estimate of how to calculate a players value, and also find statistics which heavily influence points won. The Byline and FMStag recently released an article based around using data in FM21 to select players, which is well worth a read. ![]() Essentially, rather than using attributes to judge a player’s ability, I’ll be looking at statistics. So, how does Moneyball translate to Football, and more importantly, Football Manager. Statistics and Moneyball in Football (Manager) This statistic was undervalued in the sport, and allowed them to take a team with the lowest wage budget in the division to a 20 game winning streak. Using Sabermetrics, they found a strong correlation between on-base percentage and runs scored. The idea was put into practice in Oakland, through General Manager Billy Beane and statistician Paul DePodesta. They argued that you can’t quantify a sport. They saw these statistics and numbers as fantasy baseball, something which didn’t apply to the real world. ![]() Originally, the idea was popularised by statistician Bill James and was widely derided by the traditional scouts of the baseball world. Moneyball was the use of these metrics in order to find value in players who were overlooked for perceived flaws, such as age, injury or unconventional If you haven’t the time for that now, essentially, Sabermetrics is the analysis of statistics with reference to Baseball. If you’ve never heard of Moneyball or Sabermetrics, I’d urge you to read the book by Michael Lewis, or watch the film both are excellent. Statistics and Moneyball in Football (Manager).
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