Stats Summary – Transfer Strategy: When to Follow the Crowd

There’s a lot to consider when making your transfers for the week – current fixture, price, double game weeks, injuries, lineup rotation… Every week there are a couple players who rise to the top of the transfer list. I decided to look into these players to see how they performed compared to others in single game weeks.

Note: this analysis is done based on 2016 points and transfers. The change to the transfer system definitely has some impact for players ranked 4-10.

Transfers in rankAverage score
All players4.32

This table shows us that following the crowd makes sense. The top 3 most transferred-in players each week score more points on average than the rest of the pack. They average about 2 full points per game more than the average for all players. This general trend also applies to double game weeks, with the most popular transfers averaging a better score.

Positiontop34 to 1011 to 60

I also broke it down by position to see if there are times where we probably shouldn’t follow the crowd. Defenders who land in the top 3 overall players transferred in for the week scored significantly less than forwards and midfielders who are in the top 3. If we look at the median scores for players in the top 3, things are even more bleak for defenders – Forwards median = 7.5, Midfielders median = 5, Defenders median = 4.

It should be noted that goalkeepers did not have a large sample size in this table, so we can’t put too much stock into their data.


The first step to considering your transfer option should be to look at who everybody else is bringing in and chose from the top couple there for each position. This is more applicable to the expensive players since the “cheap value” factor is removed.

Your captain should be one of the most transferred in players. There is clearly a broad consensus they have a good matchup.

This strategy gets more reliable as we move further into the season. Partly because casual players drop out of the game and don’t bring in bad choices. And partly because team and player trends become more apparent.

About Andrew Crollard

Andrew has worked as both an economist/data analyst and as a university and youth soccer coach. Naturally, marrying soccer and data together is a perfect fit.

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