The 18/19 season seem like a distant memory, but now with the sun shining and FPL prices released, means we can now start looking forward to the 19/20 season.

I’m not an expert fantasy football manager or watch football as closely as others. I rarely watch match of the day if my beloved Palace lose (so miss quite a lot☹). I play all the fantasy games by the numbers and using various analytics to aid my understanding and captain choices. The first step for the new season is to gather information on players, positions and points scored from the previous season and use this to understand how I should be spending the budget.

Data summary

The summary data for FPL is in the following link:

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The structure of the spreadsheet is:

Summary – contains all the players, their position, price and points scored. Can add other variables on request.

Season top 20 – list the top 20 by position based on total points, points per £m and points per game per £m

Team – Select a team from cell C3 and it lists that players teams.

VFM – Shows a scatter plot for each position of points per game by cost of player. A line of best fit is shown, and the top eight players compared to the line are labelled.

Metrics and initial view

It is quite difficult to know the best metric to use to compare players, but my preference is the number of points per game per value of a player.  The points per game, makes adjustments for players that have missed a game through injury or rested etc.  The chart below comes from the VFM page and is for midfielders that have played at least 10 games.

The solid blue line is a linear regression line.  The r2 figure (bottom right hand side) indicates how much of the variation is explained by the line.  The closer to 1 means a good fit and 0 means there is no relationship.  Here the value is 0.7354, which is a very good fit.

Choosing formation and where to invest budget

Once we have a regression line for each position, we can plot them on the same graph as follows:

As a starting point, assume we filled our squad with the cheapest players available. This would mean we would have some budget available. The slope of the lines indicates the benefit of investing in a certain position. It is clear from the graph that money should firstly be invested in defence and there is no obvious difference in investing between other positions.

Other considerations

As we have a captain that scores double points, it would make sense to have an expensive player who has the potential to have big scores (even if not the best in terms of value for money).

Also, the players on the pitch are the ones that score the points, so it is better to reduce the value of the bench.

The above is a good starting place but doesn’t account for players scores from last season being above or below expectation. For example, if a player had ten shots and scored all ten, then this is unlikely to be repeated. He may only be expected to score four times so the data over-estimates his likely output.

We have new players joining the league and they aren’t included in the data and new managers will change formations and style of play.

With the introduction of VAR, we are likely to see more penalties (or goals as defenders no longer foul or handle the ball). I expect this to hurt the weaker teams the most.

My first draft

My strategy for the season is to plough my money into high priced defenders and then with the remaining good value players followed by budget players with to enable some expensive ones.

My initial draft without accounting for fixtures is:

The players will change as we get nearer to the start of the season and more information is known about transfers and I start to consider fixtures.

I am heavy at the back and will consider having VVD, also uncertain about Zinchenko but could be swapped with AWB. I had thought of Sterling and Salah but gone with Kane and Auba for the time being. Partly as their clubs are paired (eg one team will always be at home) for captain options.

Roll on pre-season to spot some potential budget players.

£5,000 FPL League Prize