Sky has recently launched their fantasy football game for the 19/20 season. This is probably my favourite fantasy game and I look forward to seeing any rule changes and how they may change the pricing structure.
I base most of my decisions on the numbers, so thought I’d provide a quick article with my initial thoughts.
Sky Game Rule changes
There are two main tweaks to the rules that I have noticed. First that the man of the match bonus has reduced from five points to three points. The second is that the number of tackles (for tier 2) and shots on target (for both tier 1 and tier 2) have been reduced to achieve the bonus.
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.
I need to make adjustments for the two rule changes. For the MotM change, I deduct two points for each MotM a player achieves. Making an adjustment for tackles and shots is slightly more difficult. I have calculated the average shots and tackles per match each player achieved last season and assumed the distribution would follow a Poisson and adjusted the total points accordingly.
The summary data for Sky 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 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 0.6787 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:
The first question is what formation to choose. For this assume you had to spend £7m on each player. From the above lines it would be a goalie, followed by a defender. As you want more outfield players to be defenders then this suggests a formation of 5-3-2
The next stage is where to spend your money once the formation has been decided. This is based on the gradient of the lines. The defender line is the steepest which suggests to invest more of your money there. However, its not that much greater than strikers, so could justify spending it their if you think a player may be slightly under-valued. It also suggests going as cheap as chips in midfield or less you can identify a play who is an outlier and significantly under-priced.
Sky has a captain possibility for each matchday, so you may want to ensure you have good players to cover these matches.
There is an overhaul after week four, so selecting the initial team should be based on fixtures and hence could mean a slightly different formation is better.
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 in the introduction of VAR we are likely to see more penalties (or goals is defenders no longer foul or handle the ball). I expect this to hurt the weaker teams the most.
Sorry, there is no first draft to report. I plan to construct The Algorithm with the new data. I will then follow this up with how I will use to Algorithm to select my team.
I hope you have enjoyed this article and look forward to the new season as much as me.
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