PLFantasy

One of the key complications with player forecasting - or indeed I imagine any forecasting - is deciding which data set to use. When it comes to fantasy football, we obviously want to include as much recent data as possible but the issue is when we can exclusively rely on this season's data and when we need to look to the past seasons for guidance. I am generally quite happy to solely rely on this season's raw event data such as shots or created chances fairly early on as they tend to occur with relative frequency and thus stabilise in a short time frame. How these events get converted into goals can fluctuate a lot more though, as the key driver there - goals - happen much less frequently. With this mind, the revised player projection table below allows you to choose how you are converting the raw chances into goals and assists: Past season - uses the benefit of having a 38 game sample to see how different teams convert chances into goals. The negative, of course, is that te...

As democracies teeter on the edge of existence around the world and once-eradicated diseases return due to an apparent loss-of-uptake of vaccinations, we appear to be in a time where the masses are losing faith in experts. Scientists, journalists and those steeped in the scientific process are being drowned out by those who "go with their gut" and follow their id . I am here to stand up for the experts, though alas, I am not one. Those more learned than I will quickly realise that this blog is the work of a child in his father's suit trying to close business deals (actually, that might work these days). Still, you've made it this far so you might as well stay for a bit of analysis, even if my statistical base knowledge is formed from watching archived Harvard lectures and reading old Fangraphs posts.  For those just joining us, I ran this blog for a number of seasons but took last season off. I have built a reasonable, though hardly sophisticated model to try a...

With the new season upon us I wanted to get out some quick and dirty forecasts for the first few weeks of the year. The forecast data is almost entirely based on prior year data so I have not taken into account players changing teams (Lukaku, Walker) or those with new opportunities and teammates. By definition, a lack of historic data means that the new arrivals (Morata, Lacazette) are also missing for now, but will be added as soon as we have a small amount of data to go on. The defensive data looks a bit wacky for now so I would base my defensive decisions more on the team projections for now. I will also update and share some workings around how the model is going to work this year as I try to improve on the decent, but far from perfect version from a couple of seasons back. It's great to be back and I thank everyone reading this for giving the blog another chance. Please share your thoughts in the comments or on Twitter and I will make changes in the coming weeks. Good l...

Learn About Tableau Risk slider - this season each player is assigned a risk rating, based on their playing time and current injury status (as explained here ). There's no reason to definitely exclude all risky players, but you should consider their playing time before pulling the trigger with them. I've had a couple of questions about a couple of the 'odd' forecasts above, namely Loic Remy's lofty status and how Sturridge out ranks Suarez. I'll address those in more detail tomorrow but wanted to get the data out now.

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