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...