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The purpose of this post is two-fold. First, I want to illustrate a point I've made before in graphical form and highlight a couple of players coming out of that analysis. Second, I want to give a little bit of narrative around regression to the mean and issue a word of caution as to where I'm seeing it misapplied fairly regularly in these stat-friendly times. From some quick research over the top forwards in the league, we see that, generally, they haven't really shown an ability to consistently convert shots on target (SoT) into goals above the league average rate . The league average hovers around the 33% mark for forwards and 28% mark for midfielders, with very few players able to exceed those totals each year (and even then that would be expected purely based on statistical variance). In short then, whether it seems intuitive or not, if a player's SoT are turning into goals at a very high rate, we must expect some  regression in the coming weeks. Now then, a q...

Each player who racked up 6 or more points this week has been assigned a 'Buy', "Hold' or 'Sell' status. These don't necessarily reflect what I would do, more what I believe to be a reasonable action at this time: Buy - the player can be purchased immediately taking consideration of his playing time, fixtures, injury status etc. This status does not necessarily mean you should buy him now as it depends who else you own, only that it is reasonable to do so. Hold, and/or monitor - if you own the player you're not in a rush to ditch him but there's sufficient risk here to justify potential buyers holding off. Sell - the player has too many risks and should either be sold or not purchased. This does not mean he might not have value in the future, just not right now. Note that I don't generally include defenders as so much of their value is tied to their team's success rather than their individual skill set. Dimitar Berbatov 16 Not ...

One of the measures that goes into the team model looks at how each team has performed against their opponents compared to how the league fared in that same fixture. So, if for example, Southampton at home are surrendering nine shots inside the box per game and Everton come in and rack up 12 SiB, they have 'overperformed' by 33%. Rather than look at the standard measure of form (i.e.goals) which focuses on the results rather than the process, we can look at this data and see if teams are playing consistently or trending in one direction or the other. The added benefit to this metric is that it is opponent adjustment so 'form' doesn't get blurred by simply having a run of easy or hard games. Although the model measures shots inside the box, outside the box and those on target, I have found SiB to be (a) predictive of future success (see graph below) and (b) generally consistent for a given team (unlike SoT which can be affected by crazy on-target rates like Steve ...

Arsenal Mannone, Sagna, Koscielny, Mertesacker, Vermaelen, Coquelin, Arteta, Cazorla, Walcott, Podolski, Giroud Subs: Szczesny, Andre Santos, Oxlade-Chamberlain, Ramsey, Arshavin, Jenkinson, Chamakh There was a fair bit to take away from this game in terms of fantasy impact but not a whole lot by way of lineup issues. Vermaelen sliding to left back was interesting but Santos was hardly a legitimate option anyway so there's not much to note there. The fact that Koscielny got a rare start is also not really an issue as the more reliable Mertesacker can be had for less money if you are still buying this defense. Walcott came into the side up top which is surely the way it'll go long term, though his price tag still looks a touch high given his underlying stats and risk of rotation so I'm still not personally back on that bandwagon yet. Giroud will get more coverage in this weeks fanning the flames  piece, suffice to say I am very much a buyer, and if you are too I'd a...

One of the factors that goes into the player model is the percentage of shots each player takes, split between those taken inside and outside the box and whether they were at home or away. Given their correlation to goals, I'm going to focus on shots inside the box (SiB), though if anyone's interested I could post the shots outside the box (SoB) data too. Scroll down for some observations . . . Powered by Tableau First, a quick note on the methodology. The sharper reader will note that some teams' totals don't add up to, and often exceed 100%. The reason is because I don't have data for when each shot was taken so if a player plays 45 minutes I simply use the total shots for the game divided by two as the denominator to work out his share. It's a crude solution but I think over a season it won't particularly pollute the results. Over a couple of games though (as is the case with Benteke) it can lead to outliers. Giroud has been getting a bit of ...

Team Forecast: Goals Powered by Tableau xG Shots  Expected goals based on shot data for both the highlighted team and their opponent to date xG Shots Regressed  Expected goals based on shot data for both teams regressed using league average shot conversion rates. Team Forecast: Clean Sheets Powered by Tableau xG Shots  Expected goals conceded based on shot data for both the highlighted team and their opponent to date xG Shots Regressed  Expected goals conceded based on shot data regressed using league average shot conversion rates. Individual Forecast Powered by Tableau