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Given the number of transfers already made (290k at the time of writing), this post is potentially too late, but for those Aguero owners who haven't yet pulled the trigger on a replacement, here are a few factors to consider before you do. The Argentinian's absence seems to be being pegged anywhere between four and six weeks, which means he will almost certainly miss gameweeks 17-21 and his absence could potentially extend through GW22 or even 23 (with good squad depth City should be mindful not to push their talisman and risk further injury as seems to have been the case with Kompany in the past ). With his return therefore scheduled to coincide with the middle of the second wildcard window, the cost to buy Aguero back should essentially be ignored and value for money for right now  is  a factor. This contradicts the situation if he was missing for just a week or two, in which case it might be worth eating his cost to sit on the bench rather than lose 0.5m when you are forc

Whether you're lucky enough to still have your original wildcard stashed away in your back pocket or not, as we approach the second wildcard window, it's worthwhile putting together a transfer plan to best exploit the fixtures on offer. We have at least four transfers before then (GW16-19) followed by the important period right after we play the wildcard, so with that in mind, let's try and identify a few fixture streaks during which we might want to target specific players. For simplicity I've only looked at streaks of four gameweeks here. In reality we might want to dig deeper into streaks where you like three out of four games, or four out of six, but this is the starting point, for better or worse. Double gameweeks will also likely cause chaos at some point too, but without knowing where or when they'll strike, their impact is ignored for now. The below table shows the expected goal total over the four highlighted games above or (below) the team average. So

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As we all know, the fantasy season does not comprise 38 independent events. Medium and even long term plans need to be put in place based on the next 'x' number of games and over-reliance on the now can handcuff your team in the future. Though all teams are constructed differently and thus will encounter these periods at different times, there are also overarching factors which impact all (or at least most) teams in the same way. Sometimes these are obvious, such as the opening of the second-wildcard transfer window or the real-life transfer window which potential opens the door to new options for our teams. On other occasions, however, the trends are tougher to spot, especially when we're in the eye of them (they are much  easier to see with hindsight). We are potentially at a changing point for one of these period-changes. Like any mostly free market, the demand for players will settle into something of an equilibrium, and for most managers the leading role in de

Learn About Tableau

Learn About Tableau

Learn About Tableau

Attack-minded defenders have long been considered one of the key ingredients to a successful fantasy team, and while I may personally suggest this quest is sometimes overpursued, there's no arguing with the overall premise that such a player can be extremely valuable. Two issues arise though. First, managers tend to overvalue this threat, paying huge premiums which simply cannot be justified. The most obvious example of this in recent times has been Leighton Baines (who has rarely justified the huge premium required to get him) though we've seen similar trends in the past with the likes of Thomas Vermaelen, Nemandja Vidic and even Joleon Lescott. Second, managers tend to overvalue past success, which can be ill advised at the best of times but is particularly dangerous with defenders. With a few notable exceptions, defenders tend to enjoy limited chances to earn points and the sample sizes involved are generally very small. Thus, a player with the odd goal coming from a

Learn About Tableau

We had an interesting comment from a reader this week regarding the visualization posted plotting actual points with expected points. My proposition was that the players whose xP trailed their actual points by a distance were likely undervalued by the market, and while we wouldn't suggest they will somehow "make up" those points left on the table to date, we would  expect their production to take an uptick assuming they continue to get chances and playing time at a relatively consistent rate. The reader had a different view: "When I look at this chart I don't see underperformers or overperformers all I see is players on form who are capitalising on their chances (Ramsey and Rooney) and players who are of such quality that they will always out perform the normal (Aguero and Yaya) . . . I believe that if you reconstructed this table after xmas with a start date of tomorrow then the same players would occupy the two sides." It's a fair proposition and

The below chart is something I've posted before and am tweaking for the new website so I thought I should post it now and get your feedback while also hopefully providing a quick view to identifying some players to research further: Learn About Tableau

Post any questions in the comments below, on Twitter or on Facebook and I'll get to the best ones before this week's deadline. Learn About Tableau

The revised strategy for this season is to post the weekly preview data as soon as possible, giving you (a) the chance to use it to help with any early transfer decisions and (b) to collate questions on why a given player is so low or high, to be answered on Fridays before the transfer deadline. Learn About Tableau

Learn About Tableau Given how early in the season we are, the model is still liable to throw up the odd outlier and so in these weekly posts I plan to address those, shall we say, unexpected results. In future weeks, the plan is to post the data as soon as possible after the final games' data is up and then you can raise questions/issues during the week, to be addressed on either the following Thursday or Friday. For this week, I'll just try and guess where the questions might lie: Keiren Westwood Sunderland have conceded at least two goals in six straight contests, yet the model thinks they'll do okay this week. What gives? Well, having conceded 7.3 shots inside the box at home, they're hardly a team without hope (that alone would be the 9th best  total of the teams playing this week). Add to that the fact that Newcastle have averaged 30% less SiB against their opponents than average, while only averaging 6.0 SiB on their travels, and you get a game where w

As a quick introduction for those new to the blog, this piece runs every couple of weeks during the season and looks to shine a light on those "hot" players whose "form" looks unsustainable and those "cold" players who should enjoy success in the future if they keep playing the way they have to date. The below chart shows this week's subjects, with those on the left having outscored their underlying data and those on the right having outperformed their score. Before we start, as is becoming a tendency on this blog, I need to add a quick caveat as to exactly what we're saying here. First, we are not  saying that a player will somehow "get back" or "give back" their production to date or that bad luck will necessarily follow good luck. We are saying that players' (and teams') conversion rates should regress to the mean , seeing them earn points at a rate more in line with their underlying stats (which could be a good

Producing forecasts is a tricky business. Even with hindsight it is tough to predict the expected outcome of a given game (i.e. how shots transform into goals) and that problem increases exponentially when you also need to try and forecast the underlying data. Throw in uncertainty around how much players will play and the issue of small sample sizes and you have a recipe for some funky results over these early weeks of the season. First, to make sure the model isn't totally off track, let's look at how it performs retrospectively over the first seven weeks of the season (using actual  shot totals as inputs): Learn About Tableau Though we can see outliers in the above chart (especially at the top end of the market), the overall trend is promising and the r-squared of 57% for players with a risk factor of 2.5 or less is encouraging enough. That's not to say it's infallible, but it's a good start and for the majority of the extreme outliers we can point to sp