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Saturday, 27 May 2017

Reading vs Huddersfield, Championship Playoff Final.

The football match for the world's biggest prize takes place at Wembley on Bank Holiday Monday, when the two remaining Championship playoff teams meet to gain entry the the Premier League money mountain.

Much has been and will be written about the two sides, particularly about their less than impressive regular and advanced stats.

Reading, at least managed a positive goal difference of +4 compared to Huddersfield's -2, although the latter impressed more in the probabilistic, process driven world of expected goals.

There's a detailed preview being posted later in the weekend, but as a crib sheet for fans and neutrals alike, here's how the 46 game season looks for both teams through the lens of expected goals.

Each goal attempt has been assigned and expectation of of ending up in the net based on a variety of parameters and their historical contribution to a successful outcome.

Each individual attempt is then simulated along with all the others taken in each match and a scoreline emerges, based on the attempt events in each match.

Score effects will play a part in this partly artificial process and models will not capture every ingredient that goes into a complex team based sport, such as football.

Games have been "replayed" 10,000 times and the percentage of games which end in say a Reading win or a draw for Huddersfield have been counted.

Finally, the match have been arranged in descending order of how well the individual goal attempts and their associated expected goals reflect the actual reality of the result on the day.


Top of Reading's list for "slightly taking the liberty" is their 2-1 win at home to Wolves. The Royals' ExpG totals around 0.5 compared to 1.82 for Wolves. The home team scored with both of their only two shots of note and a simulation of all the attempts from the game suggest they win such a shooting contest 7 times from 100.

A match that kind of sums up the contrasting fortunes of both Reading and Wolves in 2016/17.


(click to enlarge).

Here's all of Reading's league matches, along with the simulated probabilities for each possible outcome. All of the top ten matches and 17 of the top 20 are Reading wins and are also games where the granular shot probabilities were initially skewed in favour of Reading's opponents.



Here's Huddersfield's season and a more mixed bag of game outcomes at the top of the table, perhaps implying that their season hasn't revolved around the Terriers pulling an Al-Habsi sized rabbit out of the hat on more than a few occasions. Unlike Reading.

Data is from the @InfogolApp which can be downloaded free and has historical Premier league, La Liga, Championship, Europa League and Champions League expected goal values for both teams and players.

Thursday, 25 May 2017

The Ticking Premier League Clock.

With the 2016/17 Premier League season now a wrap there's inevitably a raft of season reviews, both statistical and narrative driven.

Already sides are scrambling to pick apart the squads of the three relegated teams and capture the talent that shone brightest amongst the mediocrity.

Improving your Premier League squad for the upcoming 2017/18 season is an obvious priority. The likely output from you current collection of talent does not stand still, principally through the ticking of the clock.

It has been well demonstrated that a player's output, as measured by simple metrics or the amount of playing time he is given first waxes and then wanes (desperately resists obvious pun).

Although there is some positional variations, as well as individuals who possibly fall outside the usual, the peak ages in general for Premier League players lies between the ages of 24 and 29.

It is a simple task the chart which teams are well set to enter 2017/18 with a squad that is likely to show an improvement, just because players who were deemed good enough to be given playing time in 2016/17 are either moving into  the sweet spot for age related peak of performance or are remaining within their peak years.

On the flip side, other teams may be anticipating the need to recruit new, younger talent to replace an ageing squad that may have produced results that are acceptable for the club's perceived status in the Premier League pecking order, but if left unresolved will likely see an age related decline.



In the table above, the weighted amount of playing time given to players has been grouped by age,

This makes it possible to see which teams have a comfortable buffer of young talent that was deemed good enough to play some part in 2016/17 and under normal development will be expected to pick up some of the shortfall from older squad members who may begin to show age related decline.

It's also possible to wind the clock forward to spot which sides are best placed to cope with these transitions in the absence of new signings.

Ominously, Chelsea will likely retain the highest proportion of peak age performers, narrowly followed by fellow Champions League participants, Liverpool and Spurs.

By contrast, Manchester City again find themselves with a dearth of peak age performers from their current squad in the upcoming season, suggesting a bout of major squad reconstruction is imminent.

Monday, 22 May 2017

Tony Pulis Is Not A Slacker

Tony Pulis is never short of narratives.

Since the diminutive Welshman announced his presence on the main Premiership stage, guiding an under funded Stoke team, lacking in top flight talent to perennial survival, he's attracted plaudits and brickbats as the master of squeezing the most from meagre resources.

He's acquired manager of the season awards, as well as acrimony for his dour, anti football, laced with innovation, for which all Stoke fans will forever forgive him, especially as it came with the added bonus of infuriating Arsene Wenger.

Slacker, however, is a term rarely associated with Pulis or his three Premier League charges.

Until now.


Visually the evidence appears damning. In the 54 matches a Pulis led side has played after the black line in the graphic, only 45 points have been won.

That's relegation form in every season and the implication is that a manager who once infamously multi-tasked by cancelling Christmas, while also showering, has allowed his team to slacken when a likely survival target has been met.

So do the numbers support the view that a manager whose mantra is "work 'ard" actually relents during April and May.

"Can I have the month off, boss"?

Firstly, there is an element of selective cutoff points that do Pulis no favours in the graphic.

To surpass any target requires a side to either win or draw and in eight out of the nine seasons, Pulis' side reached the line set in the graphic with a win.

Therefore, just as "X has not won at Y since 2014/15, immediately tells you that they did actually win in 2013/14, each period of "rest and reflection" begins immediately after a positive result and that biases your perception of the ensuing games.

Secondly, gaining points is very difficult for mid to lower ranked teams, epitomised by those TP has managed.

It's quite easy to spot runs of 5 or 6 consecutive matches without a win during periods when Pulis was presumably cracking the whip (or wet towel).

Thirdly, the fixture list can get very unbalanced when broken down into segments of between 12 or just three matches, as has been done in the graphic.

Whether by quirk of the fixture list or design, Pulis has been sent more games against the Premier league's best and Arsenal in the latter phases of the season.

Rather than lounging on a deckchair, they've been taking on Arsenal (6 times), Man City (4 times, including once immediately after a FA Cup Final), Chelsea (3 times), Everton (3 times), Liverpool (3 times), and Manchester United and Spurs, twice each.

That's a disproportionately larger share of the current top 7 compared to a random draw.

The easiest way to quantify how a side has done over a range of games is to simulate the range of possible points won based around a probabilistic model that doesn't incorporate a "doesn't try when safe" variable.

This approach results in Pulis gaining the actual 45 points his sides accumulated or fewer in around 16% of trials.

So the return is an under performance, certainly, but one that might occur in 16% of simulations simply through the randomness of how points are won.


Here's an attempt to cherry pick a single season where the returns are so low compared to a odds based distribution of points that randomness is challenged as a possible contender for the actual points returned in the run in.

Seven out of the nine seasons are unremarkable, the two exceptions are the most recent campaigns at WBA, but even these two examples have respectively a 10 and 7% chance to just be random deviations from a bench line estimate of WBA's ability over the season.

And with a raft of sides hovering around WBA's performance expectation for points won going into April, the chances improve that someone, (not necessarily WBA), will appear to tank their season early.

Even if there is something in the tailing off of a Pulis side in two out of nine seasons, evidence must be presented for a possible cause, which could be plentiful.

Resting players carrying longterm injuries, experimenting with alternative tactical set ups, blooding inexperienced players, seeing your hot and unsustainable production from niche attacking methods regress towards less extreme levels each deserve scrutiny.

The list is nearly endless and almost universally laudable, but Tone giving the lads a breather would be way, way down my list, even if the data supported the claims.....which it doesn't.