Allsvenskan 2016 summary pt. 1

With the season ending more than a week ago, I finally have enough time to sit down and write a summary. I’ll split it in parts, with the first two looking at team and player performance respectively, and hopefully I’ll get around to writing a third part in which I look at how my predictions have done, and the model’s performance on the betting markets.

These kind of updates likely won’t return for next season when I’ll be taking on a new job compiling odds on Swedish football. I’m hoping to continue writing in some form though.

But enough about that, let’s get to it:

00

As most expected, Malmö bounced back from last season’s 5th place to reclaim the title from Norrköping. Luckily they did so without the need of the extra win awarded to them after the abandonded game against Göteborg where the home fans threw pyrotechnics against the Malmö players – and Tobias Sana responded with a spear throw.

At the other end of the table, Gefle were finally relegated after several years of clinging to their place in the top flight. Falkenberg’s extremely poor season saw them relegated as well, while Helsingborg will have to face third placed Superettan side Halmstad in a two-leg relegation play-off.

Take a look at Djurgården’s row of results by the way, only one draw!

01

Malmö were the best side in terms of shots taken and conceded as well, while bottom duo Gefle and Falkenberg really struggled together with Sundsvall, whose good start to the season saw them able to avoid the relegation battle despite only picking up two wins after the summer break. Örebro was an outlier throughout the season, usually producing some high-shooting games.

02

Göteborg were the most efficient attacking side during the season, but their low shot volume saw them unable to compete with the real top sides. AIK and Malmö relied on pure shot volume instead, probably a result of their ability to dominate games. Falkenberg on the other hand really struggled with both volume and effectiveness, usually needing nearly 11 shots to score.

03

At the other end of the pitch we see partly why Malmö were the superior side this season, and why AIK finally overtook Norrköping in second place: they both enjoyed some very efficient defending, clearly outperforming their opponents. Falkenberg struggled here as well, conceding a goal about every 5th shot, while Örebro actually did well efficiency-wise despite conceding a lot of shots.

04

Champions Malmö were the best side in terms of both xG and xG conceded, while Falkenberg’s poor defence was a big factor in their relegation. Djurgården, Hammarby and Östersund did better defensively than their final positions in the table might suggest, unable to break into the top mostly because of their weaker attacking output.

05

Ranking the teams by Expected Goals Difference did well to explain both ends of the table, getting the top 3 and bottom 2 correct. As mentioned, Sundsvall’s ‘lucky’ results at the start of the season saw them avoid the relegation battle, while Östersund, Hammarby and Djurgården formed an underperfoming trio just below the top sides.

06

Simulating every game based on the shots taken and their xG values, we can give the teams ‘Expected Points’. This is very close to the xGD rankings above but we can see some differences, like Falkenberg ‘earning’ almost as many Expected Points as Gefle, which they were no way near in reality.

Let’s see how the teams actually did compared to their Expected Points:

07

What we see is that typically the winning sides overperform against Expected Points, while the losing sides underperform. This is to be expected as you’ll very rarely (or never) dominate a game enough for your expected points to match the three actual points awarded for a win. The same goes for losing, since you’ll pretty much always ‘earn’ more than zero Expected Points.

08

There’s always exceptions to the rule though, and this season Gefle stands out as having picked up pretty much exactly the points expected from them which I would say is rare for a losing side, while Falkenberg look to have been very unlucky to pick up so few points.

09

Looking at the Expected Points distributions for the teams, we really see just how ‘unlucky’ Falkenberg have been. As mentioned above, losing sides will very often underperform against Expected Points but Falkenberg really stands out with a 100% chance of picking up at least the 10 points they ended up with, implied by the 10,000 seasons I ran through my simulation.

Djurgården

As I’ve done in a few updates, I’ll end this one looking at Djurgården. As a lifelong supporter I’ve become used to the ups and downs but despite that and the underlying good numbers I was still a bit concerned this season.

10

Luckily though, Mark Dempsey, the right man at the right time, stepped in and turned things around much like his former mentor Per-Mathias Høgmo did in 2013. Just like I’ve seen him do in Norway, Dempsey focused on a very direct attack which worked well to improve shot numbers and level out Djurgården’s dropping xGD, while at the same time crucially also getting some real results.

Defence continued to struggle though, and no real tactics but ‘get the ball up to the big boys up front’ was clearly visible – a decent game plan to get them out of the hole they’ve dug themselves into but not something to build on for the future so the club’s decision to not give Dempsey a new contract looks reasonable.

That’s it for now, in a few days I’ll be looking closer at individual player performance.

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Allsvenskan 2016 summary pt. 1

3 thoughts on “Allsvenskan 2016 summary pt. 1

  1. Conor says:

    This is to be expected as you’ll very rarely (or never) dominate a game enough for your expected points to match the three actual points awarded for a win. The same goes for losing, since you’ll pretty much always ‘earn’ more than zero Expected Points.

    I’m not sure this is the reason for this. In a one off game yes the winning team will always outperform their expected points. Over a 30 game season it should even itself out though, they can drop points in games where they were huge favourites to win. I’d suggest efficiency and “luck” combine for teams to outperform those expected goals models.

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