Predictions for the English Premier League – A midweek title shift

This will be a rather short post where I’ll run the numbers for my league prediction model again. Most of the workings behind the model are explained in detail in the introductory post, back when the model still held Arsenal in marginally higher regard than City. Oh, wait, that was actually only just over two weeks ago.

 

Bias

“How can someone reasonably have thought that Arsenal was going to win the title? I just knew it was always going to be City. Any decent football watcher could see that. All those models are just crap” (anonymous fictional reply)

Eeuhm, no. This is probably the most frustrating part about going public with predictions in football. You will always be wrong at some point. It’s just the unpredictable nature of the sport. And I could take knowledge of the past two weeks out of the data, re-run the model and confirm that, based on all information at that very point, the model rated Arsenal and City very close. I can’t do that with any human mind.

It’s a form of bias that influences our memory, so that we think we’ve always rated City higher than Arsenal. But if results would have taken another turn, we may just have focused more on that brilliant Özil stuff and Giroud finally picking up on his finishing. Once again, we would have confirm what “we [would] have already known for a long time”.

 

Public

This is exactly the reason why I like to go public with these models from time to time. Let me just put the results of the model out there and see what happens. How do the odds shift upon certain events. In hindsight, we can talk openly about when decisive trends were picked up and why certain teams were over or underrated. That way we can learn, I can learn, and next year, the model will have learned. But if you think ‘I knew it all along’, please just put it out there before events take place and we’ll see. The more models and estimations out there, the more we all learn.

 

Predictions

So, with this ramble over and done with, here we go with the predictions for the league table. The format may start to look familiar now. Boxes correspond to a spread of 50% of the outcomes of simulations around the mean, indicated by the think vertical black line. The other edges mark the 95% interval and dots are true outliers.

The outliers teach us that in extremely unlucky cases a team like Liverpool may even finish below 60 points (they have 46 already, they have Suarez and they have 16 matches left to play), with the same underlying performance they show now. Guess we’ll have a hard time convincing the conservative and trigger happy football world to accept just that, don’t we?

Boxplot projected league table English Premier League 2013-14 30 januari 2014Unsurprisingly, City lead the way after their crushing of Tottenham last night. The model has City finishing around 83 to 84 points, with a margin of just over four points to Arsenal. Both Arsenal and Chelsea have cooled off a bit, after their draws. In all likelihood, Liverpool will finish no lower than fourth and the reds may still hope for more.

 

No battle

Spurs are quite unaffected by the loss, since they had quite a margin to Everton, who lost to Liverpool, and to United, who had still some ground to make up from the start of the season. I’m sorry to disappoint the crowd of football journalists, but the battle for top-4 is just not happening. No team that is presently outside the top 4 holds more than 10% chance of finishing inside that top 4.

Everton and United are by now quite equal, and both have about a one in five chance of making the Europa League. Newcastle, Southampton, Villa and West Brom should probably already be thinking about next season.

 

Relegation

The relegation battle has seen some interesting developments. The most important match was of course Sunderland’s narrow home win over Stoke, which sees the Black Cats reduce their odds to below 50%. Things look pretty dreadful for mr. Tan and mr. Solksjaer, who hold the bottom spot and the model thinks quite firmly that they will go down.

Fulham’s underlying numbers are quite terrible and this fuels the model to give them a 4 out of five chance of relegation. I’m talking most shots and ExpG conceded and 17th in shots and ExpG for, while most of their better production came in the stints against Palace and Villa when they were already two goals up.

I do realize, however, that both teams have new managers, and it’d be interesting to see if this will correspond to a shift in underlying numbers. Obviously, the model will need a bit of time to pick that up, as it also did with Palace under Pulis. But in all honesty, “the firing of the manager has to be explained in relation to other reasons rather than for the expected improvement in team performance”.

Boxplot projected League positions English Premier League 2013-14 30 januari 2014

10 thoughts on “Predictions for the English Premier League – A midweek title shift

  1. Krrishsgk

    Does the model take the remaining fixtures into account? For example, Cardiff face teams from the top 7 four times, while Sunderland have seven such games. Surely thats a valuable 9 points that could make a huge difference?

    Reply
    1. 11tegen11 Post author

      Absolutely.
      The model projects odds for all remaining matches based on the underlying performance of the teams. ExpG is the main driver of that underlying performance input.
      Then, the model runs the remaining season multiple times and what you see is the distribution of points and the corresponding league places.

      Reply
  2. Krrishsgk

    Does that mean strikers, who’ll make up for most of the ExpG score, drive the model? ‘If’ Arsenal were to sign a striker who has a higher ExpG score than Giroud, would their probabilities change for the better?

    Reply
    1. 11tegen11 Post author

      If the striker would lead to the team as a whole producing more ExpG, then yes.
      If the striker would produce more ExpG, but reducing the team ExpG, then no.

      And perhaps you are hinting at the finishing qualities of Giroud, or any other striker. To put that in my model, I would first need to see convincing evidence that finishing quality in the past is a marker for finishing quality in the future…

      Reply
  3. Krrishsgk

    How can a striker produce more ExpG, but reduce the team ExpG?

    And isn’t ExpG metric itself a way of judging finishing quality for the future based on finishing quality in the past?

    Reply
  4. 11tegen11 Post author

    A striker could cannibalize on the chances that would otherwise fall to other players. Strikers like RvP add more to the team than just their goals. Darren Bent is a nice reverse example. You’d get his goals, but he doesn’t increase his team mates’ ExpG, and therefore not the team’s ExpG.

    Your second question is obviously a correct remark.
    If there was a way to judge quality for the future based on anything other than the past, I’d be some kind of wizard you shouldn’t believe…
    Thing with shot ratios like TSR, and it’s enhanced version ExpG, is that what you saw in the past has a high correlation with what you’ll see in the future. That a sign of a good metric.

    Reply
  5. Krrishsgk

    Hmmm I understand.

    On a different note, how do you collect data for ExpG? The various shots taken from various positions on the field?

    Reply
  6. Krrishsgk

    And then manually collate them and calculate probabilities? You’ve combined data from three odd seasons to arrive at the present ExpG values, yes?

    Reply

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