I may be a bit premature here, but it seems to me the major parts of the Premier League season are pretty much decided. Leicester City seems uncatchable at the top. Arsenal and Spurs will finish 2nd and 3rd (or 3rd and 2nd) while Man City looks pretty solid for 4th. Two of the three relegation spots are basically sealed, but there’s still the matter of whether Norwich City or Sunderland stay up. Because my interest in the season has waned significantly, I thought I’d do an early “year-in-review” where I assess MOTSON’s biggest hits and biggest misses. I’ll start with the obvious.
Yeah, I don’t know what to say about this. I had Chelsea in second place at the beginning of the season and they look to be stuck in literally the middle of the table. Everyone else was roughly in the same boat MOTSON was, and I honestly don’t know if this could have been foreseen. *Maybe* if you added a “Mourinho third year implosion” variable to the model, but even then would you have guessed 10th place? Nevertheless, it’s a pretty big miss and was the source of the majority of the error in my model.
I’m going to call this a hit and a miss, but more of a miss than a hit to be honest. I’ve been particularly proud of MOTSON predicting Leicester City higher than anyone else – 8th place on 60 points. Not bad, and if they finished 3rd or lower I was willing to call this a huge success for the model. On the other hand, if they win the title this year then it’s hard to say “I had the Champs in 8th place – I win!” I’m proud that my model recognized them as good long before anyone else did, and if you look at a lot of analytics prognostications for next year they’re saying “Leicester’s probably 7th or 8th place” so MOTSON is 9 months ahead of the curve there. But it’s a small victory assuming they win the league with 15-20 points more than I predicted.
That being said, MOTSON was ahead of the curve predicting them as Champions League qualifiers, picking them to qualify as of December 5. I know this because on December 4th I wrote that they should obviously sell Jamie Vardy because they had no expectation of the Champions League and December 6th changed my mind.
MOTSON *hated* this signing by Man City back in August, and it turned out to be right. He was a disaster in City’s backline, and is one of the reasons City’s fighting for 4th instead of comfortably coasting into the Champions League.
So MOTSON didn’t get West Ham’s success right pre-season, but it did pick up on their top 6 challenge *very* early in the season (October 24). Mike Goodman and I had a conversation about this, and I argued that West Ham banking those 8 points over expectations would be enough to get them a top 6 spot. As of today they’re 10 points over expectation, so they’ve basically broken even since then and look to be in the top 6 at the end of the season.
In all the talk of Chelsea underachieving, we haven't talked about West Ham overachieving. They look to be for real pic.twitter.com/Uv81BWuSFy
— Chad Murphy (@Soccermetric) October 24, 2015
Leicester City Redux
MOTSON really liked Jamie Vardy to have a big year this year, something I didn’t notice until it had already happened because he wasn’t on my radar.
It also really liked Riyad Mahrez, pegging his replacement as something like a 10 point downgrade.
On the other hand, I never posted anything along these lines, but it didn’t really like the N’golo Kante signing which I’d classify as a pretty big miss. He’s been phenomenal for them and MOTSON would have told them to pass.
Barcelona Will Be Fine Without Messi
Lionel Messi got injured in the early part of the season, out for a month, and “real football men” wrote all sorts of thinkpieces about how Barcelona would be in trouble losing the world’s best player despite having two other world class strikers on the pitch even in Messi’s absence (and decent young backups filling in). MOTSON got it right: Barcelona would be fine without him, and they were. This is one of my favorite analytics pieces I’ve written, so I wanted to bump it.
Those are the big ones I can remember – plenty of successes for its first year with out of sample data but plenty of room for improvement as well. I may revisit this at some point, but for now I think this is a good recap of the model. Thanks for reading, and this summer I’ll be focusing on bringing statistics to the NWSL so keep an eye out for that.