Category Archives: Predictions

Week 14: Aston Villa v. Watford Consequences

Here’s the quick rundown on the relegation six-pointer between Aston Villa and Watford. Aston Villa is a favorite in this match at home over fellow relegation contenders Watford, and with their performance so far this game is taking on “must-win” status early in the season.

Week 14 Villa v Watford

Three points would help Villa pick up about 1.4 points on expectations, which is especially important given they are underperforming by about 6 points so far. How much would this help in the relegation battle though?

Week 14 Aston Villa

According to my model, a loss puts Aston Villa in the relegation zone about 86% of the time, which is a big hole to dig out of so early in the season. A draw keeps their odds about the same, but makes them about 10% less likely to finish in last place, which gives them some room to maneuver but still isn’t ideal. A win however drops their relegation chances to about 70%, and drops their likelihood of finishing in last place by 20%. Still not ideal, but definitely would give them some hope. You can see in the above figure how much lighter the 20th place box gets with a win for Villa.

Meanwhile, a loss doesn’t hurt Watford too much, putting them at about 28% for relegation. A draw puts them at 20% chance for relegation, but a win drops that to 10%. Villa needs this win to get some hope and to have something to build on, Watford can significantly reduce their chances of relegation with a win of their own. A draw doesn’t really work for either of these teams, so I’d expect both of them to come out swinging.






Chelsea v. Spurs is a UCL 6 Pointer: Top 4 Implications of This Weekend’s Fixture

It’s awfully early to be thinking this way, but Chelsea and Spurs have a huge game this weekend. It’s really early in the season this sort of thing, but looking at the predicted probabilities this game could have significant implications on the race for fourth place. Here’s the heat map of predicted probabilities based on the potential results for both teams:

Week 14 Chelsea v. Spurs

It’s striking how similar the two heat maps look, the predicted probabilities are virtually identical for the two teams for each of the three results. A loss drops Spurs’s chances for the Top 4 down to 21%, while a loss for Chelsea drops them down to 18%. A tie puts Spurs at 29% while Chelsea has a 28% chance of finishing top 4, while a win gives both Spurs and Chelsea a 42% chance.

Thinking about pre-season expectations, the strategies here might be very different: Chelsea only having a 42% chance is really low but 18% (and falling) is unacceptable for them. Meanwhile, Spurs would be ecstatic with a 42% chance at this point in the season, while 21% would still likely be ahead of pre-season expectations. Emotionally, Spurs have less to lose and everything to gain so I would expect Pochettino to go for the win here. On the other side, Mourinho might be inclined to play it safe, play for a 0-0 draw (while hopefully stealing a win on a Willian free kick), and live to fight another day. Stopping Spurs from picking up the full three points could be as important as getting something from the match themselves.

Meanwhile, Liverpool has a slight preference for a draw, but their likelihood of top 4 isn’t really affected by what happens in Chelsea v. Spurs, leaving them at about 30% to qualify.

Week 14 Liverpool

The match is probably worth watching for the drama and early season implications, but I wouldn’t be surprised if it was a boring outing for neutrals.  There aren’t many games this early that could have such huge implications for the end of the season, so it’s worth keeping an eye on for Spurs and Chelsea fans alike.






Chelsea, Minimum Points needed to Make the Top 4, and Overachievement

One of the big topics on Twitter today has been whether Chelsea can still qualify for the top 4, and various folks have posted their predictions/simulations on what it will take. Michael Caley predicted 68.6 points, Colin Trainor and Simon Gleave have both agreed at 68 points, and I’m sure there are others out there. My model is a bit lower than the rest of these at 62 points, with 69 being my prediction for the third place team.

Week 13-3 Predicted Final Table

These results represent the mean points I expect each team to earn based on the remaining games and their probabilities of winning. For my predicted table I don’t do any simulations, just some simple arithmetic to get there1. Someone else on Twitter asked the question “Don’t models underpredict?” and while the right answer is no, there is some truth to this point, and that truth explains why Chelsea is probably less likely to win that fourth place spot than even the most skeptical models say (and far less than mine).

Right now I have four teams roughly tied for fourth place – Chelsea, Spurs, Liverpool, and Leicester City. Each of those teams is expected to earn between 60 and 62 points, which is a pretty tight race. But logically we’d expect a very different outcome. While we’d expect the teams to cluster around the mean, it’s likely that one team will find a purple patch, and that team will be the one who captures the 4th and final spot in the Champions League. So what do the simulations say?

DISCLAIMER: My model clearly overrates Chelsea so take their numbers with the largest grain of salt you can imagine. However, the model overvaluing Chelsea only means it’s going to be less likely we see these high point values for the 4th place team. 

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This density plot shows the results of 10,000 simulations, showing the number of points  each of the current contenders for the 4th place spot (ignoring those in the expected top 3) earns and the frequency of those outcomes. Chelsea has a decent chance of earning 65 points, and a low chance of earning 69 points, even at their overstated current expectations. The other three teams have a much lower likelihood of each of those outcomes. Spurs seem to have a slight but important advantage over Liverpool and Leicester, but that could change as we get more results. Leicester clearly is the least likely of these teams to make the top 4 but they’d have to be elated to even be in the conversation at this point.

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The next plot shows the likelihood of each team finishing with over 65 points. Chelsea about a 43% chance of breaking 65 points (again, see the disclaimer above), while the others are 20% or less. The joint probability of at least one of these teams finishing with over 65 points is 57%, and one of the teams other than Chelsea finishing higher than 65 is about 24%. Even given the idea that one of the teams could hit a hot streak and overachieve, or in Leicester’s case overachieve even more than they already are, we’re looking at an unlikely low point total for the 4th place team.

Finally, I look at the likelihood of finishing at 68 points or higher. Chelsea again leads the pack at about 31% (disclaimer), while the others are pretty unlikely to finish that well. Spurs are a little above 10%, Liverpool at about 7%, and Leicester at about 1%. At least one team will finish at 68 or higher 40% of the time, and a team other than Chelsea will finish at 68 or higher 14% of the time.

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My simulations indicate we’re going to see a much lower point total required for the Champions League than we’re used to, and a more competitive race for that spot than we’ve seen in years. Depending on what happens with Chelsea and if Leicester can keep up their pace, it could be a great finish to the season.

 

 

  1. I just do 3*(win prob)+ 1*(draw prob) + 0*(loss prob)

Leicester City is Performing as Well as Chelsea is Poorly

With another decent upset today, combined with losses by the two league leaders, Leicester City moved to the top of the EPL table today for the week. This is particularly impressive given that a year ago today they were at the bottom of the table, and preparing for a relegation fight they would barely survive. Because Chelsea managed to beat Norwich City at Stamford Bridge, we were given a respite from “Chelsea in crisis” stories and are finally talking about Leicester City. But how well are they performing?

In a slight moment of bragging, I would like to say that my model tipped Leicester to have a pretty good season, picking them to finish 8th in my pre-season analysis. Clearly my SVM (which I’m calling “Model of the Same old Nonsense”, or “MOTSON”) saw something in their team at the beginning of the season, despite a bad TAM Coefficient from the season before.Preseason Predicted Final Table

However, even with my lofty predictions, they’ve managed to over-perform to the tune of a +10 over expectations, which is remarkable given the already high prediction my model had for them. Compare this to Chelsea’s disastrous season where they are 12 points below expectations, and it’s evident that Leicester is in the middle of a special season here.

Week 13-1 Deviation

Analytics TwitterTM  pointed out that their next 6 games are particularly difficult: Man United (h), Swansea (a), Chelsea (h), Everton (a), Liverpool (a), and Man City (h). But the good news for Leicester City is that I only have them expected to pick up 6.42 points out of these 6 fixtures, or basically 1 point a game. So even if their pace cools off quite a bit (which you’d expect), they don’t have to do much to stay at the level they’re at through the first set of fixtures, which has them challenging for a European place and starting to separate from the pack a little bit,  especially if/when Chelsea drops off a little bit more. The Leicester/Chelsea fixture could be particularly important – I have them as a *slight* favorite actually, expected to win 1.39 points compared to 1.2 for Chelsea. Who would have thought in the pre-season that this could be a Europa League 6 pointer?

Week 12 Heat Map

I’ll leave the “Can Leicester maintain their form?” posts to others, but for my purposes it’s important to note that MOTSON hasn’t updated its predictions with Leicester’s form. Even if they only perform at pre-season levels they’ll be in contention for a European spot. It will be interesting to see what happens over the next 6 games, but their expected points from the next fixtures are low enough that they shouldn’t have much of a problem meeting them and staying up where they are as we go into the return fixtures.






The Single-Minded Forsakers of Relegation

Sunderland’s disappointing start to the season saw them bring in Sam Allardyce, and it sounds like the vultures are starting to circle at Aston Villa. Both teams have underachieved significantly so far, only out-paced at the bottom of my underperformers list so far this season by Chelsea. It should go without saying that Chelsea has the quality to avoid relegation, but Aston Villa and Sunderland both have to be concerned.

Deviation Bar Week 8-2

One of the most influential books in political science is Congress: The Electoral Connection by David Mayhew, and in it he coins the phrase “single-minded seekers of re-election” The main argument is that members of Congress care about nothing other than re-election, and will pursue that goal single-mindedly. Richard Fenno relaxes this assumption a little bit, giving politicians goals like making good public policy and pursuing power in the institution, but his caveat is key: members of Congress cannot pursue other goals without achieving the primary goal, re-election. EPL teams have a similar goal: avoiding relegation, and Sunderland and Aston Villa prove this. EPL teams are single-minded forsakers of relegation – consolidating the league status is concern #1, and no other concerns matter until #1 is met.

Sunderland signing Sam Allardyce, much like West Ham before them, was met with any number of jokes about his boring, direct style of football.1 But he’s a proven manager who did a great job of consolidating West Ham’s position in the league, putting them into a good position where they can hire a manager who plays a more interesting style without worrying their league position. With relegation seemingly out of the question, West Ham can afford to move on to concerns about playing an attractive style. Sunderland doesn’t have the same luxury, so Allardyce is their best choice.

Similarly, reportedly one of the reasons Aston Villa originally tapped Tim Sherwood to be their manager was his track record in developing young players. Aston Villa has been investing in youth for quite a while now and they have some promising potential stars, Jack Grealish being toward the top of the list. However good he may be, and however good Tim Sherwood may be at developing players, they may not have the luxury of keeping either one of them at the club. My model thinks replacing Grealish gives Aston Villa the highest upside, with a shocking 20 point increase for the max player, and an average of over 4 points. Aston Villa Max Replacements Aston Villa Average Points

Everyone likes the idea of having future stars in their lineup, especially a home-grown, local player like Jack Grealish. And everyone likes a manager who can develop young players into the next generation of stars. But if the rumor mill is true and Tim Sherwood’s position is tenuous, it’s yet another example of how teams are single-minded forsakers of relegation. Staying in the Premier League is job #1, and it’s the only one that matters because without it, you can’t achieve any of the others. Putting the youth project at least partially on the backburner might be necessary to forsake relegation and maintain their Premier League status.

 

 






  1. My favorite was a gif labeling Mourinho as “The Special One” while labeling Allardyce as “Route One.”

How Good Is Everton’s Start Exactly?

Earlier today I posted about Chelsea’s abysmal start,  now I wanted to post about how well Everton is doing. They’ve been one of the surprises of the year for my model, and I wanted to investigate exactly how good they have been.

Just like in my previous post,  I took the probabilities for Everton’s first 8 matches generated by my SVM model and ran 100,000 simulated seasons. I did this by drawing a random sample of “win, draw, loss” for game 1 based on the predicted probabilities for that game, then drawing another sample for game 2, game 3, etc. through game 8.   Then I added up the total points earned for those eight games, and counted it as 1 season (so far). I repeated this process 100,000 times, and tabulated the total number of points earned for each season. Here’s what I found.

Eight Game Sims Everton

Everton’s start is a solid 5 points above expectations, earning 13 points compared to a most likely outcome of only 8 points. This has taken them out of any talk of relegation, and has likely ended any talk of Roberto Martinez being on the chopping block. More impressively, this puts them above the 92nd percentile of all predicted seasons so far, with less than 8% of all the simulated seasons scoring more highly than Everton’s early season form.

A great start for Everton, and if they can keep it up they’ll be in good stead for the remainder of the season.






EPL Predictions: Game Day 8. City, Chelsea, and Arsenal Big Favorites.

 

 

 

 

 

Here are my model’s predictions for Game Day 8. The model likes City and Chelsea to win easily in their home games, and has Arsenal as a surprisingly big favorite over Manchester United in the big rivalry game.  Liverpool and Spurs round out the top 6, both with competitive road fixtures this week. Man United winning could be an opportunity to move up the expected table, although I’d be surprised if City and Chelsea lost.

The relegation round-up is pretty interesting this week, with many of the teams in my predicted bottom 5 facing winnable games. Aston Villa has a real chance against Stoke City, and while nothing this early is a “must-win” I think Villa needs to get 3 points here to feel good about avoiding the drop. Bournemouth and Watford are in a close battle, with Watford having the edge on the road in the 6 pointer, and Norwich City is a slight underdog at home to red-hot Leicester City.  See all my predictions in the image below:

Predictions Week 8






Arsenal Takes Back the Lead~! Week 7 Expected Table and Over-achievers

Week 7 results are in, and we have a new leader at the top of the table. With their tricky away win over Leicester, combined with Manchester City’s loss to Spurs, for the first time since week 3, Arsenal claims the top spot in my expected final table.

EPL Table Week 7-2

My model continues to miss the boat on Everton, as they are now the highest ranked team in the over-achiever table (performance compared to expectation). I’m a big believer that West Ham is just statistical noise and they’ll be back to mid-table in no time, but I sincerely think the model is off on Everton. I’ll do some exploratory data analysis later, but that’s my instinct. Deviation Table Week 7-2

Chelsea’s draw against fellow underachievers Newcastle drops them back another point or so, and I’m sincerely worried about Sunderland. They weren’t predicted to do that well in the pre-season model, and they’ve managed to underachieve even those low expectations.

Model fit is still pretty good, indistinguishable from a slope of 1 and intercept of 0, r = 0.55 which isn’t bad this early in the season. Teams above the line are over-achieving, teams under it are under-achieving. Most teams fit pretty well, which makes me confident in my model this early in the season.

Deviation Plot Week 7-2






 

 

Will Barcelona Be Fine Without Messi?

The big news this weekend was obviously Lionel Messi’s injury, and the question is what Barcelona will do without him. Michael Caley issued his take at the Washington Post saying that Barcelona will largely be fine without him, and ultimately I agree. I ran Barcelona through my transfer simulator, and found that Messi gives Barcelona on average an approximately 5% greater chance of winning each game he plays in over his replacement (El Haddadi). Over 8 games that translates to a little less than a point.

Messi Barplot

That’s not a big difference, so Barcelona shouldn’t really worry too much. As great as he is, the rest of the team is strong enough (and the rest of La Liga is weak enough) that it shouldn’t make a huge difference. However, the average doesn’t tell the full story and if we’re going to call what we do “fancy stats” then we need to do better than just calculating the average and moving on.

To see the potential loss of points, I ran 100,000 simulations of an 8 game window for Barcelona with Messi, and then ran 100,000 simulations of an 8 game window for Barcelona without Messi. I added up the total number of points for each of the 200,000 windows, and compared each window with Messi to the corresponding one without Messi. Here’s what I found.

The first plot isn’t the easiest to read, so let me explain: the height of the line (measured by the y-axis) represents the proportion of simulations where Barcelona earns a specific number of points (represented on the x-axis). The dark blue, solid line represents Barcelona with Messi, the light blue, dashed line, represents Barcelona without Messi. Notice the higher light blue line at lower values on the x-axis: this shows Barcelona is significantly more likely to earn lower numbers of points without Messi. Then notice the higher dark blue line at higher values on the x-axis, showing Barcelona is more likely to earn higher numbers of points with Messi.

Messi Density Two Lines

The next plot is a density plot showing the difference between the two scenarios: how often will Barcelona gain/lose certain point values when Messi plays compared to when Messi doesn’t play?  The y-axis represents the frequency of each result in my simulations, and the x-axis represents the number of points Barcelona gained in each of the simulations.

Messi Density Plot Diff

The distribution looks relatively normally distributed (a rough “bell curve”) with a mean around 1, but the standard deviation is somewhere around 5. Barcelona is more likely to do well when Messi plays compared to when he doesn’t, but there is significant variation here. They could easily improve by 5 points, and there’s a 5% chance they improve by more than 11 (out of 24)  points with Messi in the lineup compared to El Haddadi.

The final play I’m going to call the “luck” index. It shows the percentile of each possible point gain/loss based on Messi playing compared to El Haddadi. Basically depending on Barcelona’s luck, this is how many points they can expect to gain/lose.

Messi Out

Once again, this represents the difference in Messi vs. El Haddadi at every 10th percentile. So you can see if Barcelona gets really lucky (best 10% of all simulations) they will pick up 7 points with Messi. Even slightly above average luck (70th percentile, or 30% of the time) they gain 3 points with Messi playing over 8 games.

I largely agree with Michael Caley and Goalimpact’s analyses1 that Barcelona will be fine. But 8 games isn’t nearly enough for the law of large numbers to kick in, and in the short-term the probability distributions could hurt Barcelona substantially, especially with the razor-thin margins in La Liga.

 






  1. @Goalimpact on Twitter is a great resources, and his website is really interesting an creative for football stats fans

Game Day 7 Predictions: Arsenal, City, and Chelsea Have Tough Away Fixtures

Potentially a big week this week at the top of the table. Chelsea, Arsenal, and Man City all have difficult away fixtures so any win could make a significant difference in the end of season table.

Meanwhile Manchester United is a big favorite, and Liverpool is an equally big favorite in a must-win game for Brendan Rodgers. Southampton fans should be happy with the model’s predictions of a win over Swansea, and West Ham’s a big favorite over Norwich City which almost certainly means we can expect them to lose.

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