What’s Wrong with Stuart Armstrong?

Many describe third place teams in the Champions League groups “parachuting” into the Europa League. If we apply this metaphor to Celtic’s performance in their final Champions League group match against Anderlecht, the Celtic plane suffered some turbulence before the crew ejected and headed into the Europa League and Stuart Armstrong was the drunk pilot doing shots of whiskey before take off.

Overly complicated metaphors aside, Stuart Armstrong’s performance in the first half at home to Anderlecht had many Celtic supporters ready to move on from the midfielder. Armstrong is coming off a season last year where he was seemingly the first name on the Celtic team sheet, getting call ups and starts for the Scottish National team, and even leading the Tartan Army to victory (albeit too little too late for the World Cup). Armstrong finished the SPFL season 13 goals and 6 assists, good for a 0.79 Goals + Assists per 90 minutes.

However, as this season began and the good feeling surrounding the well quaffed Happy Armstrong.jpgmidfielder started to fade away. Armstrong was on a contract that expired at the end of the season and seemed to be an impasse on a new agreement. Though a one year extension was eventually agreed to, as fans sometimes do, Celtic supporters were not too pleased with a player who seemed to be looking for greener pastures.

This feeling, combined with a reduction in goals and assists has only furthered the belief among some Celtic supporters that Stuart Armstrong is now surplus to requirements. Indeed, Armstrong is on the score sheet less, scoring only 1 goal and 3 assists so far in league play, 0.49 Goals + Assists per 90 minutes in the SPFL. These numbers have some Celtic fans asking, “What is wrong with Stuart Armstrong?”

And the answer to that question is “Nothing, thanks.” We can expand upon that answer and add a “regressing to the mean”. If you are here, you are likely at least somewhat familiar with the advanced stats in football and that they may tell us more about a players performance compared to traditional stats. While Armstrong may not be hitting the heights he did last season in goals and assists, what do these underlying stats such as xG, xA and others say?

If we first compare expected goals for Stuart Armstrong, we do see numbers that have gotten worse so far this season. Last season in 2,168 minutes, Armstrong had an xG per 90 minutes of 0.33. If we compare that to this season, we see a decreased xG at 0.12 per 90 in 818 minutes. It seems so far that the midfielder is no longer the goal threat he was last season.

Armstrong Goals and xG Graph.png
Since last year, we see Armstrong’s goal scoring come closer to his xG

However, we might need to dig a little deeper into these shot numbers. First, let us address the elephant in the room with Armstrong’s xG numbers last year. Despite putting up very impressive numbers, Armstrong overachieved his xG numbers in his goals scored, scoring 13 goals with an xG of 7.90. Now, some players are able to consistently able to over-achieve their xG over multiple seasons, but so far this season it seems Armstrong is not showing he is able to do that.

Of course, it is still too early in the season to come to widespread conclusions, however there is no shame for a central midfielder not being able to continuously finish at that high of a rate. With his xG total at 1.02 and 1 goal scored, Armstrong is about at where we would expect. In addition to perhaps seeing a regression to the mean scoring goals, Stuart Armstrong has also found additional competition for spots in the Celtic midfield.

While Armstrong was not around the Celtic first team until this time last season, Action Stu.jpgfrom that point on it seemed he was one of the first names on Brendan Rodgers team sheet. However, this season we have seen the emergence of Callum McGregor, goal scoring threat, as well as Oliver Ntcham’s arrival. McGregor has contributed 5 goals already this season in league play, while Ntcham has also added 3 goals.

This competition has seen Armstrong playing less. Last season, Armstrong appeared in 63.39% of available minutes in league play, while this season he has only appeared in 54.37% of available minutes. He has seen a slightly reduced role so far this season, but while he has not been able to score as much for Celtic this season, he has contributed to the attack other ways.

While Armstrong might be seeing some regression when it comes to goal scoring and xG, his passing numbers suggest he is at a similar if not better level than he was last season. Last season, he averaged 0.24 xA per 90 minutes, while this year he is averaging 0.29 xA per 90. He averaged 1.79 Key Passes per 90 minutes (or passes that lead to a shot), but is averaging 2.4 this season. All of this has lead to a similar Assists per 90 minutes for Armstrong as last season, averaging 0.37 per 90 this year compared to 0.42 last season. He is setting up his teammates just as well when he is playing, he is just seeing them converted at a slightly reduced rate.

Stuart Armstrong Pass Map.png

Along with stats showing how he sets up shots, Armstrong also seems to be just as vital in Celtic’s attack overall as he was last season. Looking at xSA, which quantifies the pass before the pass before the shot, Armstong is averaging 0.17 xSA per 90 minutes this season, while last season he averaged 0.07 per 90. This is another metric showing Armstrong has been more than a great head of hair this season.

Armstrong Assists xA.png
Armstrong’s xA and assist numbers have stabilized and remained consistent.

Tuesday night was a rough night for Celtic and their supporters. There is no hiding that Armstrong had a poor game and was subbed out because of it. This game seemed to be the final piece of evidence for many Celtic supporters that Armstrong has regressed and is no longer necessary. However, over this European campaign, who DID have good performances? Ntcham seemed to do much better than Armstrong at home against Anderlecht and set up goals in Belgium, yet his passing was erratic before those goals. The list of Celtic players who get a passing grade in Europe this campaign is a short one and casting Stuart Armstrong aside because of a small sample against superior competition seems short sided.

Yet, Armstrong still seems destined for pastures new soon. He added a year to his contract, but will find himself on an expiring contract at the start of next season. While he his stats suggest a player still able to create for his teammates, we might not be able to expect a double digit goal total from him every year. If Celtic were to get in offer in January or in the summer that is near their valuation of him, it might be wise to sell. If someone offers a transfer sum for a goal scoring midfielder for Armstrong, I would certainly take that offer.

This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.

B.U.R.L.E.Y. Adjusts His Predicted SPFL Table

It seemed like a good time to check in with B.U.R.L.E.Y. and see how he sees the SPFL Premiership table shaking out, mostly because a few people asked me and I had time to update everything. If you are wondering what exactly B.U.R.L.E.Y. is, let me direct you to this link where I describe my SPFL projection model and his picks for this year. Before we get to who B.U.R.L.E.Y. sees going down and who will be in the top six, let me first point out that B.U.R.L.E.Y. has correctly picked 3 matches more than both FiveThirtyEight and you dopes. Go ahead and picture a robot with Craig Burley’s head scoring a goal, doing a front flip, and then completing a 20 yard knee slide to the corner flag.

Burley Crowds 538.png

Now that we have that out of the way, let us dive into how B.U.R.L.E.Y. sees each SPFL club finishing. First, I would like to note that the projections go through 33 matches this season, right up to where the league splits in half. The last column is the points per game B.U.R.L.E.Y. projects each team to have through 33 matches multiplied by 38. It is not perfect, but neither is playing 38 games with 12 teams in the league, so here we are.

BURLEY Projected Table

B.U.R.L.E.Y. probably will not get much credit for picking a Celtic-Rangers top 2, but B.U.R.L.E.Y sees the big Glasgow clubs separating themselves from the rest of the league. The top six according to B.U.R.L.E.Y. is a bit more interesting, with Aberdeen, Hibs, Motherwell, and Hamilton (??). St. Johnstone and Hearts are projected to finish in the bottom half, with Partick Thistle projected to go down and Ross County in the relegation playoff spot. Will B.U.R.L.E.Y. get these picks right or will some club go and stick in the robot’s eye? As some cliche spouting coach of something that I forget the name of said, “that’s why you play the game.”

Scottish Football Graduating to “Advanced” Expected Goals

Congratulations Scotland, you have passed Intro to Expected Goals and are now movingProfessor.jpg onto the advanced class. Most following me know that expected goals are the likelihood that a goal will be scored on a shot. Expected goals is now a term that more and more Scottish football fans are familiar with, understand, and can discuss coherently. Sure, there is the occasional “Yer Da” still yelling about “Goals and Points being the only stat that matters!”, but compared to three years ago, football analytics literacy has grown considerably in Scotland.

However, now that many have the basics down, we need to have a talk about expected goals. On Twitter last week, I noticed there was discussion about the usage of xG and in particular summing xG totals for individual matches and saying things like “(this team) should have scored 2 goals because they had an xG of 2.” Let me first throw myself at the mercy of the metaphorical court, I have created a few different visualizations where a summed xG total for an individual match was present. It is still on the xG maps I publish each week for the SPFL.

I chose to sum xG on the graphics I have posted to try and ease Scottish football fans into xG. With that being said, there are some issues with summing xG for individual matches. Danny Page covers the issues in an article he wrote pretty comprehensively. Danny points out that if you sum the xG, you will miss on on the variance that can occur in a single match. In his article, he says:

Arsenal won 0–3 with a xG scoreline of 0.39–1.49. In these cases, some may say “The right team won” because the xG and real life scorelines match. However, these values are only adding expected goals. But something is missing. Only adding independent probabilities misses half of the story: variance.

A good situation to think of here is a shot with an xG of 0.05. That shot may go in, it has gone in before, but it is not likely. The instances where it does go in is the variance Danny is talking about, but generally it is not a shot that is going to lead to goals often. But let’s say that a team has ten of those 0.05 xG shots, compared to a team that has one 0.50 xG shot. The second team’s shot is much more likely to go in than any of the first team’s shots, but summing the xG in this situation they would both have an xG total of 0.50.

Ross County Motherwell Prob 11_4_17
The xG graphic that will be out each week for match, borrowing heavily from Danny Page and his xG simulator.

Sometimes those lower xG shots will lead to a win, thus the idea of variance. Typically  summing xG over the course of a season variance usually will find the mean. However, anything can happen in one game. Therefore, Danny puts forth that rather than summing xG totals in a single match and making conclusions off that, it would be better to use win percentages based on the xG of each team’s shots and the likelihood of the goal difference for that match based on the xG output, so that is what we are going to do.

 

To do this, we will take the xG of each shot for a team in a match and run them in a Monte Carlo simulation 1000 times. This is similar to what I do to come up with the numbers for B.U.R.L.E.Y. for the season. With these simulations, we can come up with 1,000 results of matches with the xG results of a particular match and produce how many times each team would typically win and draw, what would be the most common scoreline, and the typical points per game from that xG performance. In addition to seeing the sum of the xG for a match, we will see the team that was most likely to win and what the score would typically be from a match with that xG output.

St. Johnstone Celtic Prob 11_4_17.png
My xG graphic for St. Johnstone v. Celtic on November 4th.

Using Danny’s xG simulator and taking all the graphics he came up with as a template, I will now be producing these graphics for every SPFL match. Henceforth, these graphics will accompany the xG maps we have been producing each week and will hopefully give some further insight into expected goals. As this now the “advanced class”, please feel free to let me know if you have questions or comments about this!

This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.