In the aftermath of yesterday’s 3-0 loss to Zenit St. Petersburg, the internet has had plenty of thoughts about who the blame for Celtic’s form this season. These thoughts range from lukewarm to spicy hot, such as seeing on one Celtic message board say that “Brendan Rodgers is a fraud”. Regardless, Celtic supporters have had numerous ideas on who to blame for the result in Russia last night.
One of those facing the brunt of the blame for both last night and Celtic’s form dipping this year compared to last is Mikael Lustig. The 31 year old Swedish fullback is in his seventh year at Celtic and has become a cult hero for much of the Celtic fan base. However, it seems the Swede has seem his form dip this year. Before this season, the right back was one of the more consistent players for the Bhoys, but from observation it seems Lustig has not played as well as he has most of his Celtic career.
The above map was created by Dougie Wright and shows where the chances created against Celtic have come from in league play. The darker the green is on the heat map, the more chances have come from that area. It becomes pretty clear that teams in the SPFL see Lustig as a weakness in the Celtic back-line and are trying to expose the area he patrols.
And if we look at the numbers for both the Celtic defense and the rest of the league, we see that to be the case. In the above table, we have the number of Key Passes (or the pass that set up a shot) teams concede on the right wing, the percentage of total key passes a team concedes that comes from the right wing, that percentage of key passes from the right wing compared to the league average, the expected goals from key passes conceded on the right wing, the percentage of a team’s xG conceded that came from key passes on the right wing, and how that percentage compares to league average.
As we see, the numbers are not kind to Mikael Lustig this season. Though Celtic have conceded about the average number of key passes from the right wing, they have conceded easily the highest percentage of the key passes coming from the right wing. 28.57% of the shots Celtic have allowed originated from a pass on the wing Lustig usually patrols, which is 12.21% higher than league average.
Celtic have also conceded by far the highest xG in the SPFL from key passes from the right wing at 5.07, which is 37.62% of their total. This is 22.03% higher than the average in the SPFL. The next highest percentage of xG conceded from Key Passes on the right is 17% less than what Celtic have conceded. Teams have clearly pinpointed Mikael Lustig and the right side of Celtic’s back line as the area to attack and these numbers show that they have clearly been able to do that.
Celtic’s recruitment strategy has been one of the more common places most have put blame for the result in St. Petersburg. Some have asked why a replacement for Lustig was not found either in the summer or January transfer market. Brendan Rodgers has been reluctant to play Christian Gamboa this season, meaning Mikael Lustig has played a lot of football this season. Both by observation and numbers have suggested that Lustig has struggled this season. Perhaps the high number of minutes he has played both for Celtic and Sweden has caused this dip of form, but if this continues Celtic will have no choice but to look for a replacement for the long serving Mikael Lustig.
It seems to be the standard now for Rangers to find themselves in the headlines of Scottish football, both for matters on and off the pitch, on a seemingly weekly basis. From memory, we have had Pedro Caixinha sacking, Carlos Pena being sent back to Mexico and his choice of handkerchief, and Josh Windass’ various hand gestures to fans as examples of off field shenanigans surrounding Rangers this season. However, among the headline grabbing antics at Ibrox, Daniel Candeias has quietly put together one of the better campaigns in the SPFL this season.
I discussed the idea of expected assists last season, but thought this would be a good time to have a refresher on this metric. Expected assists applies the idea of expected goals to those creating the chances. Using the same model we use for xG, xA applies that same number to the player who created the chance via pass. So if Daniel Candeias passes to Alfredo Morelos and Morelos takes a shot worth 0.2 xG off of it, Candeias gets an xA of 0.2. This is an attempt to quantify the type of chances a player creates, rather than something like passes completed percentage.
If we look at the expected assist leaders for the SPFL Premiership this season, we see Candeias is by far and away the league leader. Through February 11th, Daniel Candeias has a total xA of 9.06. The next highest player in the SPFL is at 6.08, quite a ways away. He has an xA per 90 minutes of 0.41, the highest of any player who has played at least 700 minutes this season. He has the highest expected assist numbers from free-kicks, open play, and is 4th in xA in set-pieces. Last season, Niall McGinn had the highest xA in the league and he had an xA per 90 of 0.35, so Candeias is averaging a higher expected assists for every 90 minutes than league leader McGinn did last year. All of this is to say Candeias has been one of the best creators on attack in the SPFL Premiership this season.
Looking at Candeias’ pass map from open play this season above, it is no surprise to see most of his contributions have come from that right wing. From that wing, Candeias has found James Tavernier for 10 key passes, Alfredo Morelos 9 key passes, and Josh Windass for 9 key passes. Most would agree those three are Rangers most dangerous attacking threats, so the Portuguese winger finding them so often has certainly helped lead to his success this year. Furthermore, looking at where the average location for those players were when Candieas set them up for a shot, we see all of three of them located in the “Danger Zone”. This is the area in the 18 yard box in between the 6 yard box and these shots have been found to be the most likely to be scored. When Daniel Candieas is setting up the likes of Morelos and Windass, he is finding them in the most dangerous locations on the pitch where they can score goals.
We see this perfectly in the clip above. Against Aberdeen at Pittodrie on December 3, Daniel Candeias sets up the winning goal. He times his run well on the right and puts a first touch low cross perfectly onto the foot of Josh Windass, who is square in the “danger zone” of the box and able to finish, leading to a man hug for Candeias from Graeme Murty. Run on the right, cross into a dangerous position where his teammate is waiting and can easily finish a high xG chance for a goal.
Despite the score finishing 0-0, Candeias had a very good match against Celtic in December. We see another example of what he has done so well this season above. He again is able to put a first touch cross into a dangerous position. His cross finds an open James Tavernier in the heart of the danger zone, where Tavernier’s shot is only kept out by a good save by Craig Gordon. Another cross on the right to a teammate in the danger zone, who forces a good save from the keeper from a high xG chance.
This season, most of the more ardent Twitter debates in Scottish football have been discussing if certain Rangers players are actually good. Never-ending feuds about whether the likes of Josh Windass and Carlos Pena are good players or not are found at various corners of the great time waster known as Twitter. Daniel Candeias thankfully does not draw such hard line opinions. Most seem to know he is valuable to Rangers success this season. However, it is a bit surprising his praises have not been sung at such a level as they have with someone like Alfredo Morelos by Rangers supporters. Both have been key cogs to Rangers attack this season and Rangers will need them to continue their form if they are looking to finish second.
One avenue to try and create understanding about analytics in football is to use them to praise players. Letting a player know he has good stats, what those stats mean on a basic level, and what he is doing to get those impressive metrics can help foster acceptance and further understanding from players. Which brings us back to our pal Kris.
If I told Kris Boyd, “Hey your expected goal numbers of 7.90 are great,” he would most likely look at me as if I had four heads, with two of the heads telling him to switch to a vegetarian diet. However, he might be more receptive to the idea if I said something along the lines of “we have this stat that says you have done a great job at creating shots that are more likely to be scored. If you continue to be able to get shots centrally in the box, you will likely keep scoring goals,” he may be more receptive to the idea. A player may be more interested in analytics if it is includes praise and includes an easy to understand idea to lead to continued success.
This hypothetical discussion with Kris Boyd does indeed contain some of the reasons why he has seen a resurgence on the pitch this season. Boyd has 9 non-penalty goals and 0.56 non-penalty goals per 90 minutes so far this season, only Alfredo Morelos has more in the SPFL Premiership. He also has had good underlying statistics this season, with an xG of 7.90 which is 4th in the league and an xG per 90 of 0.54. These xG stats show his goal scoring has been sustainable for Kilmarnock this season.
If we compare these stats to the same numbers from last season, we see a clear improvement. Last season, Kris Boyd scored 7 non-penalty goals and 0.32 non-penalty goals per 90 minutes. Like this year, Boyd’s goals were about what you would expect based on his expected goals numbers, with an xG total of 7.38 and a per 90 average of 0.30. We see the striker/pundit has already surpassed both his goals and expected goals total from last season and we are only into February. While you may or may not enjoy his TV work this season, Boyd’s goals have been a big part of Kilmarnock’s success this season.
Not only has the Killie striker been knocking in the goals this season, but he has been a bigger part of the Ayrshire side’s attack overall. Looking at his expected assist numbers from last year and this year, we see last season Boyd had 3 assists, an xA of 1.67 and 0.08 xA per 90 minutes. This year while he only has 2 assists, Boyd already has an xA total of 2.58 and a per 90 of 0.16. His contributions to the Kilmarnock attack has improved, with improved shooting and creation statistics this year.
Given that Kris Boyd is 34 years old, this improvement from last year is a bit surprising. Strikers typically regress at that age, something many may have assumed was happening last season with Boyd. So the question therefore becomes what has happened between last year and this year to see this improvement from the Killie striker.
During this campaign, Kris Boyd has been able to get far better shots than he did last season. He is averaging 0.16 xG per shot this year, while he only averaged 0.11 xG per
shot in the 2016-2017 campaign. To simplify this, on average every shot Boyd takes this year has had a 5% higher chance of going in based on where and how he has been shooting. Not only is he taking higher quality shots this season, but he also taking more of them, averaging 3.4 shots per 90 minutes this season and 2.59 per 90 last season. Taking more and better quality shots is clearly one of the reasons for the rise in Boyd’s form this season.
Thirty-four year olds do not usually see those types of jumps in those numbers from one season to the next, so why has Boyd? Well, he has some help shouldering the load at Kilmarnock this season. Last season, Boyd was the only Killie player who played at least a third of the available minutes in the league last season (1140) with an xG per 90 of at least 0.3. Only Souleymane Coulibaly had an xG per 90 of over 0.2 at Kilmarnock last year, and he left midseason. No player who appeared in at least 1140 minutes averaged at least 0.1 xA per 90 or more for Killie last season. Boyd was the focus of the Killie attack last season.
The current campaign must feel like a weight has been taken off of Boyd’s shoulders. Though both playing less minutes than Boyd, Eamonn Brophy and Lee Erwin are both averaging over 0.2 xG per 90, at 0.68 and 0.23 respectively. Both are options off the bench for Kilmarnock that are capable of scoring. Along with other scoring options besides Boyd, the Killie attack also has considerably more options for players that can set up Kris Boyd and his fellow strikers.
As previously mentioned, no Killie players averaged over 0.1 xA per 90 minutes last season. Boyd has already bested that himself, averaging 0.16 xA per 90 minutes, but he is not alone. Along with Boyd, Gary Dicker, Brophy, Jordan Jones, Adam Frizzell, Stephen O’Donnell, Erwin, and Rory McKenzie have all appeared in at least a third of Killie’s available minutes and have averaged at least 0.1 or higher xA per 90 this season (0.20, 0.19, 0.17, 0.16 , 0.14, 0.13, and 0.12 respectively). Boyd is clearly flourishing with more creative support around him.
While he may not be interested in knowing the math behind it, there is no doubt Kris Boyd has been one of the better strikers in the SPFL according to the stats. Analytics skeptical players like we can presume Boyd is may not be interested in regression models and scatter plots, but they are surely interested in becoming better players and they are definitely interested in receiving praise. Praise and recognition for a player can lead to more playing time, improved contracts, and a move to a bigger club. Framing the discussion around football analytics to a skeptical player about how it can improve their career may be a bridge to understanding for them.
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 midfielder 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.
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, from 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.
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.
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.
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.
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.
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.”
Congratulations Scotland, you have passed Intro to Expected Goals and are now moving 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.
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.
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!
The past few years have been a bit of a roller coaster for Motherwell Football Club. Over the last five years, Motherwell have finished ninth, fifth, eleventh, second, and second. While the years of European qualifiers are not that far off, the results at Fir Park have not been as successful lately, including a relegation fright in 2015 when they finished in the relegation playoff spot and had to beat Rangers to keep their Premiership status.
However, this year has started off much differently for Motherwell. While a second place finish similar to the years Stuart McCall led the club might be a bit too much to ask, the Steelmen sit in fifth place in the SPFL Premiership as of writing and have a League Cup final to look forward to. A top six finish would seem to be the expectation now this season for Motherwell. While a good spot in the table is always nice, we know that sometimes the table lies to us and we need to look deeper into the corresponding numbers behind a team’s performance.
There is good news when we look at the underlying numbers for Motherwell thus far, we see the stats match their good start. Motherwell have an xG of 13.45 and xG against of 9.30 for a xG difference of 4.15, which is 5th best in the league through 11 matches. These underlying numbers suggest that if the Steelmen can continue that type of performance, they can not only hope for a top six position in the table, but also start to possibly dream about a European adventure again.
It has taken a few years for it to happen, but Louis Moult has finally become a household name among football fans in Scotland. For TheTwoPointOne towards the beginning of this season, I wrote about Moult’s great season last year, but Motherwell needing to find some help on the attack after losing partner Scott McDonald this offseason. Last season, Moult helped carry Motherewell, putting up 15 goals and an xG of 10.74 or 0.35 per 90. This year he is back to putting up good numbers again this season, with 5 goals (3 non-penalty goals) and a non-penalty xG of 3.63, which is 5th in the league.
Moult seems to be in good form again this season, but he is getting some help from his teammates and that seems to be making all the difference for Motherwell. Before the season started, there were questions who would be taking McDonald’s place as the other Motherwell striker, but Ryan Bowman has stepped up to that role in the first part of the season.
Bowman has matched Moult’s 3 non-penalty goals, with a xG of 2.24 and 0.26 per 90 thus far. While Moult gets lots of shots, ranking 2nd in the league in shots overall and 3rd in shots per 90, Bowman has been able to get good quality shots despite not having the same quantity of shots as Moult, averaging 0.19 xG per shot, which is 7th best in the SPFL, and 66.67% of his shots occur in the danger zone. Will Bowman be able to continue to keep scoring off of such good quality shots as defenses in the league realize they need to account for him? Motherwell’s success may hinge largely on it.
Both Moult and Bowman have surely enjoyed the play of young Chris Cadden on the wing for Motherwell. Cadden just recently received a well deserved call up to the Scotland U21 squad (and I contest perhaps should have been called up to the main squad) and has been impressive so far this season. He has 21 key passes so far (2.1 per 90) and a xA of 3.06 (0.2 per 90), which are both 3rd in the league this season. Compare this to the Motherwell squad last season, where no one at Fir Park finished among the top 20 in the SPFL in xA or key passes.
Cadden has only 1 assist this season, which might hint his teammates have let him down a bit, but his passing creativity is clear to see in the numbers and on the pitch. Not only are his key pass and xA numbers impressive, Cadden also has an xSA (expected secondary assist) of 1.11, which is 19th in the league. Cadden has been vital to Motherwell’s potent attack this season and the Steelmen will be relying on him to continue this the remainder of the season.
While the likes of Ryan Bowman and Chris Cadden have helped Louis Moult and Motherwell put out a strong attack on the Fir Park pitch, last season the club actually had a decent attack as well. In 2016, the ‘Well had the 5th highest xG at 56.09. What was not decent for them was their defense, ranking dead last in the SPFL in xG conceded at 74.34.
This year has been a much different story for the Motherwell defense though. Through 11 matches, the club has the second lowest xG against in the SPFL at 9.30. Only Celtic has allowed a lower xG against thus far, as in the team that has not lost in 62 domestic matches, so pretty impressive company. If we look at the number of Key Entries allowed, or any ball that is played beyond the 18 yard line by the opposition while defending, Motherwell has allowed 222 so far, with only Celtic, Hibs, Aberdeen, and Rangers allowing less. Comparing the key entries against to xG against in the SPFL this season, we see a decent relationship, so this number will be interesting to keep track of as the season unfolds.
With such poor numbers last season, Motherwell clearly had to make a change in the back. Enter Cedric Kipre, Charles Dunne, and Peter Hartley. Stephen Robinson has deployed these three either in a back three or part of a back five in recent matches and the results speak for themselves. Both Kipre and Dunne were brought to the club on free transfers, while Hartley was brought on loan from Blackpool, though his contract expires in May of 2018. Dunne and Kipre are younger players at 24 and 20 respectively, while Hartley has more experience at age 29. These additions have turned Motherwell from the worst defense last season to one of the best this season. Furthermore, they show that SPFL teams can help turn around part of their team with some shrewd signings.
Last season, Motherwell heavily relied on Louis Moult. Their defense was a shambles and besides Scott McDonald, the attacking burden fell mostly on Moult. But so far this year, it has been much more of a team effort at Fir Park. The club no longer has to rely on Moult to win. If they can continue to get these same types of contributions from Bowman, Cadden, Kipre, Dunne, and Hartley, a top six finish should be the minimum expectation for Motherwell.
Going into match day 2, Celtic could not have a more different Champions League opponent in RSC Anderlecht that match day 1 foe PSG. Like Celtic, Anderlecht were seen as the also rans in the group also featuring mega-bucks squads Bayern Munich and Paris Saint Germain. It was all but assumed Celtic and Anderlecht would be fighting for third at the end of the group, and Anderlecht also was on the wrong end of a big loss (though not as big as of a loss as Celtic) to Bayern Munich in their first Champions League match of the campaign.
Unlike Celtic, things have not gone so well for Anderlecht domestically back in Belgium. Through eight matches, the reigning Jupiler Pro League champs sit in seventh place, 9 points behind Club Brugge. While this position may spell curtains for teams in other leagues, the Belgian set up allows for some hope. The top 6 teams in the league advance to a playoff. In the playoff, each team has their point total halved and then they play each of the top six teams twice more. The club with the most points at the end of that is the Champion.
While the unique Belgian league set up allows for a team to have hope after a slow start, it was not enough for the powers that be at Anderlecht and after seven matches manager Rene Weiler was sacked. Weiler led the club to the title in his first season last year, but only picking up 2 wins in those first seven matches was not enough for those at the club. While the club struggled to get results under Weiler this season, what do the underlying statistics say about Anderlecht’s performance thus far? Luckily, the fine folks at Strata can help us find out (as well as teach me that there is a club in the Jupiler Pro League that has “excel” in it’s name, a stat nerd’s dream team!)
Looking at the numbers for the Juplier Pro League, we see stats telling a different story than points in the table are telling us for Anderlecht. In fact, Anderlecht’s underlying stats have been fairly good so far this season. Anderlecht has the best xG difference, the 2nd best xG for, and the best xG against through seven matches in the league. The Purple and White have conceded the lowest number of shots and have the highest xG ratio in the league (the ratio of xG for/xG+xG against). The only numbers that are not so impressive for the club is their goal total at 8, their goal difference at -1, and their points at 9.
These numbers suggest that Anderlecht could be due for some positive regression to the mean, in which their performances start to result in more goals and points on the table. They also suggest maybe the club should have been more patient with Weiler, as the performances were OK despite Anderlecht being on the receiving end of some bad luck. With Nicolas Frutos, David Sesa and Thomas Binggeli are taking over managing the club on an interim basis, will the club see that positive regression that the stats say their performances deserve or will the sacking throw the club into disarray and see performances worsen? Hopefully for Celtic, it will be the latter.
Taking a look at where Anderlecht’s goals have come from domestically, a pretty clear pattern emerges. Five of Anderlecht’s six league goals in their first seven matches came from the area we like to call the danger zone, where you are more likely to score. On the other end of the ball, seven of nine of their goals conceded came from the danger zone they were defending. Furthermore, five of nine came from crosses, but only one from a header. To me, this screams out a weakness that Kieran Tierney can exploit. Tierney is wonderful at bombing down the wings and making a killer cut back low cross. This sets up his teammates for this high probability danger zone shots. Seeing as this seems to be something Anderlecht is susceptible to and is a strength of Celtic’s, one would think this is something Celtic will need to exploit to be successful Wednesday.
If we look at some individual players Celtic will need to look out for, a few names pop up on the Anderlecht squad list. Henry Onyekuru and Lukasz Teodorczyk are tops at the club in goals and expected goals, and seventh and eighth in xG in the league respectively. Everton loanee Onyekuru, who says he turned down a move to Celtic this summer, has 3 goals, an xG of 2.75, 0.61 xG per 90, and 3.3 xGAS, while Teodorczyk, the £4m signing from Dynamo Kyiv, has an xG of 2.59, 0.44 xG per 90, and a 4.26 xGAS. These two have been Anderlecht’s most high potent attackers domestically, though neither started their last match against Waasland-Beveren, though Onyekuru came on as a sub at half.
Looking at some xA numbers, Teodorczyk has the highest expected assist numbers at the club and is twelfth in the league at 1.52. The man who is pulling the strings for the Anderlecht attack has to be Sofiane Hanni. Hanni has the highest expected secondary assist total at the club and is second highest xSA total in the league at 1.87. Hanni is usually deployed as an attacking midfielder centrally and is the linchpin to the Anderlecht attack that has yet to find the goals, but has underlying numbers that suggest they are on the verge of being unleashed.
While it is hard to speak about the Belgian press, even the most ardent Celtic supporter probably understands it is a race for 3rd place after the 5-0 loss to Paris St. Germain in match day 1. To finish third and see European football past Christmas, Celtic probably need at a minimum of four points from their two matches with Anderlecht. The Purple and White may have struggled domestically thus far, but their underlying numbers suggest their is a good squad in there. Will Anderlecht rebound after Rene Weiler’s sacking? It is hard to guess, but Celtic would be wise not to take them for granted.
I can assure you there will no tired/borderline racist cliches in this article about Alfredo Morelos. Last season, Rangers had the second highest expected goal total in the SPFL, yet finished third in the table. Whether that is due to bad luck or poor finishing can be debated, but as a result Pedro Caixinha and Rangers decided that they needed to upgrade at striker. Out went Martyn Waghorn and Joe Garner and in came Alfredo Morelos from HJK Helsinki. Last season, Morelos scored 20 goals in all competitions for the Finnish club, but could he continue to score goals in the step up to the SPFL?
Through six games, Morelos has certainly answered that question with a resounding “yes”. Going into the match-up with Celtic, the Colombian is currently top the goal scoring table in the SPFL Premiership with 6 goals. In addition to having the most goals in the league, Morelos has the highest xG in our model at 3.61, which is 0.77 per 90 minutes and 0.23 per attempt.
Looking at these numbers and his shot map above, it is easy to see why Morelos has had early success with Rangers. the Colombian striker has been able to get into great positions and get off shots with a higher than average scoring probability. 63% of Morelos’ shots this season have come from the Danger Zone, or the area in the box between the ends of the 6-yard box. All but one of his shots have been inside the box thus far. Morelos clearly thrives inside the box, getting shots where they can do the most damage.
If we compare Morelos’ per 90 numbers for xG to Moussa Dembele’s from last season (0.69 xG per 90), they are similar. Of course, it is way too early to declare Morelos on the same level as Dembele, but if the Colombian striker can continue his output at this pace it would not be unreasonable to compare the two. However, even if Morelos can reach the same rarefied air that Dembele did last season, Rangers still may need someone else to help ease the burden on “El Bufalo”.
Besides Morelos, Josh Windass and Kenny Miller are both among the top 20 xG leaders in the SPFL that are on Rangers. Yet, between Miller and Windass, they have 1 league goal between them. Morelos may have the talent to carry Rangers for a period of time, but like all players, he could find himself out of favor with the finishing fairy and not find the net for a few matches. If Celtic are without Moussa Dembele, as they have been up until recently, they have the likes of Scott Sinclair and Leigh Griffiths that can help knock in goals. Can Morelos’ Rangers teammates provide the same support? It has yet to be seen.
While six games is a small sample in which we do not want to jump to conclusions, it certainly seems Rangers have upgraded significantly in the striker position from last year with Morelos. With such fine play, the Colombian striker is already subject to transfer rumors. However, if Rangers can hold onto him all season, they can expect to see greatly improved fortunes in front of the goal from last season.
Expected goals are having a moment right now. The stat most associated with advanced stats in football has recently gotten think-pieces from outlets like The Guardian, The Telegraph, Goal.com, and Fan-Sided . Football stats writer Mike Goodman said today on twitter, “I’m so happy that xG is getting increased exposure that I’m gonna grit my teeth and grin through all the re-litigation of its underpinnings.” More people now at least are aware of xG and have an idea what the stat measures than ever before. With each new “mainstream media” (shudders) piece on expected goals, we start to have the same arguments and discussions about the metric that were had years ago.
While the fight over xG’s importance may be starting all over again in places, if you dive deeper into so called “analytics twitter” you will find great pieces discussing efforts to improve the metric. Marek and Nils articles I linked there are the type of work that made me interesting in stats in football in the first place. Furthermore, those pieces are what drove me to want to track these stats for Scottish football when I could not find any publicly available.
With that being said, Christian Wulff and I have been working on improving expected goals in Scotland. The wonderful people at Stratagem have given us more data than we
could have imagined to help accomplish this. Before Stratagem, I was reliant on pulling shot “location” information from the BBC live-tracker of SPFL matches, simply because there was no other public data available. The “Beeb” xG model served it purpose well, giving us a surprisingly decent look expected goals in Scotland when it did not exist before. However, we can now do better.
Seeing honest-to-goodness x an y coordinates for shots (AND passing locations?!) in the data Stratagem sent Christian and I was a coming to god moment. No longer would be be reliant on terms of “center of the box” from the BBC. In addition to using actual x and y coordinates and shot types, we also now had such information as how many defenders were in between the shooter and the goal and how much defensive pressure the shooter was under when shooting.
With this additional info, Christian and I set out to improve our xG model for the SPFL. Common criticisms of xG is that is does not take defenders and defensive pressure into account, so this new Stratagem data would allow us to address this. Good in theory, right? Well, believe it or not, you run in to a sample size issue when you become more granular and only have a season’s worth of data. Trying to get enough shots to come up with a decent xG model for Scotland where 2 defenders were in between the shooter at 37 x, 44 y on the pitch proved to be a challenge. Luckily, the SPFL is not the only league Stratagem has data for.
While it seems to be a recent trend to try and asses how your Gran would do in the SPFL, most would agree that the level of play in Scotland is below leagues such as the EPL, Bundesliga, and La Liga. No shame in that, it is just reality. However, there are plenty of leagues in Europe and around the world that most would agree are at a similar level to Scotland. Leagues such as Eliteserien in Norway, the Swiss Super League, and others. In total, we had 11 leagues worth of data (Turkish, Swiss, Swedish, Greek, Bundesliga 2, Dutch, Austria, Australia, the English Championship, Norwegian, and Scottish league data to be specific) that gave us over 400,000 shots. With data from what I have dubbed the “League of Average Leagues”, we now can use these defensive metrics from Strata and create small zones on the pitch where shots take place to calculate xG values (though thanks to Nils and Marek’s articles I mentioned above, we are now thinking about how to implement their ideas for our model!).
With these figures calculated based on location and defensive pressure, we can develop a heat map similar to above of the probability of scoring a goal. Going from light green, as the least likely to score, to dark red, as the most likely to score, we can see where a team should be trying to take shots from in order to score. The “danger zone” concept is shown well here, with red filling the 8 yard box and the darkest red in between the frame of the goal. Compare that to the green in the sides of the pitch or outside the box. Clearly you are more likely to score in the red areas than the green (I’m looking at you, Fassai El Bahktouri).
With this new model, Christian (on his new stats and tactics vertical from the 90 Minute Cynic, xCynic) and I are also planning on doing some new things and changing some graphs and maps we have done previously. We have made some improvements to our xG game maps, xG and xA player maps, and some new team graphs that we hope will help further understanding both advanced stats in football and Scottish football as a whole.