Stats in Context: No Improvement Seen from Partick Thistle

In October, I wrote an article for The TwoPointOne discussing Partick Thistle’s performance to that point of the season. It is behind a paywall, but the main gist of the article was that Thistle found themselves towards the bottom of the table as they did the year before but unlike in the previous campaign, this lower half of the table performance matched what we would expect based on underlying metrics. It seems this article made it to Firhill, as George Francis, Communications and Media Manager at Partick Thistle, tweeted this:

Now, I certainly do not think George’s opinion represents the entirety of Partick Thistle, especially on the footballing side. However, I was needless to say surprised by this reaction. I thought I spelled out why I thought the scenario from last year was different, mainly their xG difference last season was among the top 6 clubs in the SPFL (and that is where they ended up in the table) and this season their xG numbers were much worse.

So I hope most would forgive me when I did a little twitter touchdown dancing after Thistle’s 4-0 loss to Ross County to send them bottom of the table with one game remaining before the split. However, I do not want to rub it poor George or Partick Thistle’s face too much. Rather, this seems like a good opportunity to discuss what has continued (since you know, I pointed this all out in October as well) to trouble the Jags and how these numbers can help us and clubs determine when they might be just going through some bad luck and not to panic or when things might need to change and sticking our heads in the proverbial sand like George here might not be the best course of action.

As mentioned, Partick Thistle moved to the bottom of the table after their loss to Ross County midweek. The Jags currently have 25 points after 32 games, the same as their opponent Tuesday Ross County but with a -30 goal difference compared to County’s -19 difference. To bust out the football cliche handbook, we could even say that goal difference is almost like another point advantage for County. Compare this to last season where Thistle finished sixth when the SPFL split in half.

SPFL xG Points.png
xG per Game and Points per Game through April 1.

If we look at the underlying metrics for Partick Thistle this season, we cannot be surprised by where they are in the table. Thistle was averaging 0.91 xG per game and 1.49 xG Against per game after Sunday April 1st , which are worst and third-worst in the SPFL respectively. Compare these numbers to their 6th place finish last season, where they averaged 1.07 xG per game and 1.33 xG against per game, which were 6th and 7th overall last year (though worth noting that before the post-split matches Thistle was averaging 1.01 xG against per match). Looking at these numbers, we can start to see why the Jags have fallen down the table this season.

It is not just in expected goals we see Partick Thistle regress this season compared to last. TSR, or Total Shots Ratio, is the number of a shots a team has divided by shots for and against for that team. It shows the percentage of shots a team gets in their matches. In the 2016-17 campaign, Thistle had a TSR of 0.44 (or they had 44% of the shots in the matches they played). This season, they have fallen to a TSR of 0.37 which is the worst in the league. This means that the Jags have the biggest difference in shots they are conceding and shots they are taking in SPFL Premiership play.

So what has caused this sharp decline in Partick Thistle’s play. Most would assume Thistle 1.jpgthat Liam Lindsay being sold to Barnsley would be one of the main culprits and there certainly is some truth to that. As we discussed earlier, the Jags back line has conceded shots and xG this season at a higher rate than the did last season. Though Lindsay has left Firhill, Thistle still have defenders such as Niall Keown and Danny Devine who were part of the squad last season that finished sixth. We can surmise with these players still in the squad but the club’s defensive metrics deteriorating that Lindsay was an integral part of the back line last season.

While the defense has clearly been an issue for Partick Thistle this season, a more long term issue for the club has been their attack. Last season, Kris Doolan netted 14 non-penalty goals in the league, but no other player had more than 6 non-penalty goals in SPFL play. Doolan averaged a very good 0.33 xG per 90 minutes last season. Thistle also had Ade Azeez averaging 0.35 xG per 90, but no player underachieved their xG numbers more when it came to goals than Azeez. Besides Doolan and Azeez, no other Thistle player averaged above 0.15 xG per 90. Given that the “average” player at this level has an xG per 90 of 0.22, you can see the attacking options were limited last season for the Jags.

The attacking side of the ball may have been a struggle for Partick Thistle last season, but things have gotten worse this year. As previously mentioned, the Jags are averaging 0.91 xG per match, down from 1.07 xG per match in 2016-17. Through Sunday, no Partick Thistle player has over 5 non-penalty goals, with Connor Sammon, Chris Erskine, Kris Doolan, and Blair Spittal all with 4 goals. Of the Thistle squad who have played 930 minutes this year, only Doolan, Connor Sammon and Chris Erskine are averaging an xG per 90 above 0.22 (again, the “average” number for players in similar leagues as the SPFL) at 0.24, 0.27 and 0.25 respectively. Thistle have had a need at striker for a few years now, but have failed to address it properly.

Thistle Stats.png
Stats for every Thistle player appearing in at least 930 minutes.

The one bright spot on the Partick Thistle attack has been Blair Spittal. The Scottish midfielder has 4 non-penalty league goals, 4 assists, and is averaging an xA per 90 minutes of 0.23, which is the 15th best in the SPFL. He has an xG total of 3.17 and xA total of 4.63, so he is scoring and assisting more or less at what you would expect based on his xG and xA numbers. The issue is that Spittal has had to carry much of the attack himself. The 22 year old is having perhaps his best professional season so far, but without any help from his Partick Thistle teammates, the Jags will continue to be in trouble.

It is safe to say that heading into the split, Partick Thistle was looking to avoid being

“What’s Expected Goals?”-Kingsley, probably

at the foot of the table. While Thistle’s underlying metrics have been awful most of the season and suggest they are right where they should be, most of the other clubs in the relegation fight do not have more impressive stats. Hamilton and Dundee have similarly as bad xG numbers. Ross County have had better underlying metrics than these three, but has underachieved all season. Thistle are definitely still not dead and have fixtures against all of these clubs to try and get off the bottom.

However a club employee, albeit head of PR and not on the football side, dismissing these type of statistics as “not being in context” and then finding themselves bottom of the league in April is very fitting. The warning signs were there in the numbers since October and have not improved since. Clubs can use these numbers to better judge their performance during a season, avoiding the type of blushes ole’ George has had.

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.

Celtic Have Found a Midfield Maestro in Olivier Ntcham

In their last match up against city rivals Rangers, Celtic saw two Frenchmen end up on the scoresheet in their pivotal 3-2 victory. Yet it was neither Moussa Dembele nor Odsonne Edouard that ended up with Man of the Match honors, but rather countryman Oliver Ntcham that was chosen. Ntcham put forth an assured performance in the middle of the park for the Bhoys, something that Celtic supporters have grown accustomed to from the French midfielder in his first season in green and white.

If we look at Ntcham’s goal contributions in SPFL play so far, we see that he has scored 5 league goals this season. Of those goals, 3 have come from outside the 18 yard box and he has an xG of 2.89 (0.17 per 90 minutes). While the intention of this article is to praise the play of Oliver Ntcham, a criticism you could have about him is his shot selection. 42 of his 50 shots this season have come from outside the box, or 83% of his shots in SPFL play.

Ntcham Shot Map.png
Olivier Ntcham Shot Map: Hey Olivier, why not try a shot in the box?

Scoring 3 of 50 shots is good for a conversion rate of 6%, which is higher than average (roughly 4-5% is average in the SPFL) for outside the box, but is still not a shot we would expect to go in that often. We could expect his goals coming from outside the box to start to dry up, as he is currently over-performing what we would expect. While Ntcham’s job in the Celtic line-up is not necessarily to be a goal threat, if he is going to attempt 2.9 shots per game, getting those shots in a more dangerous position will help him become an even better player.

Ntcham ling

While Oliver Ntcham’s shot selection may need work, you cannot help but be
impressed by his ability to pick a pass. Both anecdotally and statistically, the French midfielder has been impressive in his play-making this season. Though he only has 1 assist in league play so far, his underlying metrics have been quite impressive, with a total Expected Assists of 4.21 and 0.21 per 90 minutes, which is 9th in the league.

He also has a total Expected Secondary Assists (this is the same as expected assists, but for the pass before the pass before the shot) of 3.46 and 0.20 per 90 minutes, which is 2nd in the league. If we combine these passing metrics of xA and xSA, Ntcham has a total of 7.67 and per 90 of 0.44 which is fourth best in the league. All of these numbers show an impressive showing for Ntcham in his first season in Scotland.

Ntcham Pass Map
Olivier Ntcham Pass Map where he and teammates typically are when he sets them up (Open Play Only)

Looking at the pass map above, we see the median location of where Ntcham is when he makes a key pass (or the pass that leads to a shot) and average location where the player who took the shot was. It is clear that Ntcham makes his mark in the center of the pitch and from outside the box when setting up his teammates. We also see that he is most often setting up Celtic’s most dangerous goal threats such as Scott Sinclair, Odsonne Edouard, Leigh Griffiths, James Forrest, and Tom Rogic in the box, where they are more likely to score. Below is a perfect example of this, where we see Nthcam make a killer through ball from the middle of the pitch to find Griffiths in a high probability scoring location and Griffiths is able to finish.

While it is often referenced, for the most part there is not much one can gather from looking at a player’s pass completion percentage alone as a stat. This metric does not speak to the type of pass a player is attempting. If the player is just playing simple back passes, they would likely have a high completion percentage but that does not really tell us anything about the passing ability of that player. It is for these reasons most of those analytically inclined prefer metrics such as xA or Expected Passing (a metric that the data needed to calculate for Scottish football is not publicly available).

SPFL Pass % & xA xSA

However, if we combine a player’s pass completion percentage with expected assists and expected secondary assists, we can see how accurate their passing is and what type of passes they are making. Above is a graph featuring every SPFL player (minimum 900 minutes and averages at least 0.33 Key Passes per 90 minutes) total pass completion percentage and their xA+xSA per 90 minutes. That top right quadrant is where a player has completed higher than average percentage of their total passes, has a higher than average xA+xSA per 90 and where we can surmise the top passers in the league. Sure enough, we see Olivier Ntcham there among other names we would associate as among the best passers in Scotland. Ntcham not only is completing a high number of his passes, but the key passes he makes are more dangerous than most other players in the league.

Ntcham 3

In his first season in Scotland, Olivier Ntcham has been a great addition to the Celtic midfield. He has chipped in goals for the Bhoys, though if we look at his underlying numbers for goal scoring we could guess he might not be able to sustain that. We can definitely surmise that based on his passing metrics that he can continue to pull the strings for Celtic in the midfield though.

At the beginning of the season, the Celtic midfield seemed to be deep, with lots of options. However, as the season has progressed, Olivier Ntcham has started to pull away from his teammates and appears to be certain to start any big matches Celtic have. Given he is only 22 years old, if the French midfielder can continue this form and these metrics, it is hard to imagine that he will not start to gain the attention of bigger leagues and teams and Celtic may be able to cash in on another big transfer fee.

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.

Some Quick Numbers on Mikael Lustig

In the aftermath of yesterday’s 3-0 loss to Zenit St. Petersburg, the internet has had Mikael-Lustig-Sportsinternationalplenty 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.

Celtic Chances Against Map
Chances Against Celtic Map Created by Dougie Wright

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.

Lustig Frowney Face 2

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.


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.

Daniel Candeias Has Quietly Put Together a Great Season

It seems to be the standard now for Rangers to find themselves in the headlines ofCandeias side.jpg 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.

Candeias Assists xA
Candeias’ xA and Assist output has stayed consistent this season.

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.

Candeias Pass Map

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.

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 in that game. 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.

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.

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.