Austria: how do they try to score goals?

Seventh, fourth, seventh, and now tenth. After finishing second (and losing more than one third of their games on the way) in 2016/17, Austria Vienna are in what you may describe as a permanent crisis. They are definitely performing below expectations, given that they are the last club to win the league not named Red Bull Salzburg and also the record champion since the competition was installed in its current format in the 1970s.

The club, formerly known for technical and offensive football, is struggling especially at the high end of the pitch. During the current season, they have scored only one goal per game, down from 1.5 during last year's regular season and on par with the worst team of the league. Their last win (and only second in total) dates back to early October. This happens in spite of reinstalling their messiah, Peter Stöger, the last one who coached them to champions honours, as head coach this summer.

The difficulty is that their performances are just that. Although they can argue that they have been a bit unlucky (only nine goals from 15 xG), there are only three teams in the league that created even less. They are playing like a below average team and deserve the position they occupy in the table.

The shot zones map underlines their weaknesses. They create less expected goals than an average team does from any area in the box and just outside of it. Their chance creation in the zone around the penalty spot is especially poor. This is not the map of a team that competes for European competitions or even more, but rather one that needs to make sure they don't finish in a lower league the following year.

The question is if there is at least anything positive about their offensive performances this year. A strength they could rely on to score more goals during the remainder of this season. By crunching the numbers concerning their expected goals and comparing them to the other teams of the league, we can detect any possible strengths.

Unfortunately, they are not leading the league in any category, and only in one they are among the top third of teams. They are below average both before (8th best team of the league) and after the break (10th). They are somehow better after crosses (7th) than after non-crosses (10th) as well as after set-pieces (6th) than from open play (9th), but nothing to be too optimistic about.

The only category in which they somehow excel is xG after long passes, in which they are the fourth best team by now. To put this into context, they also try it quite often the direct way, playing long balls both absolutely (955 times so far) as relatively (23% of their passes are long) the second-most frequently of all clubs. Plus, this kind of football might not be the one preferred by their supporters and is also not the best one suited to some of their more gifted players such as Grünwald, Fitz or Sakaria.

The most baffling fact, however, is that they are still to create a single shot from a through ball this season. Through balls are in general a very effective way to generate high quality chances, hence the team lacking this quality shows the poor season they are having. Only fellow relegation contenders Hartberg and Altach have also failed to create something from through balls this season.

The issue is as much personal as it is structural. Last season's most dangerous players are by and large also this season's, but in general most of them on a lower level. There are some promising youngsters such as Aleksandar Jukic (20) and Patrick Wimmer (19), but they still rely too much on some players beyond their peak (Grünwald, Klein last season, Suttner this year) in terms of chance creation.

Plus, one of their most exciting younger players has hardly featured this year. Dominik Fitz has played less than 200 minutes this season, missing many games due to injury and suspension. He was easily their most creative player last season, setting up 7.5 expected goals for his teammates. On the way, he created more than two expected goals from through balls last season (no other more than one), was their best assister for shots both from crosses and non-crosses, and also both from open play and after set-pieces.

He did additionally also create danger from his own shots, being their second most effective player from non-crossed shots and their third most from open play and after short passes. His tally of four goals and eight assists almost perfectly matches his underlying performances, indicating how much his team has been missing him this year.

Altach: are they declining?

When Alex Pastoor took over at Altach in March of 2019, things didn't look very bright for the team from Vorarlberg. They languished in penultimate position of the table and were in acute danger. Wacker Innsbruck, who were relegated in the end, were only one point behind them. The dutchman's take of control meant an immediate improvement of form. He took them to the second position of the lower tier of the play-offs, eight points ahead of the relegation spot. During the play-offs, the team managed to gather one more point (18) in ten games than in the 22 matches of the regular season, albeit against in general weaker opposition. In the following 2019/20 season, the team stabilized on a higher level, gaining six points more during the regular season than the year before. Then, football was stopped for some months, and after the restart the team was not the same as before. Although they did finish second again in the lower play-offs, they did so by collecting five points (i.e. half a point every game) less than the year before. They also scored almost 50% less goals, although they also improved defensively a bit. 

This year, their downward trend seems to continue. They are again in penultimate position, only one point ahead of the worst team of the league (sounds familiar?). Never in the last few years have they collected fewer points per game than this season (a mere 0.66). Their goal difference is the second worst in the league and no team has scored fewer. This leads to the question whether this trend is down to some more or less random fluctuation (as can happen in a short time of only twelve games), or are there real problems? And can we say that the fact that they score fewer goals is down to some offensive problems?

A look at the long-term trend of their xG-numbers show that they do have a worse regular season than in previous years (the current format was installed in 2018). After having performed at quite similar levels during the 2018/19 and 2019/20 seasons before the split at around -0.41 xG-difference per game, they are now down to -0.6. This difference might not seem big, but it adds up to around four goals in the course of twenty games. 

The graph shows the evolution of the total xG-difference since the start of the 2018/19 season (thick black line) and the mean difference for each sub-season (thinner blue line). Given that it is a cumulative sum, it is not very surprising to see some variability at the beginning, with the tendency stabilising after around ten games. We can see that there was an uplift after Pastoor took over, when the team reached their highest average xG-difference (0.42). 

The trend was however not sustainable, and the performances returned to the level of the 2018/19 regular season. Things did not get much better in the 2019/20 play-offs (after lockdown), when they performed around half as good as the year before. The downward trend carried on into the current season, as exposed above.

Their difficulties are still not so much down to problems in attack. In fact, they are creating more this year (1.23 xG per game) than in the two previous. The problem is that this offensive improvement is more than cancelled by some defensive struggles. They almost concede two xG per game (1.83), which may be less than their actual goal tally against but is so high that naturally more variation occurs.

Although they are clearly not the main relegation candidate this season, there are some worrying signs concerning results and performances. They need to improve defensively if they are to get back to where they have already been in past seasons.

Admira: How bad are their performances really?

Last in the real table, and also trailing in the expected goals ranking, with the worst defence (almost 25 xG conceded) and offence (only under ten xG created) of the league: the 2020/21 season of FC Admira Wacker Mödling can be described as suboptimal, at least. They are only one point behind their closest rival (Altach), but underlying performances are abysmal. Their expected goal difference of -1.25 almost doubles that of the second worst team (Hartberg) and is also way lower than their performances in recent years (between -0.31 and -0.61 since 2016/17). But how bad are they really in a historic comparison?

Going back in time (until the start of the 2016/17 season), we struggle to find comparable teams. The current Admira squad is by any means the worst team in this period. The second worst team (Wolfsberg during 2016/17) managed to survive with an xG-difference of almost -25 in 36 games. 

The comparison might be unfair, however. Given that there were only twelve games played this season, sample size issues and schedule effects might influence this seasons' data more than those of past, complete seasons. I try therefore to make a more just comparison. From the four seasons before the current one, I randomly draw 10.000 subsamples (12 games) of individual teams and compare their respective xG-difference to the numbers of this year's Admira. By sampling randomly and repeating this quite a few times (like 10.000), we are able to eliminate with high confidentiality singular effects that might influence the current season's data. The comparison is then more grounded.

The graph shows the distribution of the xG-differences of the simulation, plus a curve that indicates a normal distribution. The line shows that results are skewed, indication that some teams (usually Red Bull Salzburg) perform on an extraordinary level, causing a longer tail on the right side of the graph. However, this should us not bother us in this case.

The results of the simulation confirm that Admira's performances this season are really bad. Out of the 10.000 simulations, only 18 (way below one percent) where worse than the team so far. Interestingly, eleven of those where Hartberg last season, obviously a rather bad season xG wise. Admira themselves feature twice (both during the 2018/19 season, their worst one before the current) in this list.

Does this mean that they are doomed? Well, not necessarily. There is still a lot to play for (ten games before the league is split into two groups of six teams each, who will face each other twice). The point difference is slim (only one) and will be further reduced even if they remain in last position, given that points are halfed after the regular season. Furthermore, the results of the simulation itself give a glimmer of hope. Of the 18 worse cases, only two (FC Wacker Innsbruck 2018/19 and St. Pölten 2017/18) were from teams that ended their season in last position (St. Pölten were not relegated due to a change of the league structure). Teams can and do overperform, but there is also a lot of room for improvement for Admira after the winter break.

Do supporters in the grounds affect results? Some evidence from Austria.

Remember when we (myself included) declared the end of home-ground advantage after football restarted? Well, not so fast. At least in the Austrian Bundesliga, things are pretty much back to normal, although we are back to closed gates after some games with fans in September and October.

We can see that away teams were actually slightly more successful even before the pandemic halted football for almost three months. They obtained around 0.1 points per game more than home teams in the 22 games before lockdown. This difference skyrocketed after restart to almost 0.5, which is generally why home-ground advantage was supposed to be at least severely damaged. Things have however changed since the start of the current season. Home teams obtain around one point more every five games than their opponents. Roughly the same is true for the number of goals scored. 

 

Interestingly, the pattern is almost identical for home and away teams if we look only at goals scored in the first half: a massive drop after restart and comparable levels in the 2020-21 games to the ones with full attendance. This also means that away teams completely outperformed home teams after the break in the ten matchdays between restart and the end of the season. Whether this is due to the absence of supporters and psychological effects thereof or just some random variation is unclear. 

Underlying statistics show a similar, although less contrastive picture. Home teams suffered a significant drop of performance levels after football restarted, both in terms of shots and expected goals. Games were almost completely level between home and away teams; hence the absence of home-ground advantage can be confirmed for this period. Interestingly, also away teams suffered a drop in expected goals after restart yet is was much smaller than the one for home teams.

 

 Since the start of the current season, things are however back to comparable levels to before the pandemic. Both home and away teams actually create around 0.1 xG per game more than before football was halted, hence the difference between them is basically the same. The question why all teams create more or better chances now than at the same time last year would be an interesting question for a separate thread or blog entry. In line with what we saw when looking at actual goals scored, analyzing expected goals shows that away teams massively outperformed their opponents especially after half-time.

One decisive point why away teams performed substantially better after restart was discipline. Referees seemed to punish them much less than before Covid, both in absolute terms as well as in comparison to home teams.

This pattern was somehow reversed after the start of the 2020/21 season. Not so much in terms of penalties, where away games are still treated preferably, although the difference between home and away teams is at the moment minimal. They still get around one penalty more every eight games, this difference was around three times higher in the final games of last season. Both get more penalties now than last season; the pressure on referees to award penalties is at least in this case negatively proportional to the number of fans in the stands.

 

Likewise, the conversion rate of penalties is much higher this season than last and also way above the long-term average of around 0.8. More than nine in ten penalties are converted this season, and the difference between home and away teams is again small. As in the case of penalties awarded, home teams suffered greatly after restart and are now at higher levels than they were before the pandemic.

Other disciplinary topics show more diverse patterns. Offside calls have been on the rise ever since, something I would not directly link to the number of spectators in stadia. These are (despite some confusing VAR cases) obviously more objective, binary decisions than fouls, cards or penalties.

 

Fouls and personal punishments were in my opinion the main drivers of away teams’ improved results after lockdown. In all three categories (fouls, yellow cards, send-offs), home teams were treated worse than their opponents in the ten rounds after football restarted, unlike before Covid. This pattern was reversed but for players sent off (both straight reds and second yellows), where they are still worse off. In all cases, the difference is however smaller than it was when fans where still allowed without restrictions, which would indicate that having full grounds does influence refereeing decisions.

So, do supporters influence results? To answer this question, the current scenario offers us nearly a natural experiment. Until matchday 22 of the past season, they were allowed without restrictions. After that, games where played completely behind closed doors until the end of the season. Then in summer, there was an initial limit of up to 10.000 visitors, which was in place however only for matchday 1 due to growing infection numbers. This limit was subsequently lowered to 3.000 and then 1.500, before the league had to return to closed gates. Under each scenario we had a couple of games played, although with a limited sample size, so conclusions should be taken with a grain of salt.

 

We can see that point average for home and away teams was relatively stable before a few games before football was stopped, with away teams overperforming their counterparts during a long time early in the season. They then started to perform worse, but immediately rose again to levels unseen before after restart and maintained this level for the rest of the season. With the return of fans, their performance levels dropped again and reached a low point a few games in the 3.000 supporters period. They then started to rise again and have reached parity with home teams lately, as one would suspect if we are to suppose that the presence of fans influences results for the teams they support. Evidence is not really robust, but we can definitely show that away teams performed better with lower attendance figures or no fans at all in the stadia.

Just a results crisis?

From almost two and a half points per game down to less than one, fewer goals scored and almost double the amount of goals conceded, former leader LASK has clearly not made a good start into Post-Covid football. Given that points were halved after the regular season and they got six points deduced from their tally due to misbehaviour during lockdown, they went from being first in the table with six points ahead of Salzburg to sitting in third position, twelve points behind. One can easily conclude that the club is in crisis, despite winning their first game after the Corona break last Wednesday, against arguably the weakest team in the upper play-off group.

The question is whether this downward trend in results is due to some unlucky factors or actually caused by worse performances. They are in any case still the second-best team in the league in terms of expected goals scored and conceded even after the league restarted, a position they held also before Corona. Furthermore, they still have the realistic chance to finish second (which means the chance to qualify for Champions League football next year). On the other hand, there are some worrying trends in the underlying numbers as well.

Table 1 shows the change in expected goals for and against as well as the difference between the two for all clubs in the champions group (a.k.a. upper play-off) in the Austrian Bundesliga before and after football's lockdown. Before this break, the twelve teams of the league played each other twice in the regular season. In order to make numbers comparable, I only included those from games against direct opponents (those which made it into the upper play-off) from games before the break.

We can see that the former league leaders are the team with the second highest drop in xG created. They score almost half an expected goal per game less, which in turn can explain why their goals tally went down by almost the same amount.

Their increased defensive vulnerability is, however, not backed up by the numbers. They remain almost unchanged in comparison. The only problem there is that relatively, they became worse, given that almost all the other teams (with the exception of Wolfsberg, obviously an interesting case in itself) improved their defensive performance much more.

	Expected Goals for	Expected Goals against	Expected Goals difference
Salzburg	-0,23	-0,77	0,54
Rapid	-0,23	-0,70	0,47
LASK	-0,41	-0,01	-0,40
Wolfsberg	-0,88	0,36	-1,24
Hartberg	-0,03	-0,67	0,64
Sturm	-0,05	-0,04	-0,01

Table 1: Difference between xG-values per game between regular season and play-off. Only games against direct opponents.

This relative decline is mirrored in the change of xG-difference, where they are again the second worst team of the upper league group. We can therefore conclude that they obviously got worse in the attacking sphere of things and did not improve enough defensively to catch up with their flaws.

The next question to look at would be to gauge whether the decline is due to structural reasons or related to more individual ones. On a structural level, it is hard to identify any significant differences. One of their most important strengths during the season so far, set pieces, works almost as well as before. They create chances from dead balls as well as ever, but concede some more. This can however not explain their drop in expected goals created. Likewise, chances created from counters and crosses have not changed notably.

This is where the individual level and one of the most popular excuses in football comes in, i.e. injuries. They lost two of their key players, Marvin Potzmann and Thomas Goiginger, both within one week at the beginning of March due to ACLs. Potzmann had accounted for a combined 0.41 of xG and xA per 90 minutes played and Goiginger for 0.67, the latter being their second most productive offensive player in this regard during the regular season.

The gap left by them could not be filled by the remaining players. Out of players with at least two xG or xA during regular season, only one improved his numbers considerably after restart, central defender Gernot Trauner. Direct replacements for Goiginger such as Dominik Frieser and Samuel Tetteh saw their numbers decline. In the case of Potzmann, younger players occupying his position such as Andrés Andrade and David Schnegg are not yet up to meeting demands and produce offensive output. The only one getting near to him, René Renner, had lower numbers even before lockdown (especially assisting his teammates less than Potzmann), plus declined slightly after restart.

The crisis that LASK are going through seems to be real, and down to losing two key players which could not be replaced neither internally nor externally, given that the transfer window is shut. Not the best prospects for the remainder of the season.

How could additional substitutions affect the title race?

Like their German counterparts, the clubs of the highest Austrian league have decided to take usage of FIFA's step to allow two additional substitutions for the remainder of the season. While it has been argued that this rule change will especially benefit the bigger teams due to their stronger squads, we can use historic data (i.e. the season before lockdown) to deduce which effects the new norm can have, especially on the most important decisions (league winner, European starters and relegation). I also propose a new measurement of squad rotation, which will be affected by the rule change.

A first look at the data shows that most of the teams in the league are quite happy to use the substitutions they are allowed to make (see Graph 1); three of the twelve clubs of Austria's highest league used all of their 66 (22 league games so far). Another seven teams missed very few possibilities to make a change during their games. Only one team (Altach) is more reluctant to make changes within games, rejecting one substitution almost every other game.

Graph 1 (click to enlarge)

There is, however, no relationship between the use of substitutions and teams' position in the table. Among the three clubs at the top of the substitution usage table, there are both highly (LASK) and lowly (Wattens, St. Pölten) classified clubs.

Pure usage figures alone don't tell us a lot about how the rule changes might influence clubs' behaviour, although we can suppose that teams which are very reluctant to even use all three substitutions will also use the additional ones more cautiously.

Likewise, the patterns of substitution timing might be affected. Right now, clubs tend to make their first substitution between minutes 50 and 60 (see Graph 2), although there are some significant differences between them. You would suppose that the first, second and third change will come earlier, so the lines on Graph 2 will be lower on the y-axis. Knowing that they have two more opportunities, coaches might even take advantage of tactical changes in the first half more often.

Graph 2 (click to enlarge)

You can also expect the number of substitutions at half-time to go up, due to the restrictions to three slots in which teams can take off players during the second half. Only seven percent of substitutions so far were done at the break, with newly promoted Wattens the most active team at this time (nine). On the end of the scale, substitution resistant Altach and Sturm have only used this opportunity twice, with all the other teams recurring three, four or five times to it.

On a club level, teams which tend to take their first changes later also tend to take their second and third later. My hypothesis would be that these patterns won't change all that much, rather we will see more double or even triple subs later on in the game by teams such as Sturm, Austria and Wolfsberg (Admira is a bit more difficult to assess given that they have their third head coach this season already). 

So far for the historic data. Beyond these, we are more interested in the way the new rule might affect teams and their playing performance during the rest of the season. We need therefore a way to assess the quality of those players which might benefit from more substitutions, i.e. the players who have not been regular starters or are not regularly subbed on when not in the starting eleven.

One possibility to assess their quality is to simply look at the number of minutes they have played (league only), assuming that higher quality players tend to get more game time. We therefore rank the players of each team by the number of minutes played and compare afterwards those players with the 12th to 14th most minutes (regular subs) to those with the 15th and 16th most. The latter are those who should benefit the most from the upcoming rule change.

Graph 3 (click to enlarge)

Higher levels of minutes played by either subgroup indicate in theory higher levels of quality, hence the club should benefit more from the new rule. As we can see in Graph 3, there is a mostly linear relationship between both indicators, with the notable exceptions of probably-not title candidate LASK and Hartberg. Both of them rely on a strong core of 14 more or less regular players, but lack depth afterwards. The latter are an interesting case, as they have reached the upper play-off group, which means that they cannot be relegated anymore but might reach the Europa League, which would be a huge success given their stature.

There is no surprise that Wolfsberg were the only club decidedly against the rule change, given their location in Graph 3. They neither had nor will have strong impact coming from the bench, which is the more interesting as they also competed at the European level before Christmas and are still in contention for another year of international football.

Leaders Salzburg should definitely be able to exploit the new rules given the large resources at their disposal, giving them an edge in the title race (which also includes third-placed Rapid). At the other end of the table, Mattersburg might have a little advantage and Admira a small drawback in a relegation battle which will be fierce, with the six teams in the lower play-off separated by four points only.

Minutes given to regular substitution players are in any case not the only way to measure squad involvement and depth. One could also analyse the total number of players used and compare teams by the amount of footballers they field during the course of a season, either total or above a certain threshold of minutes. These measurements are fine yet can be improved to get a more detailed picture. I propose therefore a methodology, borrowed from Political Science, which counts not the actual but the effective number of units (in this case, players) in a given system.

Consider the case of two fictious parliaments. In the first one, Party A got 42% of the seats, Party B has 38% and Party C the remaining 20%. In the second one, there is a majority Party D with 60% of the seats, meanwhile the rest of the mandates are distributed among parties E (25%), F (10%) and G (5%). Which one of them has more parties? 

The answer is that it depends. Surely, you could simply count parties in each chamber without further consideration of their numerical strength, which would show that there are more parties in the second example (four) than in the first one (three). This is simple, but also misleading. Our hypothetical Party D would in reality be able to govern quite easily without bothering much about the other parties, meanwhile in the first example, no party alone has enough seats to reach a majority. It is therefore more accurate to count the parties not equally, but rather weighting their seats (or vote share, if you are interested more in the electorate than in the parliament) according to their own strength and relative to the strength of the other represented parties.

That is where the idea of the effective (rather than the actual) number of parties comes into place. The concept is satisfyingly described on Wikipedia, from where I also copied the formula, although I use a slightly different one. 

Formula to calculate the effective number of players

It looks more complicated than it actually is. You basically take 1 (if you work with percentages) and divide it by the sum of the squares of the shares. In the case of our two exemplary parliaments, the number of effective parties in the first one would be 2.8 and in the second one 2.3, so the difference is actually reversed in comparison to the simple count. This difference is however much closer to reality than following the naive assumption and counting all the units the same way.

We can apply this concept to football easily, we simply have to adjust the formula a bit and of course use minutes or starts instead of seats or vote shares. Given that minutes played by all the players in a team are variable (due to injuries and sending-offs, a team's players not always play the sum of 11*90 minutes), we have to make the values comparable. We do this by not dividing 1 by sum of squares but using the square of the sum as the dividend. 

To make this a little clearer, we'll apply this to a very simple example, a team which in a single match makes three substitutions at half time and compare it to a team which plays with the same eleven players during the whole game. The first team would have 

(90+90+90+90+90+90+90+90+45+45+45+45+45+45)^2 

divided by 

(8100+8100+8100+8100+8100+8100+8100+8100+2025+2025+2025+2025+2025+2025)

effective players, i.e. 12.74. The team without substitutions accordingly would have 11 effective players.

By applying this formula to the sum of minutes played and starts throughout the season so far, we can calculate the effective number of players and starters for each team. 

Graph 4 (click to enlarge)

By comparing the actual and effective numbers of players used, we can see how many players teams give minutes and also how evenly they distribute minutes among them. A quick look at graph 4 shows that teams cluster to a certain point. St. Pölten stands out in absolute terms, a strategy not really backed up by results so far (they will start the remaining from the last position). Rapid have given a lot of young players a limited amount of minutes without conceding them starts, meanwhile the rest of teams has used between 24 and 28 players out of which 21 to 27 have been starters. 

The picture clearly changes when we look at the effective numbers of players used and started. St. Pölten still leads the trail in terms of the amount of players used, but Salzburg have more effective starters, indicating a high level of rotation in the league. This might be a decisive advantage over title rivals LASK, who used the same number of players and just one starter less in absolute terms, but whose substitution players received far less minutes among them.

In the middle, there are a lot of teams in a quite congested area of the graph. Although I put the team names with an angle, there was no way to prevent this overplotting, because teams are quite close to each other, hence there are no big differences to expect for the rest of the season. Interestingly, the closely packed teams are all from the lower play-offs, with Austria Vienna having a slightly deeper and more balanced squad than their direct rivals. This might favour them to finish first in the lower play-off, a position that would give them the chance to qualify for Europe in spite of a rather underwhelming campaign so far.

At the end of the scale, there are those three teams which also used their players 15 and 16 the least (Graph 3). Wolfsberg, Hartberg and Sturm will battle for European qualification, but based on their squad depth and quality will not be able to join the title race, even with the point difference halved.