The Rodak to Wembley

As I write these words I am still basking in the glow of Fulham’s glorious win at Wembley! Premier League football beckons and we Fulham supporters are all very excited to see whether the Whites will fare better under the pragmatic footballing philosophy of ‘Parkerball’ than we did the last time we were promoted.

Exceeding Expectations

In this piece I will look, in particular, at data on expected Goals (xG – the expected number of goals a team should score based on the number and quality of chances generated) and expected goals conceded (xGc – the expected number of goals a team should concede based on the number and quality of chances given to the opponent).

This data shows that, over the season, Fulham generated expected goals (xG) of 1.43 per game and had expected goals conceded (xGc) of 1.30 per game.  So, give or take, based on the balance of play, the xG model says Fulham should finish the season with a positive goal difference of around 6. That is upper mid-table form, typical of teams just outside the play-offs.

But hold on! Fulham’s end of season goal difference was actually +16, the fourth highest in the league and a match to their final league position. So, in reality, they scored quite significantly more goals than they conceded. If the xG model is to be believed Fulham’s actual goal difference is around 10 goals better than it “should” be!

Must be Mitro?

You may think this overperformance data makes logical sense, after all Golden Boot winner Aleksandar Mitrović plays for us, so surely this result is explained by our star striker gobbling up every chance coming his way, scoring the goals other strikers wouldn’t?

Well, no it isn’t – Fulham has scored 64 goals this season against an aggregate xG of 65.98, so offensively they have slightly underperformed, by about 2 goals.

The chart below shows our cumulative expected against actual goals through the season, you can see the two numbers have been closely entwined all year.

If we want to understand the secret to Fulham’s success (at least relative to the xG model) we need to look at the other end of the pitch. Its goals conceded, not scored, where the overperformance lives.

Navigating the xGc

As mentioned above, Fulham, have averaged an expected goals conceded (xGc) metric of 1.3 per game, this means that given the number and quality of chances given up, Fulham should concede 1.3 goals a game on average or 59.83 total goals across the season.

But the reality is that, rather than give up 60 odd goals this year, Fulham actually only conceded 48, an average of only 1.04 goals per game and nearly 20% less than expected. 

More simply put, for every 5 goals the xGc statistics say we should concede, we only actually concede 4. For a team like Fulham with 15 league wins this season by a single goal margin, this overperformance is likely to be material in terms of points accumulation and league table position

Is it unusual to overperform to this extent? Well looking at the championship, Swansea demonstrate similar xGc overperformance, and Nott’m Forest are not far behind, but it does seem that this overperformance is large compared to most other teams.

However this level of xGc overperformance is much more commonplace in the premier league – indeed 8 teams in the competition achieved xGc overperformance better than Fulham & Swansea.

This may suggest that at a premier league level, the xG model needs recalibrating…

To dig into this further, below is the chart of the cumulative expected goals conceded and actual goals conceded across the season for Fulham – unlike the goals scored chart, there is a clear and widening gap through the season!

So why has this happened? What does this overperformance in xGc mean and how do we explain it?

Well there are generally 3 possible explanations for this kind of anomaly:

  1. Fulham have simply been very lucky this year, their goal has led a charmed life, but unless some sort of voodoo is involved, this kind of luck is unlikely to be sustainable,
  2. When teams shoot against Fulham, they tend to take shots which are of a consistently lower quality than we would expect based on the position and nature of the opportunity they get. Perhaps opponents are tired from chasing the ball during Fulham’s long periods of possession? Perhaps Fulham defenders put opponents under more pressure when they get into good shooting positions?
  3. When teams take good shots against Fulham, our goalkeeper is just much beter than those of other teams, and simply saves more of the shots that he faces

Or it could be some combination of all 3 of the above…Lets investigate

Is it Luck?

This is a hard question to answer, we can do a simple statistical test (Two Tailed T Test) to see if the data demonstrates some bias, ie is it random or is some other factor driving the team to overperform? This test shows that the overperformance data does not exhibit characteristics of randomness but with a sample size of only 46 matches, we can get to a 95% level of confidence. That might sound high, but it also means that in a league of 24 teams, we would expect at least one team to achieve the type of overperformance that Fulham have by chance alone.

So it could be that Fulham have been that lucky team this year!

Is it the defence or the way we play?

The question to consider here is whether Fulham’s defence or playing style is doing something to reduce the quality of shots so that the probability of opponents scoring is lower than we would expect for the situation / position they are shooting from. This typically requires use of a ‘post-shot’ xG model which measures the quality of the actual shot produced in each goal scoring opportunity, rather than the quality of the situation. We could then see if teams are taking worse shots than we would expect. Unfortunately, such data is kept behind paywalls so I don’t have access to it!

We can see from the public data that Fulham’s defensive stats generally look unremarkable, 13th in the league for proportion of shots on target suggests if Fulham are doing something to worsen opponents shooting, it doesn’t extend to making them miss the goal entirely!

So could it be goalkeepers?

The chart below tracks the growth of the xGc overperformance through the season, it measures the cumulative number of ‘missing’ conceded goals by Fulham this season.

The chart clearly shows that we did not overperform our xGc from the start of the year, we started to do it around game 16 (marked by the green line). As you may have gathered from the title of the article, this also coincides with Marek Rodak taking the gloves and becoming Fulham’s starting keeper (actually there was a slightly bumpy introduction of Rodak into the side, he came in game 13, got sent off in 14, was suspended for 15 then properly took over from 16, but the point stands)!

The xGc overperformance starts almost immediately with Rodak coming into the side, then grows pretty steadily and consistently through the season (there are a couple of setbacks: in games 38 & 39 when Brentford and Leeds scored 5 against us after lockdown off of quite low xG and in game 23 when we conceded 3 at Luton).

The plot Thickens… 

So is this the story of our season? We were basically mediocre all year and then Rodak came in and made us great (well done TK for locking in a long-term contract btw)? Well, maybe, but the story is not quite that simple…

You see, when Rodak took over in goal, Fulham did not actually start conceding fewer goals (wait, what? Didn’t you just say…)!

No, what actually happened is the number of expected goals against us (the xGc) increased massively, so when Rodak came in our defensive performances got worse, a lot worse. It was in xGc terms, comfortably our worst run of form of the season.

In fact our xGc increased from 1.15 over the 13 games with Betts starting in goal to a relatively whopping 1.6 over Rodak’s first 13 games.  How bad is this form? Well, based on the infogol data, only three teams (Charlton, Bristol Ciity & Luton) produced such high xGc across the season.

But, this phase of the season is also where the overperfomance comes in, because despite this high xGc, Rodak conceded the same number of goals (15) in his 13 starts in this period as Betts did in his 13 starts earlier in the season. Indeed Rodak’s shot stopping percentage over this time was 74% over his first 13 appearances, compared to a save percentage of 57.1% for Bettinelli over his first (and only) 13 appearances (this is actually quite a low save percentage, but it should be noted that Betts matched his expected goals conceded, which tells us he faced some tough shots – indeed just 2 more saves and fewer goals conceded would have put Betts save % to a more typical championship level)

So, when Rodak came in, we gave up more and better chances (I have no explanation for why we got so much worse during this phase of the season) and our offensive stats stayed the same, but for whatever reason these extra chances given up did not lead to more goals conceded, so results remained stable during this period.

The next major event to impact Fulham’s defence was the inclusion of Hector in the starting line-up. Following his introduction and for the remainder of the season (20 games) our xGc came back down to 1.22 close to what it was at the start with Betts in goal, but, crucially, the xGc overperformance continued, with average actual goals conceded falling to just 0.9 per game. I suspect the fall in xG at both ends of the pitch reflects Fulham’s developing game management under Parker, where we were able to get a lead and then suffocate the games, limiting both xG and xGc.

Another relevant piece of data – during his 18/19 loan with Rotherham, Rodak actually underperformed his xGc data, conceding 83 goals from an xGc of 75.7 (despite impressing Millers fans during the year). Again this is using pre-shot data so we cannot be sure how much of this over/under performance against xG is explained by shot quality.

Summary and the Eye Test

In trying to answer the homework question as to whether Rodak has been a key driver of Fulham’s success this year, I offer one more chart.

It shows for each team, the goalkeeper save percentage on the x axis and the average xG per shot conceded on the y axis (this can be seen as a measure of the average quality of chance given up by each team).

As you might expect there is a clear inverse relationship between the quality of shot given up and the save percentage of the keepers.

I have shown this by adding a trend line, and in general teams / goalkeepers to the right of the line have performed better than average (given the quality of chances conceded) and those to the left of the line have performed worse than average.

For Fulham, I have split out the two goalkeepers used, Betts and Rodak are shown separately. You can clearly see that Rodak’s save %, approaching 75% betters that of any team, but you can also see that the quality of chances conceded is towards the higher end of the range. Rodak’s peers in terms of the chance quality faced would be Luton, Derby, Hull and of course Betts. He significantly outperforms those peers.

We cannot discount the role of luck in these performance stats and the lack of post-shot xG data is, very much, a limiting factor. But whether due to luck or individual brilliance, the numbers do suggest that with Rodak in goal, Fulham concede a lot less goals than they should given chances conceded.

But what do our eyes tell us about Rodak, does he look like he is having this kind of effect on the team?

Well as a goalkeeper myself (although to no standard of note) I would say that being a good goalkeeper in less about making the spectacular ‘high-light reel’ stops (although Rodak has a few of those),  but is about consistency. Its about not getting beaten by a mediocre shot, ever. If its savable, you save it – always. This is how Rodak has appeared to me, I can only recall a small number of goals conceded where, on reflection, Rodak should have done better. How many goals go ‘through’ Rodak – I would argue its almost none.

So by way of a conclusion I will offer this – I think the ‘eye-test’ supports the data in positioning Rodak as a keeper who exceeds the championship standard and I think Fulham owe a great deal of points this season to consistency of the man between the sticks – simply doing his job, consistently, without fuss, with minimal error. The number of points gained is hard to tell for sure, but I think it likely to be critical to Fulham making the playoffs at all.

For Parkerball to work, with its emphasise on game management and defending narrow leads, it is critical that Fulham do not give away silly unnecessary goals and I believe Rodak is perfect for such an approach.

3 thoughts on “The Rodak to Wembley

  1. I’m getting my head around the xG concept still (it helped reading Moneyball and understanding how they apply similar thinking to the destination and nature of hits in baseball, using huge previous sample sizes of past near-identical hits). This helps me to get my head more around the potential of applying this to shots.
    Have I got this right: xG is basically just about the shots/chances, yes? All other factors are basically discounted because ultimately they are just the way the shots are arrived at, and it’s the end that matters, not the means?


    1. Yes, its a measure of the percentage of similar shooting opportunities (defined in terms of position on the pitch, approximate level of defensive pressure, whether left/right foot/header) which have historically ended up in a goal.

      A key weakness is that if there is no shot, there is no xG. But we can all think of times where great chances did not involve a shot: the striker had the ball nicked away at the last second or passed when he should have shot: and these types of event generate no xG despite being moments where a team could or should have scored…

      Its an evolving area but I think it is interesting when a team does not perform as the xG models predict. The models say Fulham should have conceded a lot more goals, they also say Liverpool should not have won the premier league this year. So it is useful to think about what those teams do that leads to inaccurate predictions.


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