Pep Guardiola X Data

Mulan

In the 2019-2020 season, Liverpool achieved their highest points tally and won the league for the first time in over 30 years 18 points ahead of Manchester City.

That season was strange as statistics and data showed that the season should have ended differently as shown different stats and data analyzing companies, using different data like xG and other data terms.

What is xG?

Simply put, each shot and chance has a certain likelihood out of all shots and chances similar to it. You take all the chances and the data behind each player, blend them together in a blender and you get a result that is often very close to reality.

Before we get to what went wrong in the 2019-2020 season, we must learn one thing

What Was Supposed To Happen

According to data analytics at least.

On December 31st, 2019, BBC Sport came out with a report showing that data has Manchester City at the top of the table with 4 points difference according to expected goals.

The reality, however, had Manchester City in second place 14 points behind Liverpool.

A month and a half later, StatsBomb released their own report and study which showed that not only did Liverpool score more goals than expected but also conceded less. You can read the full report here

Even Liverpool Echo, which is a pro-Liverpool site, talked about how Klopp and Liverpool broke the system. Based on their statistics, Liverpool gained 18 more points than the club should have.

The End Of The Season

By the end of the season, the data was even more contradictory to reality as it showed that Manchester City had 59 expected goal differences compared to 30 in Liverpool. That's almost twice as many goals that Manchester City was expected to score as Liverpool in Liverpool's greatest season.

Margain Of Error

It should be noted that these studies differ from one another as they use different specifics. That's why these analysts always aim to be on the safe side when presenting their results. Still, they couldn't have been more wrong than in the 2019-2020 season.

People and experts started looking for the reason behind the data contradicting what happened in real life. Here are the popular ones.

Accumulated xG

This one basically states that the reason Manchester City has an xG higher than Liverpool is that they keep attacking while winning opposite to Liverpool who takes a more conservative approach.

So, Manchester City is just more likely to turn a lead by one or two goals into four or five goals than Liverpool. That doesn't really translate to more points as the winner gets three whether they won by one goal or ten.

That seems like a reasonable explanation, right? It sure seemed that way at the time as well.

Infogol's report

Now, it seems like am just adding more reading materials. However, Infogol's report was different as it not only studied the same data as before, but compared it to the teams' status during the game, I.E, whether they were losing, winning, or drawing.

Yes, it did confirm that Manchester City attacks more when winning than Liverpool. However, it showed that there is almost no difference between Manchester City and Liverpool in the quality of their scoring chances while behind or drawing, in fact, Manchester City's goal-scoring chances were better.

Back to square on.

Uhm... Talent?

After all explanations failed and all data seemed to contradict what happened in the 2019-2020 season, the Guardian newspaper interviewed Ted Knutson, StatsBomb found in August 2020. In the interview Ted Knutson stated that the contradiction was caused by talent as it is the main thing among things that data can't quantify perfectly.

Talent is why Salah scores while Sterling misses. It is also why Alisson saves and why Ederson gets scored against.

Is That A Good Answer?

It is a good answer. Am I convinced? Maybe, maybe not.

I am willing to say that Alisson is more talented than Ederson and is the better keeper. However, does the talent difference between Manchester City's attack and Liverpool's attack explain an 18 points difference and the expected goal difference is less than half what it was supposed to be according to data?

The "Duh" Answer

It's not that Manchester City isn't creating chances, but simply them not scoring those chances. I know it is an obvious answer but it is needed so we talk about the most important stat in all of this.

Wasted Opportunities

According to the official Premier League site, Manchester City had a total of 83 wasted goal opportunities. That's not only 18 more wasted opportunities than Liverpool, but it is the highest in the league's history ever since they started collecting wasted goal opportunities data.

Even based on regular shot chances, Manchester City had a 100 shooting chance. That's not the total, that's the difference between them and the ones in second place.

In Conclusion

The 2019-2020 season is a great season to study when attempting to understand what is wrong with Manchester City and Pep Guardiola. It could be easily said that the answer is the players failing Guardiola.

However, in my opinion, there's more to this. And it is a problem that is hugely caused by Pep himself. I will elaborate on that in my next post.



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I am interest to see what kind of arguments you will have. I think PEp is a great coach who sometimes outcoaches himsself but the main reason why he is so unlucky the past view seasons is that football is a very unpredictable sport. I think the try of making it understanble with all this data is just irrelevant to a certain degree.

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It's not his fault that football in unpredictable, it's him trying to control it without counting on his players that is his fault.

Regarding the data, I disagree, you just need to read different data before reaching a conclusion as I show in my follow-up posts in this series.

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I believe that science will always have its limits when it comes to humans. It's quite easy to collate tangible data and try to arrive at a meaningful conclusion, but then there will always be intangibles with humans.

Things like selfishness, the split second decision, his understanding at a particular and other things are some things that science can't always predict accurately.

I'll love to see what your argument will be

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