Chapter 187 Big Data Era

"I'm curious, Dr. Satori, and have a question."

While walking back to the training building with Marcus du Satoy, Yang Huan asked the doubts in his mind.

“Why is the football world so uninterested in statistics?”

I believe this is everyone’s doubt.

Since big data can solve so many problems, why doesn’t anyone do it?

Marcus Du Satoy shook his head and smiled. "You are wrong, Master Huan. It's not that no one has done it. It's that many people have been doing it for a long time. It's just that the level of data analysis is still too backward compared to other industries."

"Tell me about it." Yang Huan was very interested.

He is aware of his own shortcomings and deficiencies, and he has always been very self-aware.

Since it is something you don't understand, leave it to someone who does.

Or, just work hard yourself to figure out what it is all about.

Marcus du Sautoy organized the answer to this question in his mind, because he found it difficult to answer.

"The introduction of data analysis and high-tech gadgets into the football world has actually been done a long time ago. After Wenger took over Arsenal, he attached great importance to data. Let me give you an example that I know of."

"Flamini, you should know this player, Master Huan?"

Yang Huan nodded. The French midfielder had just shown some level of performance at Arsenal when he left for AC Milan in Italy.

"When Wenger decided to bring in this player, it was because he heard that Flamini could run 14,000 meters in a game. This number was too amazing, so he went to investigate. After confirming that Flamini's long-range running was not blind, Arsenal brought in this player."

Yang Huan had never heard of this incident, but he found it quite interesting.

"It is also well known that AC Milan has a world-famous Milan laboratory. This laboratory played a great role in their winning the Champions League. Even earlier, the Brazilian national team and Nike of the United States had cooperated in conducting research in this area."

At this point, Marcus du Sautoy's conclusion is very clear.

The introduction of data into football has actually been done a long time ago, and has even developed to a certain extent.

"Master Huan, do you know how many relevant data items oPTA currently collects for each game?"

Yang Huan shook his head this time because he had never had any contact with oPTa.

"There are more than 1,500 items, and they are getting more and more detailed. In the past, everyone only cared about some relatively superficial things, such as ball possession rate, number of shots, running distance, number of dribbles, etc."

At this point, Marcus du Sautoy couldn't help but laugh.

"I still remember that in the early days, oPTA data was calculated by observers sitting in the stands or in front of the live broadcast on TV. It was the most primitive and inefficient manual method, and there were many errors."

Yang Huan couldn't help but smile. It turned out that the oPTa data company, which sounds so impressive, actually has such a history?

"After they were acquired by Sky TV, they received ample funds for development, and continued to improve their software and hardware, and developed specialized analysis software, which allowed them to obtain more and more detailed data."

"So that's how we got movement heat maps, passing route maps and that kind of thing."

Different fields have different meanings, and Yang Huan doesn’t understand everything.

He really doesn't know much about the data field in the football industry, and it can even be said that he knows nothing about it.

In the past, ordinary fans could only see a few items of data at most, but oPTA collects more than 1,500 items of data for each game, which shows how complicated this is.

As long as you pay, you can get the advanced data of oPTa.

"Dr. Satoy, as you said, data has been rooted in the field of professional football for so many years, and several data service companies like oPTA have been developed. Why do you still feel outdated?"

Marcus du Sautoy nodded and smiled, "Because these are just data."

Now, Yang Huan began to understand a little.

"The data provided by companies like oPTA are indeed very detailed. They give us a lot of data, but what can these data show? This requires us to analyze."

“Data is dead, but analysis is alive.”

"To give you a simple example, there is a striker who is very good at scoring goals and is leading the league's top scorer charts, but his team's results are very bad.

"If you only look at the player's statistics, you will find that he is a top scorer because he can get a lot of shooting opportunities every game, and then how many shots can be converted into a goal and so on."

"But if you analyze the whole team more deeply, you will find that this player shoots frantically in pursuit of his own goal, which leads to the team's overall offense lacking threat and unable to operate smoothly."

"Also, there is a defensive midfielder whose interception and tackling data are very eye-catching, and the running distance covered in every game is also very large, but his team does a very bad job in defense. The media and fans have blamed the defense line, but what is the truth?"

"If we analyze it in depth, is there another possibility that this player's individual ability is indeed very strong, but his team and tactical awareness is very weak. He runs all over the field without any sense of position. He cannot appear in front of the defense to provide a strong protective barrier when the team needs it, and he casually exposes the defense line to the opponent's fire."

Now Yang Huan really understood it completely.

Marcus du Sautoy's point is clear: data is not important because these things can be bought.

What is really important, or the key link that determines whether the data is useful, lies in analysis.

"According to the two examples I just mentioned, if we only go to the first step, that is, only analyze the surface data, we will definitely find that the players are too good and the teams are too bad, so many teams will spend a lot of money to introduce these players. As a result, when they use them, they find that they are not right and the players are not used well, and they become so-called parallel imports."

"If you analyze it more deeply, you will find that the problem is not that simple, and you will be closer to the truth."

"So in my opinion, the reason why many people say that data can lie is because the data they get is too one-sided."

“This is a manifestation of a lack of data!”

After listening to this, Yang Huan nodded continuously. This statement was indeed very convincing.

Especially in the United States, a large number of professional competitive sports such as NBA, football, golf, baseball, tennis, etc. are increasing their investment in data analysis, which is enough to illustrate the prospects of data application.

Professional competitive sports all have one common pursuit, and that is results!

Every aspect of football always revolves around scoring goals.

With goal orientation, everything is quantifiable.

As long as it is quantifiable, there is room for big data to play a role.

“So why do many football clubs ignore the data?”

Only then did Marcus du Satoy answer the question that Yang Huan had just raised.

"There are two situations. One is that they think the data is unreliable. The other is that they lack the courage to invest and think that investing so much is not as cost-effective as introducing stars. So we see that almost every team in the Premier League is buying data from oPTA, but they are just buying it."

"AC Milan tasted the sweetness and won the Champions League, but the next year they immediately made changes to the Milan laboratory and terminated all scientific research projects. The reason was simple: their management believed that the current level was sufficient and it would be a waste to continue investing in scientific research."

"They just want to get a rough idea of ​​the data in the areas they are interested in, but they have never thought about establishing a systematic project to scientifically analyze the entire team and the entire football field, because the latter requires too much investment!"

"Football rejects data and high technology, not because it is closed and conservative, but because of money!"

"In the United States, the NBA, NFL and baseball clubs have higher revenues than football, so they have enough financial resources to invest in research and development in this area."

At this moment, Yang Huan understood everything completely.

As I said before, no one is dumber than anyone else in this world.

It’s just like when the founders of oPTA saw that Americans started to introduce data into the NBA and NFL, they immediately started to do it in the Premier League, and there was not much difference in time.

But now, the gap between the data analysis capabilities of European football and those of the major professional sports leagues in the United States is really huge.

Ultimately, it's a matter of money.

The two chatted as they walked, and before they knew it, they arrived at the downstairs of the training building.

Because the new training building is still under renovation, the office of the Data Analysis Center is currently on the first floor of the old training building.

Yang Huan plans to rebuild an independent building for them to use as office space.

It will be Southampton's digital heart in the future.

"Master Huan." Marcus Du Satoy stopped walking. "When Charlene told me that you were very interested in statistics, I didn't believe it at first because Southampton is just a League One team. But after getting to know you, I believed it."

"I believe that no one in the entire football world knows the future of data better than you."

Yang Huan nodded continuously. Both WeChat and game companies attach great importance to data collection and analysis.

He knows the wonderful uses of big data better than anyone else.

In the past, he had neglected football, but now he is determined to catch up.

"But I still have to remind you, Master Huan, that the data of football and Internet companies are different because it involves people, and people are the most complicated, so we need experts in many fields such as anthropology, physiology, nutrition, etc. to collaborate and analyze together."

This means that the more manpower invested, the more R&D funds are needed.

"OK, I understand!" Yang Huan clapped his hands vigorously.

"Don't worry, Dr. Satoi. I've already told you that your data center will have as much funding as you want in the future. As long as you think it's necessary, you can apply for funding to conduct research, and I will support you!"

"Thank you, Master Huan!" Marcus du Satoy immediately thanked him with a smile.

But Yang Huan waved his hand and shook his head, "Don't say thank you yet, I haven't finished yet."

Marcus du Satoy immediately listened carefully.

"Although I will provide strong support in terms of funding and other aspects, I want to see results. We at Southampton will not be like AC Milan, which stagnated after a good start. As long as I am here, I will do my best to support your research and development."

"But I have to see results!"

"I understand, Master Huan!" Marcus du Satoy immediately nodded in agreement.

"Please rest assured, we will not let you down."

This is the case with all scientific research projects around the world. No one is interested in projects that seem hopeless or that will never produce results.

Or to put it simply, scientific research is also a kind of investment.

Marcus du Satoy seemed to be afraid that Yang Huan would not believe him, so he immediately smiled and pointed to the office in the data center.

"I think, Master Huan, you should come in and take a look. Dr. Howard Hamilton has something good!"

It looked like a naughty little devil offering treasures.

Yang Huan couldn't help but smile, "Good stuff? What is it?"

"A wonderful product that has been very helpful to us!"

After hearing this, Yang Huan became really interested.