Players Stats

Players Stats – The World Cup is now in full swing, with the Round of 16 starting this weekend, so who are the best performers so far?

The World Cup is now in full swing, with the Round of 16 starting this weekend, so who are the best performers so far?

Players Stats

Players who dropped out of the top 10 after the first round include the likes of Bukayo Saka and Jude Bellingham, after England’s 0-0 draw with the USA and Brazil’s Richarlison struggled to beat Switzerland 1-0.

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Although some may be surprised, Antoine Griezmann figures to be the best performer at the World Cup so far with an average rating of 8.70 from SofaScore.

He is yet to score but has one assist to his name after creating five big chances in France’s wins over Australia and Denmark.

Griezmann averaged 4.5 key passes per game, one shot on target, four accurate long balls and five duel wins.

Few fans will be surprised to see Bruno Fernandes in the top five after the win over Uruguay (despite Cristiano Ronaldo’s best efforts to claim the first goal).

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Poland’s number one has two clean sheets to his name while also saving one penalty and averaging 4.5 saves per game.

Iran beat England 6-2 on their opening day but beat Wales 2-0.

Mahdi Tarimi scored the second goal to save England from defeat and also set one up against Wales.

Valencia has been impressive for Ecuador, who have high hopes of qualifying from Group A ahead of their crunch clash with Senegal. Time to collect the numbers. Create custom static graphics quickly and easily – anywhere on any device!

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Just as we went from semaphore to telegram to fax to Facebook, understanding football statistics should be easier now than at any point in the past. If you’re reading this blog and you still don’t know your xG from your shoulder, you’re in luck: it’s the best time to start learning.

Here are the things our former and declining (status year) internal data expert, Mark Thompson, wishes he had known when he started:

Expected goals are a measure of the quality of chances, using hundreds of thousands of past shots to create that measure

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This is a relatively short definition of what a complex statistical model might be, but it’s the only concept you need to understand.

It’s also worth noting that xG captures many things, but not everything. It is true that a particularly unusual spin on the ball could potentially affect the scoring opportunity in a way that the model would not pick up, but the model

Taking things like distance and angle to the goal and roughly how clear a player’s sight was at the goal.

‘Stats are what a man does on the pitch’ sounds silly in its simplicity, but it’s a useful frame of mind.

Stats Infographic Graphic

The reason we have ‘expected goals’ as a metric is because people ran statistical models to see if some shots were made better than others. Similarly, some statistics (such as shots) are more clearly related to team results than others (such as passes).

Just because a player does a lot of work doesn’t mean it’s worth a lot. Data scientists (people who build statistical models, really) will often try to figure out what’s valuable and what’s not, but expert opinion.

When you understand that ‘stats are what a person does’, it’s easy to wonder if a player has a high personality for a particular stat because they are.

People will also often talk about ‘per 90 minutes’ – an easy way to ensure that the players at the top of the lists aren’t the only ones who play a lot of football. The figure is compared to the amount of time spent on the pitch (ie 900 minutes would be 10.0 90, 945 would be 10.5).

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Nicolas Otamendi hasn’t had many tackles and interceptions in 90 minutes this season – is that a bad thing? A sign of the quality of the team on this? An indication of the role he is asked to play?

This is a short summary of Marilyn Strathern’s Goodheart’s Law, and in football terms, it’s called ‘The Tottenham effect on Andre Villas-Boas’.

Perhaps influenced by early statistical knowledge indicating that successful teams take more shots, AVB’s Spurs outscored the opposition in nearly every match. And yet he (just) came off the top and left the club with them in seventh.

Take as many shots as you want on your way to becoming a good team. The reaction to possession in football had a similar effect, where teams began to prioritize possession because possession percentage was an indicator of good teams.

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It is also useful to think that ‘stats are what people do on the pitch’. For example, just because a player dribbles or pulls a lot doesn’t mean they will.

After these two points the defensive stats deserve their own special mention as they are more affected than the offensive stats.

There are only limited ways to score goals and create chances in soccer. You score by shooting; You will get opportunities for dribbling or passing.

There are many ways to defend, and the most basic one—collective team formation—doesn’t show up very clearly in the data. As I mentioned earlier, statistics are only about what a player does on the pitch, and especially with defensive players, it’s worth stopping for a moment to think about what a person does on the pitch. what should be done

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Unlike defending, where there are many different ways to do things, there are relatively few ways to keep goalkeepers guessing. Apart from collecting crosses, goalkeepers are only called upon in moments of real danger. Like a flood defense system, you don’t want to think about it until it happens

Because of this, it can be interesting to see how many floods (or targets) they let in. But, as we’ve seen with expected goals, some shots are more dangerous than others, and then some are more valuable than saves. someone else

Most data providers have ‘expected target on target’ or ‘expected target postshot’ models (names vary).

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