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JK Profile picture
@_JKDS_
Jul 19 • 6 tweets • 2 min read Twitter logo Read on Twitter
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📊What are the characteristics of successful Premier League teams?

Investigating how strongly a range of team metrics correlate with points accumulated in a season, using data from the last 5 Prem seasons.

Correlation scores indicate strength & direction of correlation (1/5) Image
Correlation scores are in the range [-1, 1], with magnitude > 0.4 indicating moderate correlation with points.

We know that goal diff and points will be closely related, and we include it to demonstrate a metric that correlates extremely strongly with points: r =0.97 (2/5) Image
On the other hand, we see some metrics that appear to have absolutely no correlation with points accumulated.

Percentage of expected threat (xT) conceded by opposition crosses is a great example of this: r = -0.02 (3/5) Image
Plenty more in-depth work to come on this, including a discussion/digestion of the initial results shown.

As a quick preview, we can look at the linear correlation between any pair of metrics using a correlation matrix. Please zoom in!🔎 (4/5) Image
A few notes: (i) All metrics have been generated by aggregating Opta event data over the past 5 Prem seasons. (ii) Some metrics are normalised by ball losses as a proxy for "per possession". (iii) As always, code is available on GitHub:
(5/5)github.com/jakeyk11/footb…
Brief definitions of metrics used: Image

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More from @_JKDS_

JK Profile picture
May 29
BIG THREAD OF PREMIER LEAGUE DATA AND VISUALS.

An extensive collection of data visuals, statistics and insight that covers the entirety of the Premier League 22/23 season. (1/14) Image
Teams ranked by total threat creation. Liverpool, Leeds & Chelsea significantly underperforming based on threat created.

Forest some way off the rest of the league by this metric, making their survival even more impressive! (2/14) Image
De Bruyne, TAA & Trippier lead the way by threat created through in-play passes. Mitoma and Grealish lead by threat created through carries. (3/14) Image
Read 14 tweets
JK Profile picture
Feb 12
📊🧵Big thread of EFL Championship data and visuals!

Up first, which teams have generated the most "threat" per 90, and from which areas of the pitch? (1/12)
Which players have generated the most "threat" per 90 for their respective teams - broken down into threat creation through passes and carries. (2/12)
A closer look at the top threat creators through successful carries.

As expected, in general players have more success carrying the ball from the less-congested wide spaces.

K. Davis, J. Sargent, T. Pukki frequently drop deeper and carry the ball forward for their teams (3/12)
Read 12 tweets
JK Profile picture
Jan 10
🆕📊 Premier League - Full Back (FB) interplay

Liverpool FBs have a reputation for combining to switch play and create chances, but which other team's FBs combine well?

Ranking teams by mean threat generated /90 through in-play passes between starting full-backs.

A thread: Image
Firstly, let's address how we assess the 'quality' of passes between FBs. We use xT as a statistical measure of the impact that the pass has on a team’s probability of scoring.

However, it does not tell us what actually happens after the pass, which is clearly important.
To address this, we take a look at 10 seconds worth of events that follow a pass between full-backs.

If a shot is taken within this time, the pass clearly had at least some positive impact on the team. Such passes are marked in white (rather than coloured by xT).
Read 9 tweets

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