Modern analysis terms explained!

It's fair to say the landscape of coaching and analysis has evolved a lot over the years. We are seeing the emergence of new terms or descriptions of specific stats that sometimes sound a bit overwhelming.

I remember the first time I seen the term 'xG'. I mean, was I supposed to just know what that was?!

Anyway, I've done a previous post on Expected goals that you can check out here. It goes over exactly what it is, how it is calculated and other things to consider. Anyway, I thought I'd stick to that similar theme and just run over a few definitions that I have come across recently that you may not have seen before.

I've listed seven, so let's get into them...

Expected Assists (xA)
If you know about expected goals, you will probably be able to guess what this one is. xA quantifies the likelihood of a pass resulting in a goal based on various factors such as pass location, pass type, and the positions of the passer and potential recipients.

xA takes into account historical data to generate a numerical value that estimates the probability of a successful goal-scoring opportunity arising from a particular pass. It helps in assessing a player's creativity, vision, and decision-making skills by providing a measure of their potential contribution to goal-scoring opportunities, even if the chance was not converted.

Expected Threat (xT)
This is probably the next level up from xA. Expected threat looks to evaluate actions (such as a pass or a dribble) that move the ball into areas of the pitch that are more dangerous and can lead to goalscoring opportunities.

For example, a through pass may not be the assist as there could be a couple more passes before the goal. However, it was the initial through pass that had the impact and so this is rewarded with a score.

If you can consistently move the ball into dangerous areas of the pitch (near the goal) you will have a higher xT score. Unsurprisingly, players like Kevin De Bruyne excel in this metric as they are consistently able to put the ball in dangerous areas of the pitch by making good passes or other actions.

Goals Saved Above Average (GSAA)
One for the goalkeepers this and is almost a reverse of xG. The best way to explain would be via an example.

Let's say your goalkeeper faced 100 shots on target in the season and these shots had an xG of 0.2. From this, you would expect the goalkeeper to save 80 of the shots, and 20 would result in goals. Well, imagine you had a decent GK, and they actually saved 85 of the shots and only conceded 15.

This would mean that as the 'average' number of goals to concede in this position is 20, your GK saved 5 above average (by only conceding 15). Therefore, you could say that they had 5GSAA.

This can also be presented as a % where you could say your GK had a GSAA% of +5%. This is because we expected the GK to save 80% of the shots, but the actually saved 85%.

Shot Creating Actions (SCA)
This metric can help you see which players are the most involved in attacking actions or which teams are the most creative.

More specifically it looks at the offensive actions that lead to a shot (pass, dribble, winning a foul). Players are credited depending on the involvement they had in that particular shot and a single player can receive credit for more than one thing. For example, if an attacking player breaks the lines with a great dribble and then lays off to the striker, they will be credited for both the dribble, and the pass.

Goal Creating Actions (GCA)
Yes, same as above but for just the shots that lead to goals, rather than all shots!

Passes per Defensive Action (PPDA)
This is quite an interesting one actually. It quantifies the number of opposition passes allowed by a team before initiating a defensive action, such as a tackle, interception, or foul.

A low PPDA value indicates an aggressive pressing style, where a team applies intense pressure on their opponents and aims to disrupt their passing game quickly. Conversely, a high PPDA value suggests a more passive or conservative defensive approach, allowing the opposition more time and space on the ball.

PPDA provides insights into a team's defensive strategy, work rate, and effectiveness in disrupting the opponent's attacking play.

Field Tilt (FT)
Field Tilt takes into account what a team is doing with the ball when they have possession. More specifically is looks at touches or passes in the final third. It can help you understand which team is aggressive with their possession and actually looks to attack their opponents by getting high up the pitch with the ball, rather than just keeping possession and not really doing much with it.

Something to consider with FT is that if a team is known to press high then they are likely to have a higher FT as more actions will occur in the opponents defensive third.

As a basic example if one team has 47 passes in the final third against an opponent that only has 19, you could say that the team with 47 had a FT of 71.2%

[47 / (47+19)]

Anyway, if you want a bit more of an explanation of expected goals specifically, you can check out the video I did on it here...

I'm sure as we continue to progress and discover more insights, there will be plenty more acronyms to look out for. Comment below if there is anything you use a lot or have come across that I haven't included in this!

📧 If you enjoyed this post, why not consider subscribing to my free weekly newsletter where I share more tips and industry insights direct to your inbox. Just enter your email address in the field below.

📺 I also have a load of useful videos over on my YouTube channel including a podcast where I interview industry professionals to share more behind the scenes knowledge, advice and ideas.

📝 If you are wanting to improve your CV for a job in sport, you can grab my free template HERE.

💻 If you are a coach or analyst on the look-out for video analysis software (that is actually affordable!) then I got you… check THIS out.