New metrics

Combining two data-sets in this way also means we have been able to develop brand new metrics, instantly allowing for a more forensic examination of a player’s performance.

Available for all of the leagues for which you have access to traditional event data, these new metrics include:

Number of Passing Options

Interrogate a player’s use of the ball, and your team’s ability to close down passing lanes using this brand new data set.  This is calculated for each pass and shows the number of unobstructed passing options available to the player on the ball.

Line-breaking Passes

Assess the penetrative nature of the passing throughout the pitch using data that gauges whether a player has the option for a line-breaking pass and how many they actually attempt.

The example below shows all of the passes made by Manchester United’s Paul Pogba against Bournemouth:

All passes

Clear line-breaking opportunities

Line-breaking passes

We are now able to show whether Pogba had an open teammate in a position that would have broken a defensive line, as determined by combining tracking and event data, regardless of whether he took that option.

The highlighted passes in the third graph are line-breaking passes that Pogba actually made during the match – note that these include passes where there wasn’t a clear line-breaking option, which suggests the ball was played into space for a teammate to run on to.

Shots and Passes Under Pressure

We understand that not all shots and passes are created equal, and by combining traditional event metrics and tracking data we’re able to analyse whether every pass and shot is performed under opposition pressure. This gives a much deeper insight into the fundamentals of a player’s performance.

There is a clear preference towards longer cross field balls when not under pressure

Pogba’s pass sonar - highlighting pass distance and frequency under pressure

Pogba’s pass sonar - highlighting pass distance and frequency when not under pressure