The probability of success has been calculated for each pass. This was done by including a number of determining factors within an Artificial Intelligence model that is based on tracking data. This includes, for example: the length, speed and direction of the pass. But also how much pressure there is on both the passer and receiver. This model shows the pressure on both the passer and receiver in percentages.

Pressure on passer and receiver.

This measurement of pressing is supplemented with a metric based on the zone of the pitch. Inmotio calculates a score by placing a grid over the field in which a box closer to the goal represents a higher value. When the passer and receiver are closer to the goal, the difficulty of the pass increases and so the higher the score is.

Distance to the goal - zone principle

The combination of several factors ultimately provides a value to measure pass quality through tracking data characteristics.

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  1. Andrienko, G., Andrienko, N., Budziak, G., Dykes, J., Fuchs, G., von Landesberger, T. &Weber, H. Visual analysis of pressure in football. Data Min. Knowl. Discov. 31, 1793–1839 (2017).

  2. Goes, Kempe, Lemmink, 2019. Predicting match outcome in professional Dutch football using tactical performance metrics computed from position tracking data.

  3. Link, D., Lang, S. & Seidenschwarz, P. Real time quantification of dangerousity in football using spatiotemporal tracking data. PLoS One 11, e0168768 (2016).

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