Pass disruptiveness is made up of two variables that map the disruption of the opponent.

Individual Induced Movement - Per pass is calculated how much this movement produces the opponent, so it says something about the spaces that are created with that type of pass. This was then standardized per second to compare the effect of passes (Goes et al., 2018).

I-MOV is a tactical parameter that adds a lot of value through the pass success. I-MOV refers to the individual movement by the defending team when the attacking player has made a pass. , standardized per second/meter. A good example of this is a switch of play from the left to the right flank where a lot of movements are required from the opponent. The degree of individual movements made by the defending team's players is being measured between the time that the pass is made and subsequently received.

Individual movement of the defending team, created with a pass

Defensive Disruptiveness - How much disruption of the opponent is made by a pass

The defensive disruption is calculated for each pass based on a model that measures the impact of the pass on the defensive organization of the opponent. When a pass disrupts the defence of the opponent*, the value of it is made visible with this separate feature. Defensive Disruptiveness is the disruption of the defensive organization in order to create gaps for chance creation in offensive areas.

*When calculating this, the actual positions are observed to determine the formation and lines rather than using pre-defined formations like on a team sheet

By combining both of these features, the total Defensive Disruption has been made transparent

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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. 2.Goes FR, Kempe M, Meerhoff LA, Lemmink KAPM (2018) Not every pass can be an assist: a data-driven model to measure pass effectiveness in professional soccer matches. DOI: 10.1089/big.2018.0067

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

  4. Rein, R., Raabe, D. & Memmert, D. “Which pass is better?” Novel approaches to assess passing effectiveness in elite soccer. Hum. Mov. Sci. 55, 172–181 (2017).

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