A knowledge discovery framework for the assessment of tactical behaviour in soccer based on spatiotemporal data

Figures & data

Figure 1. Sketch of the conceptional model. Based on the coach’s view on the exercise, we structure the temporal domain into meaningful phases. Phase transitions are the crucial moments of the exercise, and are therefore described by measurements based on the position data. Using unsupervised clustering techniques, different behavioural patterns are extracted and related to performance indicators.

Table 1. Summary of the description of the one-versus-one exercise. See [28] for the full study design.

Phase	Description
Approaching	The exercise starts (t1) with the beginning of the attacker’s movement (at the centre circle) into the direction of the defender (starting at the penalty box). Thereafter, the defender also runs into the direction of the attacker the players approach each other. In an adequate distance to the attacker the defender slows down to be able to attack the striker efficiently (t2, placing), when/before the striker tries to pass the defender.
Confrontation	This phase is the direct confrontation between the two players. At t2, chosen by the defender, the attacker has to prepare for an attempt to pass the defender. The defender adapts to the speed of the striker, which means that he is running backwards. The time of t3 is the moment, when the attacker makes the first movement to irrevocably go into one direction (left or right) in order to pass the defender.
Duel	If the striker was successfully passing the defender, the defender has most often still the opportunity to prevent a shot/goal, if he wins the running duel or is able to block the shot.

Table

Basic fuzzy statement	Fuzzy truth value
s1: attacker is accelerating at time t	$v(s_1(t))=\frac{{\sum }_i{\mu }_{P_i}(t)\hspace{0.17em}{\mu }_{\hspace{0.17em}ac\hspace{0.17em}}({\overline{a_1}}_i)}{{\sum }_i{\mu }_{P_i}(t)}$
s2: defender is decelerating at time t	$v(s_2(t))=\frac{{\sum }_i{\mu }_{P_i}(t)\hspace{0.17em}{\mu }_{\hspace{0.17em}dc\hspace{0.17em}}({\overline{a_2}}_i)}{{\sum }_i{\mu }_{P_i}(t)}$
s3: attacker is accelerating laterally at time t	$v(s_3(t))=\frac{{\sum }_i{\mu }_{P_i}(t)\hspace{0.17em}{\mu }_{\hspace{0.17em}lat,ac\hspace{0.17em}}({\overline{l_1}}_i)}{{\sum }_i{\mu }_{P_i}(t)}$

Table

Rule	Meaning
R1	T1 is fired at time t if $v(s_1(t))\ge {\theta }_1$
R2	T2 is fired at time t if t is after phase P1 and $v(s_2(t))\ge {\theta }_2$
R3	T3 is fired at time t if $v(s_3(t))\ge {\theta }_3$

Figure 2. The disagreement in the transition moment prediction between the two sports experts (E1–E2) and the disagreement between our detection algorithm with the first expert (E1–NN) and second expert (E2–NN). Left plot shows results for t₂, right plot for t₃, respectively.

Figure 3. Spectral clustering result with performance indicators for three identified behavioural patterns (left) and the derived linguistic description based on four manually selected features (right).

Table 2. Summary of the player assessment.

Player	Games	Goals	Goal ratio	Exp-GR	GSI	P(A)	P(B)	P(C)
P2	7	4	0.57	0.22	1.44	0.12	0.76	0.12
P3	8	2	0.25	0.20	1.33	0.15	0.66	0.20
P4	7	0	0.00	0.20	1.30	0.26	0.59	0.15
P5	9	3	0.33	0.19	1.27	0.20	0.58	0.21
P6	7	2	0.29	0.19	1.26	0.29	0.54	0.17
P9	9	0	0.00	0.15	0.99	0.40	0.27	0.33
P10	9	1	0.11	0.15	0.95	0.62	0.15	0.23
P11	6	1	0.17	0.14	0.92	0.48	0.18	0.34
P12	9	1	0.11	0.14	0.91	0.28	0.26	0.46
P13	9	0	0.00	0.13	0.85	0.39	0.17	0.45
P14	9	1	0.11	0.13	0.84	0.44	0.13	0.43
P15	7	1	0.14	0.12	0.79	0.29	0.16	0.55
P17	6	1	0.17	0.12	0.75	0.25	0.14	0.60
P19	6	1	0.17	0.10	0.65	0.33	0.03	0.64
Total (P1–P20)	124	19	0.153

Figure A1. Illustration of the signal decomposition based on discrepancy norm, which yields a coarse-to-fine approximation due to the chosen level of the generated tree of nested intervals. That three vertical solid lines indicate the transition moments t₁, t₂ and t₃ (from left to right).

R. Leser, B.A. Moser, T. Hoch, J. Stoegerer, G. Kellermayr, S. Reinsch, and A. Baca, Expert-oriented modelling of a 1vs1-situation in football, Int. J. Perform. Anal. Sport. 15 (2015), pp. 949–966.

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