1. 1 Raúl Hileno, Cristòfol Salas, & Bernat Buscà

2. 2 INTRODUCTION Attack tempo is the elapsed time between the setting touch and the attack hit (Fernández, Salas, & Molina, 2009). Fernández, M., Salas, C., & Molina, J. J. (2009). Technical and tactical variations in the blocking of zero attacks considering contextual variables: the influence of the scoreboard in volleyball. Kronos, 8(14), 71–78.

3. 3 INTRODUCTION Attack tempo is one of the main variables in the game because it’s a determinant factor for the block cohesiveness and the attack efficacy (Afonso & Mesquita, 2011). Afonso, J., & Mesquita, I. (2011). Determinants of block cohesiveness and attack efficacy in high-level women’s volleyball. European Journal of Sport Science, 11(1), 69–75.

4. Attack tempo 4 INTRODUCTION Data Volley System (Data Project, Bologna, Italy, release 3.4.2) includes attack tempo in its category system.

5. 5 INTRODUCTION The different user manuals of this software are unclear with the criteria to distinguish quick, fast, and high attacks.

6. Fernández, M., Salas, C., & Molina, J. J. (2009). Technical and tactical variations in the blocking of zero attacks considering contextual variables: the influence of the scoreboard in volleyball. Kronos, 8(14), 71–78. 6 INTRODUCTION Fernández et al. (2009) propose three criteria to define the attack tempo categories: 1) Control the trajectory (maximum height) of the setting pass. 2) Observe the relationship between set and attack. 3) Examine the interaction between attack and block.

7. 7 INTRODUCTION The purpose of the present study was to analyse the relationship between attack tempo and type of block in high-level men’s volleyball. Thus, we expected to determine: 1) The time intervals when the different types of block are significantly formed. 2) A temporal threshold to differentiate fast and high attacks of the outside hitters.

8. Blanco, A., Losada, J. L., & Anguera, M. T. (2003). Data analysis techniques in observational designs applied to the environment- behaviour relation. Medio Ambiente y Comportamiento Humano, 4(2), 111–126. Bakeman, R., & Gottman, J. M. (1992). Observing interaction: an introduction to sequential analysis. Cambridge, UK: Cambridge University Press. 8 METHODS Type of data SequentialConcurrent Event-base Time-base III IIIIV T12 DB. T18 HB. T14 DB. T04 HB. … Multi-event Timed-eventState/Interval Event Observational design F/N/M Nomothetic Idiographic PunctualFollow-up

9. 9 METHODS Participants 15 volleyball matches (57 sets) from the 2010 Men’s Pan- American Cup held in San Juan (Puerto Rico). 9 national teams: Argentina, Brazil, Canada, Colombia, Dominican Republic, Mexico, Puerto Rico, USA, and Venezuela. 1451 multi-events (attack-block interactions).

10. 10 METHODS Observational instrument 1) Attack tempo = 21 categories: 0.2 to 2.2 s. 2) Type of block = 5 categories (Data Volley System): No block Single HoleDoubleTriple

11. 11 METHODS Procedures and material The matches were recorded using a digital camcorder (JVC Everio GZ-MG630) at 25 FPS.

12. 12 METHODS Procedures and material Frame-by-frame analysis was performed using Kinovea video analysis software (Charmant & Contrib., Bordeaux, France, release 0.8.15).

13. 13 METHODS Procedures and material Multi-events were recorded using MS Excel 2007 and were analysed using SDIS-GSEQ statistical software (Bakeman & Quera, Atlanta, GA, EUA, release 5.1).

14. 14 METHODS Statistical analysis The relationship between attack tempo and type of block criteria was assessed using Pearson’s chi-square tests for independence. Statistical significance was set at P < 0.05. The adjusted residual for each cell of the contingency table was computed. A z-score greater than 1.96 indicated that the relationship between a given and a target category was significant.

15. 15 RESULTS There was a relationship between attack tempo and type of block criteria (  2 = 718.50, P < 0.01). Twenty-two significant relationships were found between the given and the target categories (Z > 1.96, P < 0.05): No block Single HoleDoubleTriple 0.4, 0.8 – 0.9 s 0.2 – 0.9 s 1.0 – 1.2 s1.3 – 1.8 s1.6 – 1.8 s

16. 16 DISCUSSION Non-cohesive blocks + jump settings in ideal zones + attack simulations by the middle hitters (Afonso, Mesquita, Marcelino, & Da Silva, 2010) No blockSingleHoleDouble Triple Cohesive blocks + settings in non- ideal zones + non-simulations by the middle hitters (Afonso et al., 2010) Quick attacks of the middle hitters: 0.3 – 0.5 s (Selinger & Ackermann-Blount, 1992) Quick attacks of the middle hitters: 0.3 – 0.5 s (Selinger & Ackermann-Blount, 1992) Fast attacks of the outside hitters: 0.6 – 1.2 s (Selinger & Ackermann-Blount, 1992; Zimmermanm, 1993) Fast attacks of the outside hitters: 0.6 – 1.2 s (Selinger & Ackermann-Blount, 1992; Zimmermanm, 1993) High attacks of the outside hitters: 1.3 s onwards (Zimmermanm, 1993) High attacks of the outside hitters: 1.3 s onwards (Zimmermanm, 1993) Afonso, J., Mesquita, I., Marcelino, R., & Da Silva, J.A. (2010). Analysis of the setter’s tactical action in high-performance women’s volleyball. Kinesiology, 42(1), 82–89. Selinger, A., & Ackermann-Blount, J. (1992). Power volleyball. Paris: Vigot. Zimmermann, B. (1993). Main characteristics of defense (block, court defense, counterattack) in top volleyball. International Volley Tech, 1(93), 9–16.

17. 17 CONCLUSIONS Non-cohesive blocks No-blockSingleHole 0.2 – 1.2 s Quick/Fast attacks DoubleTriple 1.3 s onwards Cohesive blocks High attacks Temporal threshold

18. 18 Raúl Hileno, Cristòfol Salas, & Bernat Buscà