This blog post is the first of a three-part series into the effect that score-line has upon passing in hockey. For these blogs, score-line refers to whether the analysed team at the time of performing a pass was behind (losing), level (drawing) or ahead (winning). This blog will examine pass outcome, which is the % of complete and incomplete passes.
It will probably come as no surprise that publicly available match analysis research into hockey is scarce, and with regards to whether performance is affected by score-line, I was unable to find any previous work. This is problematic, given the profound effect that has been shown to have across other sports. For instance in football, it has been shown that when winning, teams complete significantly less high intensity work than when behind or level (Lago et al., 2010; Castellano et al., 2011) and work hardest when level (O’Donoghue and Tenga, 2001; Shaw and O’Donoghue, 2004). When losing, most of the research has concluded that teams have significantly more possession when losing than when drawing or winning regardless of whether they were a successful or unsuccessful team (Lago and Martín, 2007; Lago, 2009; Lago-Peñas and Dellal, 2010; Taylor et al., 2010) – an important distinction given successful teams typically dominate possession.
For those in applied circles, the results of research into score-line are potentially important for a number of reasons. If teams play differently as a consequence of the score-line, this information could help prioritize training time to areas that need development or formulate drills that simulate the effects of the different score-lines. It could also allow teams to devise game plans for specific opponents and score-lines, or in-game allow the coach to change the teams strategies/tactics as a consequence of the score-line in order to protect their weaknesses/exploit their opponents.
All matches were from the 2012 Olympic men’s competitions. The foundation for this blog is my MSc dissertation data, the methods section of which I have made available here.
From figure 1 below, ‘ALL’ is the average of the 12 teams. All teams (ALL) completed a higher % of passes when level, than when ahead or behind, and when behind than when ahead. Further, pass completion was significantly higher when level than when behind (p < 0.0175), perhaps representative of teams taking more risks in order to equal the score.
Figure 1: Pass % by score-line for each team.
Australia’s pass % when behind looks, at first glance, very poor. It is only until further context is added (figure 2) that we realise this is likely due to the very small amount of time they had in possession when behind.
Figure 2: % of possession by score-line.
The Netherlands are the best overall passers, and seem largely undisturbed by the affect of score-line, perhaps because of excellent technical ability (finished 2nd) or some other factor. South Africa are the second best overall passing team, a particularly interesting result given they finished the tournament in 11th place.
Top and Bottom 6
Although score-line was found to have an overall significant effect upon the percentage of complete (p < 0.05) and incomplete (p < 0.05) passes for the bottom 6, no score-line pairs differed significantly. Score-line did not significantly affect the % of complete or incomplete passes.
Figure 3: Pass % by score-line for the top and bottom 6 teams.
The bottom 6’s worst pass % was when ahead. When ahead, they threw three times as many aerials than when behind (not presented here, but also part of my MSc research). This is possibly representative of a lack of confidence in playing possession-based hockey, or is done in an attempt to regroup and force their opponents to gain territory and break them down to score an equalizer.
Although I have only presented pass %, I hope I have shown just how influential the effect of score-line can be, and how different teams and team strengths perform differently under each condition. The next blog in this series will examine the effect of score-line on pass direction.
Castellano, J., Blanco-Villaseñor, A. and Alvarez, D. (2011). Contextual variables and time-motion analysis in soccer. International Journal of Sports Medicine, 32(6), 415-421.
Lago, C. (2009). The influence of match location, quality of opposition, and match status on possession strategies in professional association football. Journal of Sports Sciences, 27(13), 1463-1469.
Lago, C. and Martín, R. (2007). Determinants of possession of the ball in soccer. Journal of Sports Science, 25(9), 969-974.
Lago, C., Casais, L., Dominguez, E. and Sampaio, J. (2010). The effects of situational variables on distance covered at various speeds in elite soccer. European Journal of Sport Science, 10(2), 103-109.
Lago-Peñas, C. and Dellal, A. (2010). Ball possession strategies in elite soccer according to the evolution of the match-score: the influence of situational variables. Journal of Human Kinetics, 25, 93-100.
O’Donoghue, P.G. and Tenga, A. (2001). The effect of score-line on work rate in elite soccer.Journal of Sports Sciences, 19, 25-26.
Shaw, J. and O’Donoghue, O.G. (2004). The effect of score line on work rate in amateur soccer. In Performance Analysis of Sport VI, edited by P.G. O’Donoghue and M.D. Hughes, pp. 84-91. Cardiff: CPA Press, UWIC.
Taylor, J.B., Mellalieu, S.D., James, N. and Barter, P. (2010). Situation variable effects and tactical performance in professional association football. International Journal of Performance Analysis in Sport, 10, 255-269.
Analyst for Wales Men’s Hockey Team
Originally published at self-pass.com