Network Analysis – Individual interaction – Field Hockey


The previous post was to share how colours can change a view of how we see things. In this post I wanted to share how network graph for individual can make a good used. Jose Gama et al. (2014) conducted a study on network analysis on intra-team activity in attacking phase of professional football. The results indicated how individual key players are orchestrating the game and providing great influence to the team in engaging the attacking pattern of play.

Here is the final match of the Rabobank Hockey World Cup 2014. The match was between Australia and Netherlands. From the analysis I have chosen a player that possessed the highest interaction in their respective team. However, this analysis did not analysed their playing position related to the zone or area on the field, instead they were placed to their normal position of play.

Both player seem to have different approaches in their game. Visually, what we can see Mark Knowles was heavily engaged with forwards more then his defence. It seems that Australia would be in a more attacking play than Netherlands. Robert seems to have difficulty playing the ball forward. Both of the players had a common job, they initiated the restart. That is why both achieved a high volume of interaction.

Which player shows a positive attributes? Knowles or Robert? Sunderland et al (2006) suggested that most of repossession leading to goal occurred in the attacking half shows  75%  and 42% of all repossession occurred in the attacking 25 yard area. Logically, gaining possession higher towards the D would created a better chance of scoring. So, how effective were they? statistically Knowles made 17% of unsuccessful pass out of 34 passes while Robert made 16% of unsuccessful pass out of 44 passes. Knowles made 82% of successful pass to the forwards and midfield players in total of 20 passes. Robert made 67% of successful pass to forwards and midfield players out of 18 passes. I choose to group up midfielders and forwards as midfields do happen to assist in some of the attack leading to the final third.

The graph shows Knowles delivering more pass heavily to forwards and Robert made an almost evenly distribution of pass to forwards and midfield players both had a difference of 2 passes which would concluded that their both were success in delivering the ball to the forwards and midfields, but were they effective?. In this case, if the analysis can linked the pass leading to a chance of scoring, which is penetration into D, attempted shots on goal and goal, then only we will know how effective the players and passes were in the game.

Mark knowles network HWC 2014

Robert van der host network HWC 2014

Gama, J., Passos, P., Davids, K., Relvas, H., Ribeiro, J., Vaz, V., & Dias, G. (2014). Network analysis and intra-team activity in attacking phases of professional football. International Journal of Performance Analysis in Sport, 14(3), 692-708.

Sunderland, C., Bussell, C., Atkinson, G., Alltree, R., & Kates, M. (2006). Patterns of play and goals scored in international standard women’s field-hockey. International Journal of Performance Analysis in Sport6(1), 13-29.


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