systematic record of performance using match and motion analysis techniques. • PA has evolved rapidly over the last decade to a point where most ‘serious’ teams have a dedicated analysts who is an integral member of the backroom team. However, despite the importance of the role it is not uncommon for analysts to have no or limited interaction with players (Carling, Wells & Lawlor). • There role has traditionally been (and I would suggest largely still is) to disseminate video compilations and game statistics. Where is PA currently? Performance Analysis Constraints • Short-term appointments: We all know the competitive nature of professional sport and this makes it hard for all sport science staff to operate with any long-term thinking, but can we find a way? • Arriving by the front door: Too often having an analyst can be a box ticking exercise.
questions which directly inform the coaching process might be dependent on the coaches’ ability to clearly articulate and operationalise what they associate with success in football. This clearly might be a concept which some coaches will struggle with (Anderson 2013) One of the key issues with PA; it relies so heavily on the coaches understanding and openness. S&C coaches, the medical staff and sports psychologists don’t face the same issues. “At this point another important question might be to consider where the stimulus for analysis should lie; does the responsibility lie with the coach or the analyst team? Would we expect the coach to be proactive in setting specific performance related questions or is it the role of the analyst to proactively provide insight which the coach has not previously considered… Compared to other sports science disciplines I don’t think that responsibility lies with the coach as much as it does in PA. Which raise the point is PA a legitimate ‘stand-alone’ sports science discipline or just another tool available to the contemporary sports scientists and coaches? What is clear is that we need more evidence based research on the actually effects of PA, not just papers looking at the game actions themselves. Previous research surrounding feedback has suggested that performers can become too reliant on feedback and thus it suppresses the performer’s ability to identify faults (error detection) and correct faults (error correction) themselves (Hodges & Franks, 2008). Careful consideration should be given as to how and when information might be best delivered to the players to enhance its impact, ‘ultimately, a good performance management and analysis tool is not just a control mechanism but a learning system that effectively communicates and informs’ (Wiltshire 2013)
sports Typical comments about GAME STYLE: “As soon as I was appointed manager in 2011 the big debate was whether I would follow the ‘West Ham way’ which nobody could define, but, whatever it was, I apparently didn’t play it. The fans were being brainwashed into thinking that, historically, the club had a particular style of play which was akin to Barcelona which was potty.” Sam Allardyce (Big Sam 2015)
the model for younger teams. When you’re talking to fans it’s about coming to the game every week and seeing things you hadn’t seen the week before – whether that’s an individual player or part of our game style” Paul Roos (De Stoop 2015) “When players join our club from another club, the adaptation to our game style and the way we go about things can be quite significant early on” Matt Knights (McNicol 2015) “Port Adelaide and Hawthorn play a similar, attractive game style: fast, ambitious and uncompromising when it’s switched on” Matthew Agius (Agius 2014) The team's game plans in marquee matches in 2014-15 would be more streetwise, more astute…. Wenger knew he had to adapt Arsenal's playing style….. he knew he had got the game plan horribly wrong. Not only did we not have a Plan B but Plan A was nowhere near good enough. [http://www.goal.com/en- us/news/85/england/2014/10/16/5190573/no-more-mr-nice-guy-how-wenger-is-getting-tough-to- fuel-arsenals-] Principles of Play
movement of the ball • Look for space • Unbalance defense Transition from Attack to Defense • Press and pressure opposition on the ball to regain possession • Make opponents play backwards to force delay • Get compact to either continue to press the ball carrier or to get organised to defend Established Defence • Pressure zone defense • Limit, direct and pressure opponent in order to close space • Take away wide and deep space • Provoke mistakes and win ball possession Transition from Defence to Attack • Pass the ball away from defensive pressure • Take advantage of defensive organisation • Get attacking players into open spaces • Keep ball possession • Rapid offensive organisation
Maintain possession and create goals scoring opportunities • DEFENDING • Prevent goals • Regain possesion Moments of Play Characteristic playing patterns Regularly repeated, relatively stable, predictable within context Variables of importance – success, excitement, emotion Player and ball movements Interaction of players GAME STYLE INFLUENCES What is game style? Need to develop a definition in order to measure & study it Game style is the characteristic playing pattern demonstrated by a team during games. It will be regularly repeated in specific situational contexts such that measurement of variables reflecting game style will be relatively stable. Variables of importance are player and ball movements, interaction of players, and will generally involve elements of speed, time and space [location].
analysis and GPS tracking Performance Analysis Deeper understanding of game dynamics Improve performance and increase success BENEFITS Relationship of game styles with performance Evolution of sports over time Quantify changes in game styles among teams, players, leagues, coaches Insight into strategies and tactics commonly employed Game style pilot research Define key variables that reflect patterns of game style Use a range of methods to quantify variables Compare performance variables among a range of AFL teams Characterise game styles through combinations of variables 1 2 3 4 SET PIECES mean z-score 1 0 -1 -2 2 1 0 -1 -2 2 ESTABLISHED OFFENCE TRANSITION TO OFFENCE ESTABLISHED DEFENCE TRANSITION TO DEFENCE most control least control best worst MOMENTS IN THE GAME
[general architecture / fundamental rule set of play] Space Optimising position Ball movement Mobility Delay opposition movement Goal-side of offensive players Increase defensive player density Rapid and coordinated organisation [What is possible] Ball Speed1 Rate of ball recovery Weighted position of turnovers Passing sequences Offensive and defensive player numbers Passes per minute Disposal efficiency Location of goal attempts Goal efficiency 1: Edgecomb & Norton (2006) Ball speed Rate of ball recovery1 Weighted position of turnovers Passing sequences Offensive and defensive player numbers Passes per minute Disposal efficiency Location of goal attempts Goal efficiency 1: Vogelbein, Nopp, & Hökelmann (2014) Defence Offence Ball speed Rate of ball recovery Weighted position of turnovers1,2,3 Passing sequences Offensive and defensive Player numbers Passes per minute Disposal efficiency Location of goal attempts Goal efficiency 1 2 3 4 Champion Data (2015) 1: Dawson, Appleby & Stewart (2005); 2: Gomez et al. (2012); 3: Lorenzo et al. (2010)
of turnovers Passing sequences1 Offensive and defensive player numbers Passes per minute Disposal efficiency Location of goal attempts Goal efficiency A B C B A C B A B A D C D B A D C A C B A C B A ABCD ABAC ABCD ABCA ABCA ABCD 1: Gyarmati, Kwak & Rodriguez (2014) Team A Team B 7 5 1: Norton (2013); 2: Norton (2014); 3: Wallace & Norton (2014) Ball speed Rate of ball recovery Position of turnovers Passing sequences Offensive and defensive player numbers1,2,3 Passes per minute Disposal efficiency Location of goal attempts Goal efficiency Ball speed Rate of ball recovery Weighted position of turnovers Passing sequences Offensive and defensive Player numbers Passes per minute1,2 Disposal efficiency Location of goal attempts Goal efficiency Total number of disposals Time in possession ABC (2015) 1: Redwood-Brown (2008); 2: Chassy (2013) Ball speed Rate of ball recovery Weighted position of turnovers Passing sequences Offensive and defensive Player numbers Passes per minute Disposal efficiency1,2,3 Location of goal attempts Goal efficiency 1: Rampinini et al. (2009); 2: Redwood-Brown (2009); 3: Sullivan et al. (2014)
ball recovery Weighted position of turnovers Passing sequences Offensive and defensive player numbers Passes per minute Disposal efficiency Location of goal attempts1,2,3,4,5 Goal efficiency 1: Hughes, Robertson & Nicholson (1988); 2: Michailidis et al. (2004); 3: Olsen (1988); 4: Sotiropoulos, Mitrotasios & Traulos (2005); 5: Yiannakos & Armatas (2006) Ball speed Rate of ball recovery Weighted position of turnovers Passing sequences Offensive and defensive Player numbers Passes per minute Disposal efficiency Location of goal attempts Goal efficiency 15m 30m 40m 50m 80% 71% 48% 63 % 52% best worst SET PIECES ESTABLISHED OFFENCE TRANSITION TO OFFENCE TRANSITION TO DEFENCE ESTABLISHED DEFENCE most control least control mean z-score 1 0 -1 -2 2 passing rate passing efficiency scoring accuracy shot at goal accuracy location of goal attempt ball speed in play period offensive - defensive number rate of ball recovery weighted position of turnover weighted turnovers punished by score tackles per minute of defence total player number in 50 m best worst SET PIECES ESTABLISHED OFFENCE TRANSITION TO OFFENCE TRANSITION TO DEFENCE ESTABLISHED DEFENCE most control least control mean z-score 1 0 -1 -2 2 Hawthorn Sydney AFC GWS PAFC Carlton
-.5 -.25 0 .25 .5 .75 1 West Ham Leicester City Tottenham Hotspur 1 3 7 Manchester City Manchester United 4 5 6 Southampton Arsenal 2 20 Aston Villa Norwich City 19 18 Newcastle 17 Sunderland Bournemouth 16 15 Crystal Palace 14 West Bromwich Albion 13 Watford 12 10 11 Chelsea Everton Swansea City 8 9 Liverpool Stoke City key -1 -.75 -.5 -.25 0 .25 .5 .75 1 Z-score worst best Established defense Transition to offense Established offense Set pieces most control least control Z-score EPL 2015-16 [n = 12] [n = 28] [n = 20] [n = 20] 20 18 16 14 12 10 8 6 4 2 -3 -2 -1 0 1 2 Finishing position Z-score sum 6 8 10 12 14 16 18 20 22 24 26 1 2 3 4 5 6 p=0.03 Finishing position p<0.0001 Z-score sum Future game style research • refine variables of interest • automation of data collection • computer program to analyse rapidly • more sports, levels, seasons etc • better statistical methods of comparisons and characterisation of styles • predictability of outcomes, when style A plays style B etc