In the early 1980s, Keith Lyons started to quantify ball in play time in rugby union football. When he shared his findings with coaches and game administrators, there was a sense of disbelief about his findings.
An early example is from an international game played on 16 January 1982 in what was then the Five Nations rugby tournament. Scotland played England at Murrayfield in a game refereed by Ken Rowlands (Wales).
The first half game time was 42 minutes and 33 seconds. The ball was in play for 10 minutes 28 seconds.
The second half game time was 44 minutes. The ball was in play for 13 minutes 10 seconds.
In the whole game, the ball in play time was approximately 27% of the available time. By 2015, ball in play time in the Six Nations Championship had increased to 46% of game time (link). Benjamin Pollard and his colleagues (2018) have provided more recent data about ball in play times in rugby union football.
In the 1990s, RAI broadcasts of Serie A association football games measured gioco effettivo. Howard Hamilton (2013) defines this as effective time and proposes that “effective time as the total amount of time that the ball is in play in the match, after removing all stoppages due to fouls, ball outs, corners, substitutions, injuries, goals, and so forth” (original emphasis).
Howard notes that in the 2010-2011 English Premier League season “effective time varied between 44 and 66 minutes, centered about a mean effective playing time of 55 minutes 6 seconds”. In that season, there were two games with 66 minutes ball in play time: Manchester United v Wolves; and Arsenal v Liverpool.
In the 2018 FIFA World Cup (link), ball in play time varied from 45 minutes 57 seconds (Morocco v Iran) to 68 minutes 46 seconds (England v Belgium). The median ball in play time was 56 minutes 35 seconds.
Ball not in play?
At Sports Wizard®, we have been contemplating how we might conceptualise and operationalise ball not in play time as we think there are important performance gains to be had in using this time in strategic and tactical ways.
We use the term dwell time to refer to opportunities to organise and act when the ball is not in play with the aim to achieve a performance standard that is rooted in game preparation and within-game individual, unit and team optimisation. Our conversations with our partners focus on the flow of performance throughout a whole game and the ownership of the totality of game time.
Dwell time has a variety of uses in the literature. We see our use of the term connected to but distinguishable from these uses. Some of the literature is noted in the next section of this post.
In non sport contexts …
In transportation, dwell time refers to the time a vehicle spends at a scheduled stop without moving (Herbert Levinson, 1983; Tyh-ming Lin and Nigel Wilson, 1992; Kenneth Dueker and colleagues, 2004; Robert Bertini and Ahmed El-Geneidy, 2004; Thomas Lumley, 2019). Herbert Levinson (1983) established a seminal approach to the study of dwell time that has a resonance beyond transportation and in doing so demonstrated the potential for closely observed temporal behaviour.
In cybersecurity, dwell time is the duration a threat actor has undetected access in a network until it is completely removed (Susmit Jha and colleagues, 2010). In information retrieval, dwell time is the actual length of time that a visitor spends on a page (Chao Liu, Ryen White and Susan Dumais, 2010) before returning to the Search Engine Results Pages. It has been used as a metric in learning to rank, query expansion and query-independent page importance. In the literature on linear switched systems, dwell time is used to measure the stability of these systems between consecutive switchings (Joao Hespanha and Stephen Morse, 1999; Xudong Zhao and colleagues, 2012).)
In sport contexts …
Athalie Redwood-Brown and her colleagues (2019) provided a summary of the effects of playing position, pitch location, opposition ability and team ability on the technical performance of elite soccer players in different scoreline states (see also: Wayne Tucker and colleagues (2005); Carlos Lago and Rafael Martin (2007); Joseph Taylor and colleagues (2008); Carlos Lago (2009)). Athalie Redwood-Brown and her colleagues (2019) investigated how players’ performances varied (in relation to playing position, opposition ability, team ability, pitch location and time scored) at different scoreline states at home and away games.
Daniel Linke, Daniel Link, Hendrik Weber and Martin Lames (2018) quantified the contribution of game interruptions to the fatigue-related declines in match running performance over the course of a football match (n=792 Bundesliga games). Results showed a significant decline in effective playing time over the course of a match, from 66.3% of the total playing time in the first 15 minutes to 55.9% in the final 15 minutes of a match. Under consideration of the total playing time, match running performances decreased by 24.2% on average; considering the effective playing time, they decreased on average by only 10.2%. It can, therefore, be concluded that more than half (57.9%) of the commonly reported decline in match running performance cannot be assigned to physical fatigue, but rather to an increase in game interruptions as the game progresses. They concluded “the decline in players’ match running performance during football matches is substantially amplified by a proven increase in game interruptions, indicating that there may be a tendency among practitioners to overestimate fatigue-induced performance declines” (our emphasis).
Sarah Whitehead and her colleagues (2018) reported on the use of micro-technology to quantify the peak demands of football codes. They noted “Given the differences in peak match-demands between codes, prescription of training should be football code and position specific. The highest velocity-based running demands are reported for Gaelic Football, followed by Australian Football; however, the peak acceleration/deceleration demands reported are greatest in rugby league. Positional differences exist across all the football codes, and differences are dependent upon the variables investigated”. (See also, Chris Carling and colleagues’ (2018) commentary on this paper, namely, “it is our view that further debate and additional research are necessary in relation to player monitoring and conditioning”.)
Spatio-temporal analysis was discussed by Joachim Gudmundsson and Michael Horton (2017). They noted Xinyu Wei and colleagues’ (2013) analysis of formations in association football and the identification of stoppages in play (classified by the reason for the stoppage: out for corner; out for throw-in; foul; or goal). Michael Horton’s (2018) thesis investigated the use of algorithms for the analysis of spatio-temporal data from team sports. It contains references to stoppages in play as part of temporal segmentation including their definition in terms of the breaks between possession plays.
Thomas Kempton and Aaron Coutts (2016) noted in their study of rugby league “matches played away from home, early in the season and following short recovery cycles were associated with reduced relative total and High Speed Running distances. Matches won contained less relative total and High Speed Running distance; whereas only High Speed Running distance was higher against weaker opposition”.
Tim Gabbett (2015) discussed the influence of ball-in-play time on activity profiles of rugby league match-play. He concluded “the greater movement, contact, and repeated high-intensity effort demands when rugby league time-motion data are expressed relative to ball-in-play time. Furthermore, the reduction in relative intensity with longer total ball-in-play time suggests that during prolonged passages of play, players adopt a pacing strategy to maintain high-intensity performance and manage fatigue”.
Pieter Vansteenkiste and his colleagues (2014) sought to measure dwell time percentages from head-mounted eye-tracking data.
Malte Siegle and Martin Lames (2012) analysed game interruptions in Bundesliga football in detail and the tactical use of game interruptions. They noted “an average of 108 interruptions per match. Throw-ins (40) and free kicks (33) were most frequent. Goal kicks (17), corner kicks (10), substitutions (4), and kick offs (3)”. They observed “for 38% of the total match time observed, matches were halted. The mean duration of running and interrupted match parts were 32.1s and 18.7s, respectively”.
Jason Williams, Mike Hughes and Peter O’Donoghue (2005) reported on the effect of rule changes on game time and ball in play time in rugby union football. (See also, Ken Quarrie and Will Hopkins, 2007)
In vision research …
Jan Theeuwes and Richard Godijn (2004) investigated the duration of attentional dwell time (as a variant of the attentional blink paradigm) and estimated a dwell time of approximately 250 msec..
Riitta Hari, M Valta and K Uutela (1999) noted that “attentional dwell time is prolonged by ~30% in dyslexic adults compared with normal readers”.
Jos Adam and Fred Paas (1996) reported their study of dwell time in reciprocal aiming tasks. Their tentative conclusion was “that depending on the task constraints dwell time might partly depend on the speed of the movement and partly on processes related to feedback pertaining to the movement just completed”.
Bruce Abernathy and David Russell (1987) investigated visual search strategies of expert and novice badminton players. They concluded that experts were distinguished from novices by the use made of received information.
James Bergen and Bela Julesz (1983) discussed visual persistence and shared their approach to temporal restriction to determine type of information extracted. (1983:857) They discussed attention as a selective process operating at or near the level of the primary visual cortex.
Talking about performance
We have found dwell time to be an excellent way to talk about performance with our partners. Whilst each of them finds their own way to refer to this time, we share an understanding about flows in performance, behavioural and psychological momentum and the ownership of game time.
The more we observe and discuss dwell time the more we see its potential to enhance performance and extend our qualitative understanding of sport behaviours.