Linganisha mbinu

	Sequential Behavior Analysis in Sport	Time-Motion Analysis of Match Play
Nyanja	Sport Leisure Studies	Sport Leisure Studies
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1997	1976
Mwanzilishi	Roger Bakeman & John M. Gottman	Thomas Reilly & V. Thomas; Jonathan Bloomfield, Remco Polman & Peter O'Donoghue
Aina	Sequential pipeline for transition probabilities of coded behavior streams	Observational pipeline for quantifying locomotor demands of competition
Chanzo asilia	Bakeman, R., & Gottman, J. M. (1997). Observing Interaction: An Introduction to Sequential Analysis (2nd ed.). Cambridge: Cambridge University Press. ISBN: 9780521574273	Carling, C., Bloomfield, J., Nelsen, L., & Reilly, T. (2008). The role of motion analysis in elite soccer: contemporary performance measurement techniques and work rate data. Sports Medicine, 38(10), 839-862.
Majina mbadala	Lag Sequential Analysis, Sequential Pattern Analysis, Transition Probability Analysis, T-Pattern Analysis	Work-Rate Analysis, Movement Analysis, Locomotor Demand Analysis, Match Activity Profiling
Zinazohusiana	3	3
Muhtasari	Sequential behavior analysis treats a sporting performance not as a bag of independent events but as an ordered stream in which what happens next depends on what just happened. Drawing on Roger Bakeman and John Gottman's authoritative 1997 text Observing Interaction: An Introduction to Sequential Analysis, the method codes play into a time-ordered sequence of mutually exclusive events, builds a transition matrix counting how often each event is followed by each other event at a given lag, and converts these counts into conditional transition probabilities. Crucially, it tests those probabilities against what would be expected by chance, so that genuinely recurrent patterns of play — the move that reliably leads to a shot, the defensive action that triggers a turnover — can be distinguished from coincidence. Hughes and Bartlett's performance-indicator framework supplies the bridge from these tested sequences to actionable tactical knowledge.	Time-motion analysis quantifies the physical demands of competition by classifying a player's continuous movement into discrete categories — standing, walking, jogging, running, sprinting — and measuring how much time and distance is spent in each. Thomas Reilly and V. Thomas's 1976 study of professional footballers established the template: hand-tracking players through a match, classifying their locomotion into movement bands, and showing that different positional roles impose different work-rates, with midfielders covering the most ground. The method matured through video-based work such as Bloomfield, Polman and O'Donoghue's 2007 analysis of physical demands by position in the Premier League, and has since been transformed by GPS and optical tracking that record position continuously and automatically. Across these technologies the analytical logic is constant: turn continuous locomotion into categorized time-and-distance metrics that characterize the locomotor demands of the sport.