Naturalistic decision-making of football coaches

Abstract

Effective coach decision-making is important for achieving success in sport, with the decisions made by coaches during matches having a major influence on match outcome. However, to date there has been minimal research investigating the cognitive decision-making processes of coaches during dynamic match play. The current study aimed to investigate the factors that influence the decision-making process of high-level football coaches during dynamic moments in football matches. We applied the critical decision method to assess the decision-making process of 11 high-level football coaches across two football match scenarios 1.a Send off, and 2. Chasing the game. Data was thematically analysed and coded to the perceptual cycle model which is a model of decision-making whereby information available in the world activates decision-maker schemata resulting in an action in a cyclical nature. The results indicate that decision-making processes differ based upon situational constraints. In the Send off scenario, participants relied on mental models and schemata rather than information taken from the match to select a course of action. In contrast, in the Chasing the game scenario, participants tended to use information from the match to assess the situation prior to selecting a course of action. The findings have implications for coach education programs, which are discussed.

Keywords

Communication emotional regulation mental models perception schemata soccer

Introduction

The quality of decision-making is often what separates winners from losers in sport.^1,2 Decision-making is broadly defined as the selection of a course of action amongst different options.^3,4 Decision-making research in sport has investigated the differences in process and outcomes between novice and expert decision-makers^5,6; and has largely focused on the decision-making of athletes, referees, and to a lesser extent, coaches.^7,8 Given the critical role coaches play in match outcomes,⁹ understanding coach decision making during matches and the factors influencing coaching decisions and decision quality is critical.^10–12

Sports coaching can be considered a continual process of decision-making to handle the varied tasks.^13–15 For some tasks such as developing pedagogy associated with player training and development coaches can spend time comparing and contrasting to select the best option to satisfy their goals.^16,17 However, they are also faced with dynamic and changing circumstances which require decisions to be made quickly and without time to consider several options.^16,17 For example, coaches engage in thorough planning prior to the season regarding player development and selection strategies, however, during the season coaches must be adaptable to changes and alter decisions to support their goals.^18,19 During matches coaches are faced with uncertainty and dynamic moments which require an effective response, which cannot be precisely planned for, therefore, it is important to understand the decision-making processes engaged in by coaches.

Classical decision-making theory suggests that options are compared and contrasted to optimise or satisfice a goal.^20,21 However, decision makers are often under time pressure which makes this impossible.^22,23 The heuristics and biases framework suggests that the decision-making process and option generation is driven by mental shortcuts and the utilisation of a selection of readily available cues.²² The heuristics and biases framework has been applied to understand and describe the processes which result in deviations from optimal decision.^24,25 However, experts are able to select courses of action which not only satisfy the goal condition but result in success more often than chance or random option selection.

The Naturalistic Decision-Making (NDM) framework was developed by Klein and colleagues²⁵ to describe the decision-making process of experts during time-sensitive and dynamic situations, and been applied across many domains including sport.^26–30 Research investigating decision-making by experts in dynamic and uncertain environments suggests that decision makers rarely rely on a comparative process between options but rather on making sense of the situation to enable pattern recognition of similar experiences.³¹ This pattern recognition is supported by the mental models of experts.³¹ Mental models refer to the expert's beliefs regarding causal relationships of the world and direct their mental simulations of events to determine the plausibility of a course of action to satisfy the situation.³¹ Mental models of experts are thought to be more sophisticated than novices due to the extensive domain experience associated with expertise which is developed through experience and feedback from similar situations.^31,32 It is therefore, important to understand the processes engaged in by experts to which facilitate this type of decision-making.

Neisser's³³ Perceptual Cycle Model (PCM) has been applied to understand NDM.³⁴ The PCM has three components which include ‘World’ (information available in the environment to make decisions), ‘Schema’ (the cognitive structures and prior experience of the decision-maker), and ‘Action and exploration’ (the potential actions available to the decision-maker including information-seeking to confirm decisions) which interact to select a course of action (see Figure 1.).³² The PCM considers decision-making as a schema driven process whereby schemata direct individual's interaction within the environment (e.g., information seeking), perception, course of action selection, and action.³³ PCM emphasises the critical role of expertise and past experience of similar situations in driving the decision-making process.

Figure 1.

The perceptual cycle model.

Research has investigated the decision-making of coaches across several aspects of their roles.^10,35–37 For example, research has examined the factors and processes associated with a coach's decision to select specific players,³⁵ or how coaches design pedagogy and development opportunities for athletes.^16,38 These decisions are often made under organisational pressure with changing constraints which requires adaptive decision-making, however the decision-making process is supported by prior planning and overarching organisational goals.¹⁷ Decisions such as talent selection provide opportunities for coaches to engage in an analytical decision-making process where options are compared and contrasted to determine the most optimal course of action.

Understanding the decision-making process of expert football coaches during non-routine situations can inform the development of methods and strategies to support and enhance decision-making. Whilst research has examined the decision-making of coaches related to several important components of coaching (e.g., talent identification, team selection, matchday organisation).^10,35–37 there is limited research which examines the processes and factors which influence their decision-making during matches. During matches, coaches are faced with dynamic and non-routine moments and are able to intervene through implementing changes, for example, substitutions, playing styles, and formation changes. These decisions allow the team and players to adapt to and overcome the challenges they face during matches. Therefore, understanding how expert coaches make decisions during time-pressured and dynamic moments is crucial for improving coaches, teams, and subsequently clubs. The aim of this study is to identify factors which influence the decision-making of high-level football coaches during dynamic and uncertain events during matches, through the lens of NDM.

Method

Study design

This qualitative study was designed to investigate the decision-making processes of football coaches during non-routine match scenarios. The work of Klein and Colleagues (1989)³⁹ identified that examining decision-making in dynamic and naturalistic environments had significant barriers, including the inability to access expert decision-makers during decision-making moments. To overcome this issue the application of a cognitive task analysis method, the critical decision method (CDM) will be applied to this study. The CDM is derived from Flanagan's (1954)⁴⁰critical incident technique and is a semi-structured interview technique which aims to elicit the tacit knowledge used by experts when making decisions during time-sensitive and dynamic situations.^39,41 The CDM has been applied to a wide range of domains including sport.²⁹ Whilst, there are known issues associated with recall due to memory alteration and decay.⁴¹ However, the strength of the CDM is that it examines events that have occurred and does not require individuals to respond to artificial situations which do not have the contextual depth faced by decision makers in the real word.³⁹

The CDM was applied to obtain data through one-on-one interviews with football coaches via video conferencing software (Zoom). Two predetermined football match scenarios were used which required coaches to talk though their decision-making process during the interviews based on their recall of similar situations that they had been involved in. The study was approved by the Human Research Ethics Committee of the University of the Sunshine Coast (S211582).

Participants

A purposive sampling approach was used to recruit participants. To be eligible for the study, participants were required to hold a B, A, or Pro qualification from any FIFA confederation (see Table 1). Eleven coaches fitting this criterion volunteered to participate in the study. All participants were male, and most had received their coaching certification through the Asian confederation despite invitations being sent to a diverse range of coaches, from different confederations. Whilst accreditations across confederations are not always recognised, all coaching qualifications require significant coursework and practical experience of coaching, which is why this was considered a measure of coaching expertise. The number of participants was considered adequate when compared to other applications of the CDM.^42–44 The mean age of the participants was 37.7 years (range = 29–57; SD = 8.0). The mean experience of the participants was 15.09 years (range = 6–25; SD = 5.66) Participants were employed in roles including head coaches, assistant coaches, technical directors, Skill Acquisition Phase (SAP) directors, analysts, and coach educator positions.

Materials

A demographic questionnaire was used to obtain relevant information regarding participants and their coaching experience. As recommended by Klein & Armstrong⁴¹ the CDM interview probes were modified to support appropriate data collection in the current context of football. The probes included were derived from Klein and Colleague's³⁶ original work and Blandford & Wong's⁴⁵ probes (see Table 2). The video conferencing software Zoom was used to conduct and record interviews with participants. Microsoft's Word was used to transcribe interviews. The transcribed interviews were analysed using the qualitative analysis software Nvivo 20.

Table 1.

Participant coaching experience and accreditation.

Participant	Accreditation	Gender	Coaching Experience (years)
1	UEFA Pro-Licence	Male	23
2	AFC Pro-Licence	Male	25
3	AFC Pro-Licence	Male	15
4	Pro-Licence*	Male	12
5	Pro-Licence*	Male	10
6	AFC FFA A-Licence	Male	20
7	AFC FFA A-Licence	Male	6
8	AFC FFA A-Licence	Male	15
9	AFC A-Licence	Male	15
10	AFC A-Licence	Male	11
11	UEFA B-Licence	Male	14

Note. AFC: Asian Football Confederation; FFA: Football Federation Australia; UEFA: Union of European Football Associations; *Coaches did not indicate the confederation of their accreditation.

Table 2.

Scenario descriptions.

	Scenario Description
1. Send off	You have a central defender sent off in the early- to mid-stages of a game (prior to halftime or early in the second half)
2. Chasing the game	You are behind in a game in which you need to secure a result (a draw or win) with 15-min to go

Procedure

At the commencement of the interview, participants were given an overview of the study and its aims, following which they were presented with the two scenarios that formed the basis for the CDM interviews (see Table 2).

The two scenarios were designed by the research team based upon their own experiences playing and coaching. The two scenarios were selected as they represent critical in-match incidents which an effective response requires a coach to undertake a decision-making and course of action selection process opposed to inaction or ‘continuing with the plan’. Participants were briefed on the theoretical basis of the study (CDM) and were given an opportunity to ask further questions. Each scenario was explained to participants and they were then asked to think of a specific instance where they had experienced each scenario as a head coach prior to participating in the interview. Once participants had identified a relevant scenario, they participated in a CDM interview with the first author taking the role of interviewer and the participant the interviewee. Due to time constraints, the participants identified the most relevant decision point associated with scenario, opposed to recounting the entire match and identifying all decisions which occurred during the match. The CDM interview was then conducted using four sweeps designed to elicit a deeper understanding of the incident and allow the participant to immerse themselves within the event to determine the processes involved with their decision.

Sweep 1: Incident identification, selection, and elicitation. Prior to the interview participants were asked to select an instance when they were coaching for the two study scenarios. Incidents were assessed for suitability before the interview began proper. Participants were asked to select the main decision related to the scenario presented, such deciding to make a tactical change, or deciding to make a substitution.

Sweep 2: Timeline verification and decision point identification. Participants gave an overview of the matches that were selected to provide context. Participants then explained the main decision that was made related to the scenario. Unlike typical CDM interviews, only a single decision point was examined for each scenario. This procedure was selected to allow for an in-depth investigation of specific decision-points and the factors which influence decision-making.

Sweep 3: Deep probes. A series of cognitive probes were used to elicit information regarding the various cognitive processes and variables that influenced the decision (see Table 3 ).

Table 3.

Critical decision method probes.38,44

Probe Type	Probe Content
Cues	What were you seeing, hearing,…?
Cue identification	What features were you looking at when you formulated your decision? How did you know you needed to make the decision? How did you know when to make the decision?
Knowledge	What information did you use in making this decision, and how was it obtained?
Key info	What were the most important pieces of information related to your decision
Additional info	What would have been useful – what players did the opposition have
Influence of Uncertainty	At any stage, were you uncertain about either the reliability or the relevance of the information that you had available? At any stage, were you uncertain about the appropriateness of the decision?
Analogues	Were you reminded of any previous experience? – did influence your decision-making? How so?
Goals	What were your specific goals at this time? – Did they change?
Options	What other courses of action were considered by or available to you?
Bias	How was this option selected/other options rejected? What strategy was being followed being followed?
Experience	What specific training or experience was necessary or helpful in making this decision?
Basis of Choice	Do you think you could develop a strategy or tactic, based on your experience, which could assist another person to make the same decision successfully? Do you think that anyone else would be able to use this rule successfully? Why/Why not?
Decision Blocking/Stress	Was there any stage during the decision-making process in which you found it difficult to process and integrate the information available? Describe precisely the nature of this situation
Aiding	If the decision was not the best, what training, knowledge, or information could have helped?
Time Pressure	How much time pressure was involved in making this decision?
Hypotheticals	If a key feature of the situation had been different what different would it have made in your decision? – i.e., different score line/player position/already made subs

Note. Probes derived from Klein et al.³⁹ and Blandford & Wong.⁴⁵

Table 4.

Definitions and examples of key findings.

Themes/Sub-Themes	Definition	Example
Schema
Experience or Prior learning	Experiences from coaching, playing or other football related activities of the coaches and learning which occurred during the coaching accreditation courses	“I've chased games as a player and as a manager. Moved Centre-halves up front, that we've gone very direct, squeezed in, got second balls try to play as much in their half as we can so, of course, we were reminded of it” – Coach 1 (Send off)
Mental simulation	The expectancies developed by coaches regarding potential outcomes related to the game state and their potential courses of action	“we thought if we put the winger out there as well, to combine with that fullback now would cause them more problems and tend to start to drag them more out because you'd have to drag more players, into those areas where we want to try and get in behind and then there's less players in the central area”. - Coach 7 (Chasing the game)
Mental models	The mental models held by the coaches related to players, the opposition, the coaches’ own game model	“usually we like to go behind the fullback or wing back, and you know carry into the box and create high X G chances in a good cutback. We just couldn't create those type of chances, we had to deliver a bit earlier, and then the evolution as well we're gonna have to find ways to occupy the box and be a threat in that regard.” – Coach 3 (Chasing the game)
Goals	The goals developed by coaches which directed and supported the decision-making process	“send a message of like an implicit message through instruction that we're going to be able to stabilise here quick. I wanted to act pretty quickly so that the players didn't feel in that freefall space that sometimes can happen when you get a Punch to the nose, so to speak.” – Coach 10 (Send off)

World
Player characteristics	Information regarding the coach's own players including the pace of the players, the workload of players, player emotion, and player reactions	“seeing as in our players, were dejected because they knew that we were in a very difficult place with 70 min to go and they came and we're already a goal down” – Coach 5 (Send off)
Opposition	Information regarding the opposition including players, playing style, reactions to events during the match, and whether the opposition were dominating the game	“because he [opposition player] had the quality once he got ball at his feet in the final third. He was making stuff happen he was having shots on target, he was creating [chances], he was crossing … it was just too much of a threat coming from him once he got the ball.” – Coach 4 (Chasing the game)
Coaching Factors	Information related to the coaches’ experience on matchday, including their emotions, personality and other coaching staff	“Feeling most probably pissed off with the players stupidity, really early in the game I guess adrenaline and whatever” – Coach 2 (Send off)
External Factors	All the information which influenced the match beyond the players involved in the match. Such as field conditions, refereeing, organisational goals and the referee	“Yes, for me [it's instant] and you've got all the hullabaloo and the mayhem and discussions in the background and you can hear them and you can't help your staff and whatever you've people from the crowd going off and do this or what did you do, do that. All the critics and experts.” – Coach 2 (Send off)
Situation Assessment	The combination of several pieces of information which aids in recognising specific game patterns or patterns of play. Key pieces of information included live data or footage, the score line and time	“individual performance being ineffective in terms of creating moments with end products, we were building up really well, we were playing through the opponent. We'd either pass our way through, and then we needed that cross, and the pass in the box was a poor decision made by the player or the player was too slow and got tackled, we've got them in a one-on-one situation and couldn't beat the player nine times out of 10” – Coach 7 (Chasing the game)

Action & Exploration
Emotional Regulation*	The act of calming down after an adverse event or refocusing away from the event to focus on the game	“quick acceptance of the situation move on from the problem in the referees not going to change his mind on the on the second yellow and a red card and it was as quickly as possible, keeping the players on task so it was very much a task based objective for the game” – Coach 9 (Send off)
Communicating to Players	The action of communicating to players during the match	“My message to him as we went on was we continue to play, the way we set out to play us yeah you tell the boys, because you can't yell out and be heard by players so he's going to go on, so we just continue the same we've got Joe blow up front” – coach 2 (Chasing the game)
Options	The potential and actual courses of actions engaged in by coaches during the match	“I could have probably changed maybe a couple personnel, perhaps you can change midfielders it probably could quickly become this inverted wing 433 situation that they are playing a 433 as well, so there it's a bit more like for like” – coach 8 (Chasing the game)
Situation Assessment	The act of scanning and behaviours which facilitate the development of situational assessment during the match	“Watching the game always checking our defensive shape which was my area, making sure that when we went forward, numbers were back relaying that information on, feeling, disappointed because I honestly probably thought that we were going to struggle to get anything out the game” – coach 1 (Chasing the game)
Prior Actions	The preparation and planning engaged in prior to the match	“The players know to, it's something you talk about early in the start of the season, when we lose a man we go into this shape so they know as a player you lost your Centre-back someone's going to drop in quickly they might solve it themselves” – Coach 6 (Send off)

Emotional regulation was identified in the Send off scenario only.

Sweep 4: Hypotheticals. (what if…?). The last sweep included hypotheticals where the participants were encouraged to consider whether or how different circumstances may impact upon the decision under scrutiny.

Data analysis

Following the interviews, the transcripts and audio files were downloaded from Zoom. All transcripts were reviewed and edited while re-watching the recorded interviews in full to ensure accuracy and clarity of the data. Edited transcripts were uploaded to NVivo 12 for coding. The researchers’ epistemological perspective entailed an interpretive approach as the research aimed to understand how and what coaches used to develop an appropriate course of action during dynamic and non-routine events during matches.⁴⁶ Interviews were coded utilising thematic analysis to develop themes based upon the data.⁴⁷ Implementing a method such as thematic analysis allows for flexibility when analysing and interpreting qualitative data.^48,49 The approach to developing themes followed the processes outlined by Braun and Clarke⁴⁷ whilst also being guided by the theoretical underpinnings of the PCM to support the identification of relevant cues, mental strategies and actions utilised by coaches to make decisions during games. Participant dialogue was chunked at each probe and new dialogue began once the next probe was asked by the interviewer this allowed the entire response of the participant to be analysed together. In line with previous research,⁴⁹ within each chunk of dialogue mutliple codes were developed from the responses. Through the coding process themes were developed which were associated with the coaches decision-making. The themes were then applied to the PCM framework and placed within World, Schema, or Exploration and Action (see Table 3 for examples of coded responses). The World aspect of the PCM was characterised as the information available to coaches during the match. Schema referred to both cognitive processes engaged in regarding sense-making of the information obtained in World, alongside the mental models held by coaches related to football. Lastly, Action and Exploration covered specific cognitive and physical behaviours engaged in by the coaches in support of the decision-making process.

Inter-rater reliability

All interviews were coded by one member of the research team. To ensure that coaches’ statements were not misinterpreted a second member of the research team coded 10% of the data, any disagreements regarding the coding were discussed until consensus was achieved.

Results

A total of 21 scenarios (Send off n = 10; Chasing the game n = 11) were examined during 11 CDM interviews. Interviews ranged from 47–135 min in duration (mean 95 min, SD = 25 min). One participant had not experienced the Send off scenario as a coach and was only interviewed for the Chasing the game scenario, which lasted for a duration of 47-min. The interviews involved decisions made from across a range of age levels (youth to senior football) and playing levels (community level to professional and international football).

The participants reported coaching decisions related to player substitutions, formation changes, and changes to style of play. The themes developed from the data were mapped onto the three components of the PCM (World, Schema and, Action and Exploration; see Table 4). The proportion of references coded to the three PCM themes can be seen in Figure 2. Five themes were developed through the analysis which related to the World component. This theme describes the specific cues which participants attended to during matches to develop a course of action. Four subthemes were developed which related to Schema. This theme describes the coaches’ perceptions of the cognitive processes and mental models utilised by coaches during decision-making during matches. Four themes were developed under Action and Exploration for both scenarios. Emotional regulation was only developed within the Send off scenario (see Figure 3). Overall, the analysis developed and identified a wide range of factors which influence the decision-making process of football coaches (see Figures 3 and 4).

Figure 2.

Proportion of references coded to perceptual cycle model. The figure indicates the percentage of references coded to each theme from the PCM across the two scenarios.

Figure 3.

PCM themes for the send off scenario (red card).

Figure 4.

PCM themes for chasing the game.

Discussion

The aim of this study was to identify factors which influence the decision-making of expert football coaches during dynamic and non-routine events during matches, through the perspective of NDM. The current findings produced insights into situations when in-game decision-making process of high-level football coaches are required. The findings suggest that during matches, participants spent their time assessing the match to diagnose and identify relevant cues in the environment. The cues identified were typically combined with mental models to develop an appropriate course of action.

Coaches’ decision-making in dynamic moments

The results identified that participants employed different decision-making strategies when compared across the two scenarios. The red card scenario required participants to restructure the team formation and tactics under high time pressure, limiting the amount of time available to develop a thorough and detailed plan of action. Whereas, in the Chasing the game scenario, the participants reported being afforded more time to implement a course of action around tactical substitutions and formation changes. A key finding was the difference between the proportion of schemata used during the decision-making process across the two scenarios. During the Send off scenario the participants ostensibly utilised a higher proportion of schemata compared to Chasing the game.

The Send off scenario represented a challenging moment given the impact on play, as the team is forced to play with a player less for the reminder of the match.50 In line with NDM theory, the high level of coaching experience and previous experiences in football likely enabled them to select their relevant course of action.⁵¹ This was evident in the higher proportion of the sub codes ‘Mental models’ (i.e., player attributes) and ‘Experiences and prior learning’ (i.e., playing experience, coach education) in the Send off scenario compared to the Chasing the game scenario. One interpretation of this finding regarding rapid decision-making could possibly indicate the presence of pattern-matching decision-making processes in football coaches. Based on the current findings, a recommendation for coaching education could be the inclusion of training for planning for events which force decisions under time constraints for example, red cards or injuries to key players.

Whilst there is an ultimate time pressure in football, as matches last 90-min, in Chasing the game participants typically were able to engage in more perceptual exploration and action to develop a comprehensive course of action. For example, coaches reported identifying relevant cues such as opposition attributes to support the development of a course of action. The findings highlight the role of situational assessment in decision-making, evidenced by the higher proportion of the subcode ‘situation assessment’ in Chasing the game. Similar to previous findings, an initial course of action was generated, however prior to the implementation of this course of action situational assessment continued as a form of diagnosing the situation.⁵² This continual situational assessment allowed participants to potentially alter their pre-selected course of action if new information (i.e., opposition scoring a goal) was obtained.

A unique sub-theme was identified in the Send off scenario that was absent in the Chasing the game scenario ‘emotional regulation’, which referred to the behaviours engaged in by participants to calm down and refocus on the match after their player had been sent off. Whilst this was only referenced three times it has important implications for coaches’ decision-making. Given the impact a red card has on a football match it is likely to evoke negative emotions.⁵⁰ Previous research has found that the emotional salience experienced during a decision point may negatively influence the decision-making process resulting in an undesirable outcome.^5,53 The findings showed that participants experienced a range of negative emotions or emotional states such as helplessness, frustration, disappointment and stress, however the findings indicate that they were cognisant to manage and regulate these negative emotions. This finding has implications for coach education also, as coaches must first be able to recognise the presence of these negative emotions and secondly, regulate the emotions quickly to refocus on the match.

The current findings appear consistent with previous NDM research in sport. There are several implications that should be explored related to the current results. The Send off scenario emphasised the importance of schemata and previous experience, therefore, coaches need to be exposed to large quantities of football activity to support the development of appropriate schemata for critical scenarios. This may be achieved through scenario-based training,⁵⁴ or simulation which is being used in sport to improve decision-making of athletes.⁵⁵ The findings of the Chasing the game scenario also have implications regarding training for improving the skills involved in situation assessment and the ability to alter potential courses of action. For example, the cues reported by participants in the present study could form a template outlining what cues coaches should look for when faced with the task of Chasing a game. Whilst differences emerged between the scenarios, it is important to consider the similarities between scenarios. Many factors were consistent across both scenarios. These findings merit comment regarding their implications for decision-making in dynamic contexts.

Participants reported attending to different types of cues across scenarios for example attention was typically directed at the opposition during the Send off scenario. Whereas when Chasing a game attention was directed at their own players. The participants reported that prior to a red card, their teams were typically struggling in the match which would activate an expectancy of the situation. A possible explanation for this finding is the influence of schemata on attention during these dynamic decision points.³³ Previous research suggests schemata allows decision-makers to engage in a top-down process to identify relevant cues.³⁴

A key component of NDM is the development of schemata which produces appropriate expectancies.³¹ The current analysis identified evidence of coaches’ use of expectancies to develop a course of action. Participants reported analysing the situation, for example, how the opposition defence were playing and applied various schemata to assess the workability of a course of action. This process may be explained by the process of PCM wherein world information activates schemata as a decision-making process.⁵⁶ This integration of information with schemata is a key skill required for decision-making in dynamic contexts such as sport.⁵⁷ This finding further supports the notion of the importance of well-developed schemata and its role in decision-making in dynamic contexts.

Impediments to decision-making

The participants possessed expertise within football coaching which may allow for quick and appropriate decision-making in matches. However, several factors were reported as impeding this process. Participants reported previously having access to live data or footage to assist in decision-making, for example, when live data such as field positions or video replays were unavailable this was viewed as a hinderance to their decision-making process. Previous research in business,⁵⁸ firefighting⁵⁹ and the military⁶⁰ has emphasised the role of accurate mental models and appropriate decision-making.⁵¹ The findings from the present study indicate that coaches could develop erroneous models based upon misinformed analysis. Participants reported engaging in comprehensive analysis of the opposition which typically influenced the training goals of that week. However, when inaccurate information was used, inappropriate expectancies were developed. This finding is consistent with previous research which shows the hampering effect of incongruent information.^57,61 In the current study, to minimise the impact of a lack of opposition information, participants reported an emphasis on understanding their own style of play (i.e., game model, player abilities or attributes). These schemata of game models and player abilities or attributes would direct decision-making during the match. This has implications regarding the way coaches can prepare for matches, particularly regarding the amateur level where high-level and accurate data is unavailable for preparation for the game.

Strengths and limitations

The present study had limitations which should be considered. Firstly, the sample was homogenous with only male coaches (despite invitations to female coaches to participate), and seven receiving their coaching accreditation from the same regional confederation (Asian football confederation). Secondly, the adaptation of the CDM interviews did not allow for all of the decision points which occurred during the matches to be analysed and therefore the analysis did not examine the impact of the decision on the match. Whilst the sample lacked coaches across confederations, the participants held the top three qualifications available to coaches in football, indicating their expertise. The moments the coaches identified were not temporally constrained and thus coaches were able to select instances from any time in their coaching experience. Further, whilst the sample lacked gender diversity, future research investigating the decision-making of football coaches should include female coaches. The current study was strengthened through its application of the NDM methods and models to an under-researched area in sports coaching.

Future directions

Future investigations could implement the use of CDM directly after or during matches via concurrent verbal protocols to enhance the naturalistic aspect of the work. Given the small and homogenous sample of the current study, future research in this area should include a larger sample size with greater diversity regarding gender, and level of competition (e.g., youth through to professional). The findings around the importance of schemata also suggest that future research could look to compare the differences between high-level and amateur coaches and experienced and inexperienced coaches to assess the differences in the decision-making process. As football continues to evolve with the integration of live data available to coaches on matchday, further research should consider the implications of such technology on the decision-making of actors particularly coaches during matches. Additionally, the methodology could be applied to a broader range of sports to determine similarities and differences related to the in-game decision-making of coaches. For example, do invasion style sports (e.g., football, rugby, basketball) differ to bat-and-ball sports (e.g., cricket, baseball) regarding the decision-making process of coaches during matches.

Conclusion

This study applied NDM methods and models to the decision-making of high-level football coaches. The study identified a number of factors which influenced the decision-making process of football coaches. First, in high time pressure situations, i.e., a red card, participants relied on mental models and schemata to guide decision making. In contrast, in situations where time pressure was reduced, i.e., Chasing a game, participants used information from the match to assess the situation prior to selecting a course of action. This study provided unique insights into the decision-making of coaches during the dynamic non-routine moments during a match. High-level coaches were able to construct mental models of important game related information and apply information from different modalities to support decision-making. Further research is required to understand the numerous other aspects of decision-making of football coaches during a match, particularly related to the increasing technology insertion in sport.

Footnotes

Acknowledgements

The Authors wish to thank all the participants who volunteered to participate in the study.

ORCID iDs

Isaiah Elstak

Scott McLean

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Ashford

Abraham

Poolton

. What cognitive mechanism, when, where, and why? Exploring the decision making of university and professional rugby union players during competitive matches. Front Psychol 2021; 12: 609127.

Lyle

. Coaches’ decision making: a naturalistic decision making analysis. In: Lyle

Cushion

(eds) Sports coaching: professionalisation and practice. 1st ed. London: Churchill Livingstone, 2010, pp.27–41.

Arrow

. Economic theory and the hypothesis of rationality. In: Eatwell

Milgate

Newman

(eds) Utility and probability. 1st ed. London: Palgrave Macmillan, 1990, pp.25–37.

Baker

Bridges

Hunter

, et al. Guidebook to decision-making methods. Report, Department of Energy, USA, December 2001.

Laborde

Raab

. The tale of hearts and reason: the influence of mood on decision making. J Sport Exerc Psychol 2013; 35: 339–357.

Raab

Bar-Eli

Plessner

, et al. The past, present and future of research on judgment and decision making in sport. Psychol Sport Exerc 2019; 42: 25–32.

Inns

Petancevski

Novak

, et al. Decision-making assessments in youth team invasion game athletes: a systematic scoping review. Int J Sports Sci Coach 2023; 18: 2360–2381.

Samuel

Galily

Guy

, et al. A decision-making simulator for soccer referees. Int J Sports Sci Coach 2019; 14: 480–489.

Forcher

Jekauc

, et al. How coaches can improve their teams’ match performance—the influence of in-game changes of tactical formation in professional soccer. Front Psychol 2022; 13: 914915.

10.

Almeida

Sarmento

Kelly

, et al. Coach decision-making in futsal: from preparation to competition. Int J Perform Anal Sport 2019; 19: 711–723.

11.

Debanne

Angel

Fontayne

. Decision-making during games by professional handball coaches using regulatory focus theory. J Appl Sport Psychol 2014; 26: 111–124.

12.

Giske

Benestad

Haraldstad

, et al. Decision-making styles among Norwegian soccer coaches: an analysis of decision-making style in relation to elite and non-elite coaching and level of playing history. Int J Sports Sci Coach 2013; 8: 689–702.

13.

Abraham

Collins

Martindale

. The coaching schematic: validation through expert coach consensus. J Sports Sci 2006; 24: 549–564.

14.

Abraham

Collins

. Taking the next step: ways forward for coaching science. Quest (National Association for Kinesiology in Higher Education) 2011; 63: 366–384.

15.

Lyle

Muir

. Coaches’ decision-making. In: Schinke

Schack

Papaioannou

(eds) The routledge international encyclopedia of sport and exercise psychology. 1st ed. Milton Park: Routledge, 2020, pp.135–153.

16.

Collins

Taylor

Ashford

, et al.

It depends coaching–the most fundamental, simple and complex principle or a mere copout?

Sports Coach Rev 2022; 12: 1–21.

17.

Collins

. The foci of in-action professional judgement and decision-making in high-level adventure sports coaching practice. J Advent Educ Outdoor Learn 2017; 17: 122–132.

18.

Mees

Sinfield

Collins

, et al.

Adaptive expertise–a characteristic of expertise in outdoor instructors?

Phys Educ Sport Pedagogy 2020; 25: 423–438.

19.

Abraham

Collins

. Thinking (too?) fast and slow: an example of professional judgement and decision making processes in athletics. Int J Sports Sci Coach 2024; 20: 1–13.

20.

Simon

. A behavioral model of rational choice. Q J Econ 1955; 69: 99–118.

21.

Simon

. Bounded rationality. In: Eatwell

Milgate

Newman

(eds) Utility and probability. 1st ed. London: Palgrave Macmillan, 1990, pp.15–18.

22.

Tversky

Kahneman

. Judgment under uncertainty: heuristics and biases. Sci 1974; 185: 1124–1131.

23.

Klein

Calderwood

Clinton-Cirocco

Rapid decision making on the fire ground: the original study plus a postscript. J Cogn Eng Decis Mak 2010; 4: 186–209.

24.

Dale

. Heuristics and biases: the science of decision-making. Bus Inf Rev 2015; 32: 93–99.

25.

Yung

Ardern

Serpiello

, et al. Judgement and decision making in clinical and return-to-sports decision making: a narrative review. Sports Med (Auckland) 2024; 54: 2005–2017.

26.

Bossard

Kérivel

Dugény

, et al.

Naturalistic decision-making in sport: how current advances into recognition primed decision model offer insights for future research in sport settings?

Front Psychol 2022; 13: 936140.

27.

Johnston

Morrison

. The application of naturalistic decision-making techniques to explore cue use in rugby league playmakers. J Cogn Eng Decis Mak 2016; 10: 391–410.

28.

Kermarrec

Bossard

. Defensive soccer players’ decision making: a naturalistic study. J Cogn Eng Decis Mak 2014; 8: 187–199.

29.

Macquet

. Recognition within the decision-making process: a case study from expert volleyball players. J Appl Sport Psychol 2009; 21: 64–79.

30.

Neville

Salmon

Read

. Analysis of in-game communication as an indicator of recognition primed decision making in elite Australian rules football umpires. J Cogn Eng Decis Mak 2017; 11: 81–96.

31.

Klein

. A naturalistic decision making perspective on studying intuitive decision making. J Appl Res Mem Cogn 2015; 4: 164–168.

32.

Klein

. Naturalistic decision making. Hum Factors 2008; 50: 456–460.

33.

Neisser

. Cognition and reality. 1st ed. San Francisco: W.H.Freeman and Co Ltd, 1976.

34.

Plant

Stanton

. What is on your mind? Using the perceptual cycle model and critical decision method to understand the decision-making process in the cockpit. Ergonomics 2013; 56: 1232–1250.

35.

Hill

Sotiriadou

. Coach decision-making and the relative age effect on talent selection in football. Eur Sport Manage Q 2016; 16: 292–315.

36.

Aarons

Vickery

Bruce

, et al. A framework to explain the in-match decision-making of elite Australian football coaches. Psychol Sport Exerc 2023; 67: 102439.

37.

Fiander

Stebbings

Coulson

, et al. The information coaches use to make team selection decisions: a scoping review and future recommendations. Sports Coach Rev 2023; 12: 187–208.

38.

Collins

Carson

Collins

. Metacognition and professional judgment and decision making in coaching: importance, application and evaluation. Int Sport Coach J 2016; 3: 355–361.

39.

Klein

Calderwood

MacGregor

. Critical decision method for eliciting knowledge. IEEE Trans Syst Man Cybern Syst 1989; 19: 462–472.

40.

Flanagan

. The critical incident technique. Psychol Bull 1954; 51: 327–358.

41.

Klein

Armstrong

. Critical decision method. In: Stanton

Hedge

Brookhuis

, et al. (eds) Handbook of human factors and ergonomics methods. 1st ed. Boca Raton: CRC Press, 2005, pp.373–382.

42.

Popov

Harmer

Raphael

, et al. Elucidating cognitive processes in cardiac arrest team leaders: a virtual reality-based cued-recall study of experts and novices. Ann Med (Helsinki) 2025; 57: 2470976.

43.

Foster

Plant

McIlroy

. The never-ending nightshift: insights into organisational adaptation during COVID-19. Saf Sci 2025; 184: 106740.

44.

Schnittker

Marshall

Horberry

, et al. Human factors enablers and barriers for successful airway management – an in-depth interview study. Anaesthesia 2018; 73: 980–989.

45.

Blandford

Wong

. Situation awareness in emergency medical dispatch. Int J Hum Comput Stud 2004; 61: 421–452.

46.

Wiesner

. Doing qualitative and interpretative research: reflecting principles and principled challenges. Pol Res Exch 2022; 4: 2127372.

47.

Braun

Clarke

. Using thematic analysis in psychology. Qual Res Psychol 2006; 3: 77–101.

48.

Braun

Clarke

Gray

. Collecting qualitative data: A practical guide to textual, media and virtual techniques. 1st ed. Cambridge: Cambridge University Press, 2017.

49.

Braun

Clarke

. Reflecting on reflexive thematic analysis. Qual Res Sport Exerc Health 2019; 11: 589–597.

50.

Liu

Gomez

MÁ

Lago-Peñas

, et al. Match statistics related to winning in the group stage of 2014 Brazil FIFA world cup. J Sports Sci 2015; 33: 1205–1213.

51.

Lipshitz

Shaul

. Schemata and mental models in recognition-primed decision making. In: Zsambok

Klein

(eds) Naturalistic decision making. 1st ed. New Jersey: Lawrence Erlbaum Associates, Inc, 1997, pp.313–324.

52.

Menn

Bossard

Travassos

, et al. Handball goalkeeper intuitive decision-making: a naturalistic case study. J Hum Kinet 2019; 701: 297–308.

53.

Helsloot

Groenendaal

. Naturalistic decision making in forensic science: toward a better understanding of decision making by forensic team leaders. J Forensic Sci 2011; 56: 890–897.

54.

Yates

Tschirhart

. Decision-Making expertise. In: Erisson

Charness

Feltovich

, et al. (eds) Expertise and expert performance. 1st ed. Cambridge: Cambridge University Press, 2006, pp.421–438.

55.

Yunchao

Mengyao

Xingman

. Application of virtual simulation technology in sports decision training: a systematic review. Front Psychol 2023; 14: 116117.

56.

Plant

Stanton

. The process of processing: exploring the validity of Neisser's perceptual cycle model with accounts from critical decision-making in the cockpit. Ergonomics 2015; 58: 909–923.

57.

Gredin

Bishop

Broadbent

, et al. Experts integrate explicit contextual priors and environmental information to improve anticipation efficiency. J Exp Psychol Appl 2018; 24: 509–520.

58.

Gary

Wood

. Mental models, decision rules, and performance heterogeneity. Strateg Manag J 2011; 32: 569–594.

59.

Okechukwu Okoli

Weller

Watt

Eliciting experts’ knowledge in emergency response organizations. Int J Emerg Serv 2014; 3: 118–130.

60.

Kaempf

Klein

Thordsen

, et al. Decision making in complex naval command-and-control environments. Hum Factors 1996; 38: 220–231.

61.

Klatt

Smeeton

. Visual and auditory information during decision making in sport. J Sport Exerc Psychol 2019; 42: 1–25.