Flow in Sports and Exercise: A Historical Overview

Abstract

Originally, Csikszentmihalyi studied activities such as rock climbing, playing chess, composing music, modern dancing, playing basketball or conducting a surgery. Csikszentmihalyi’s interest was to determine, why people pursue these activities even though they might offer little, if any extrinsic rewards. He claimed that if we better understood, what makes us put a lot of effort into something that is seemingly lacking an extrinsic reward, then it may help us be less dependent on extrinsic rewards (cf. Engeser, Schiepe-Tiska & Peifer, Chap. 1). Competitive sports, as well as physical exercise (in terms of prevention) are often linked to extrinsic rewards (e.g. performance & money in competitive sports, or gaining and stabilizing health in prevention settings). Nevertheless, there are a lot of sports activities, which can’t be explained with extrinsic rewards, such as marathon-running as a hobby. Since the early 1990s, flow-experiences were often in the focus of sports- and exercise psychology. The aim of this chapter is to describe the historical development of flow research in sports and exercise settings and furthermore methodological as well as theoretical advances (e.g. neuro-cognitive aspects) related to sports and exercise will be reported and discussed.

Full text

Chapter 13
Flow in Sports and Exercise – a Historical
Overview
Oliver Stoll & Michele Ufer
Abstract. Originally, Csikszentmihalyi studied activities such as rock climbing,
playing chess, composing music, modern dancing, playing basketball or conducting a
surgery. Csikszentmihalyi’s interest was to determine, why people pursue these
activities even though they might offer little, if any extrinsic rewards. He claimed that
if we better understood, what makes us put a lot of effort into something that is
seemingly lacking an extrinsic reward, then it may help us be less dependent on
extrinsic rewards (cf. Engeser, Schiepe-Tiska & Peifer, Chapter 1). Competitive
sports, as well as physical exercise (in terms of prevention) are often linked to
extrinsic rewards (e.g. performance & money in competitive sports, or gaining and
stabilizing health in prevention settings). Nevertheless, there are a lot of sports
activities, which can`t be explained with extrinsic rewards, such as marathon-running
as a hobby. Since the early 1990´s, flow-experiences were often in the focus of sports-
and exercise psychology. The aim of this chapter is to describe the historical
development of flow research in sports and exercise settings and furthermore
methodological as well as theoretical advances (e.g. neuro-cognitive aspects) related to
sports and exercise will be reported and discussed.
____________________
Oliver Stoll (*), Michele Ufer
Institute of Sports Science, Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany
e-mail: oliver.stoll@sport.uni-halle.de, mail@michele-ufer.de
C. Peifer & S. Engeser (eds.), Advances in Flow Research, 2nd Edition
© Springer Science+Business Media, LLC 2020

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Introduction: Flow in performance sports
Flow is a mental state where athletes have a laser-like focus up to being completely
absorbed in the activity. Attention and performance seem to happen effortless and
spontaneous, like on autopilot, without any distracting or negative thoughts at hand,
thus flow is considered a highly functional state that underlies superior performance in
sport (Jackson & Roberts, 1992). Due to its links with peak performance, and
psychological concepts, such as positive subjective experience (Csikszentmihalyi,
1975, 2002), enhanced well-being (Haworth, 1993) and self-concept (Jackson,
Thomas, Marsh & Smethurst, 2001) it is of great interest for athletes of all levels,
coaches and researchers to understand the concept of flow and to know how athletes
can experience this highly desirable state more often and intensely (Jackman, Crust &
Swann, 2017).
While climbers and basketball players were included in Csikszentmihalyi’s original
work (1975), the first empirical studies that explicitly adopted flow research into sport
were published in 1992 (Jackson, 1992, Jackson & Roberts, 1992, Kimiecik & Stein,
1992). Since then numerous studies have been conducted in all kind of sport settings,
while “elite athletes have been the population of primary interest” (Jackson &
Kimiecik, 2008a, p. 385). For two reasons this is not surprising. In elite sport, athletes
compete at the highest level. They may face intense pressure and important rewards
are at stake. Even small improvements in high performance settings can have dramatic
impacts on the outcome in terms of success or failure (Nicholls, Polman & Holt,
2005). So knowledge about mental states that underlie and influence peak performance
is crucial. In addition, the “elite level also represents the domain from which most can
be learned from an applied perspective” (Swann, Piggot, Keegan, Crust, Smith et al.,
2012., p. 808). It seems more likely that athletes with a lower performance level learn
from elite athletes than vice versa.
Based on the systematic review on flow research in elite sport conducted by Swann,
Keegan, Piggot, Crust, Smith et al. (2012) and some more recently published studies
the following section describes how athletes experience flow, what key factors
facilitate, disrupt or prevent the occurrence of flow , how flow can be controlled and
manipulated and how flow influences performance in sport.
Part 1: The experience of flow in sports
The current description of flow generally suggests nine dimensions to describe the
phenomenon (Csikszentmihalyi, 2002, Jackson & Csikszentmihalyi, 1999, cf. Engeser,
Schiepe-Tiska & Peifer, Chapter 1). Three of these dimensions are proposed to be the
preconditions through which flow occurs: challenge-skill balance, clear goals, and
unambiguous feedback. The remaining six dimensions are supposed to be the

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characteristics of flow, describing the subjective experience during flow: concentration
on the task at hand, action-awareness merging, loss of self-consciousness, sense of
control, transformation of time, autotelic experience (e.g. Nakamura &
Csikszentmihalyi, 2002). This conceptualization has been widely supported by
qualitative and quantitative research in the field of sport (e.g. Aherne, Moran &
Lonsdale, 2011, Chavez, 2008, Jackson, 1996, Stavrou, Jackson, Zervas &
Karterliotis, 2007, Swann, Crust, Keegan, Piggot & Hemmings, 2015). However, in
some studies athletes have reported concepts that go beyond Csikszentmihalyi’s
dimensions of flow, e.g. Jackson’s (1996) and Sugiyama & Inomata’s (2005) athletes
mentioned the following aspects: aware of effort, feel out of body, as if watching self,
endless supply of energy. Elite golfer reported a kind of (self-)awareness of being in a
flow state while it occurred (Swann, Piggot, Crust, Keegan, & Hemmings, 2015).
Researchers should consider the possibility that the original flow model based on
nine dimensions may not represent exhaustively flow experience in sports and thus be
open for refinements and adjustments of the original flow model. Swann (2016)
suggests that at least an additional dimension accounting for kinesthetic perceptions of
flow experience seems evident (Swann, 2016).
The demand for a further investigation into refining the concept of flow experience
in sport is strongly supported by recent findings. Swann, Crust and Vella (2017c)
raised concerns about existing knowledge on flow in sports. They found that during
superior performance flow or a second, overlapping but different “clutch state” can be
experienced. The latter happens in moments, when competitive athletes experience
and are fully aware of high pressure but anyway perform at their best through skilled
actions (Jackman, Crust & Swann, 2017). Theses clutch states are considered to
underlie “clutch performance”, defined as “any performance increment or superior
performance that occurs under pressure circumstances” (Otten, 2009, p. 584). Flow
and clutch states share several aspects, like absorption, altered perceptions, enjoyment,
perceived control, but they also differ in various dimensions: intense effort instead of
effortless experience, and deliberate focus instead of effortless attention (see Tab. 1).
Tab. 1: Flow vs. Clutch States
Flow
Clutch
Shared characteristics
Absorption
Absorption
Altered perceptions
Altered perceptions
Enjoyment
Enjoyment
Perceived control
Perceived control
Differences
Effortless experience
Intense effort
Effortless attention
Deliberate focus

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Flow occurrence
Based on their in-depth review of flow studies in elite sport Swann et al. (2012)
found ten factors, which are associated with the occurrence of flow in sport. The
combination and interaction of the following internal states, external influences, and
behaviors facilitate the occurrence of flow: focus, preparation, motivation, arousal,
thoughts and emotions, confidence, environmental and situational conditions,
feedback, performance, team play and interaction. Depending on whether these factors
occur prior or during a performance, they can facilitate, prevent or disrupt the flow
experience. If these factors appear in their negative form, they prevent flow, if they
appear during flow they are likely to interrupt the experience. It is not yet clear what
exactly makes each of these factors negative, nor what level or intensity of a facilitator
(e.g. of arousal) is needed to promote flow, which can be seen in line with Hanin’s
(1997) concept of individual zones of optimal functioning. Also it appears that not
every aspect is experienced during every flow state and it is not clear why a certain
factor is experienced in one flow state but not in another one (Swann et. al., 2012).
Surprisingly the three dimensions that are considered preconditions for flow
(challenge-skill balance, clear goals, and unambiguous feedback) were not reported as
flow facilitators by elite athletes. Possibly, these were just taken for granted in high
performance settings (Swann et al., 2012). While the ten influencing factors seem
rather general in nature and apply to many sports, some sport specific facilitators have
also been found. In a study with jockeys, Jackman, VanHout, Lane and Fitzpatrick
(2015) found that an optimal relationship between horse and jockey and a positive
horse demeanor and performance promote flow. Swann, Piggot, Crust, Keegan and
Hemmings (2015) found that in elite golf the caddie has an important influence on the
occurrence of an athlete’s flow.
While situational factors influencing the occurrence of flow have been extensively
researched, to date individual differences have widely been neglected or were used for
vast explanation of inconsistent data (Swann et al., 2012). But due to the fact that flow
is a subjective state, it is of vital importance to understand how individual differences
affect the occurrence and experience of flow. A couple of studies addressed this issue,
though. Canham and Wiley (2003) found that expert rock climbers were more likely to
experience flow dimensions, such as automatic performance, unambiguous feedback,
clear goals, and time transformation than novel climbers. Catley and Duda (1997)
report a positive correlation of skill level and flow in golf, which is in line with
Engeser and Rheinberg’s (2008) general assumption that “it is likely that individuals
with higher abilities have higher flow values” (p. 161). Due to the fact that elite
athletes regularly experience and have to cope with highly challenging and
competitive situations they may also develop exceptional mental skills during their

5
career, that facilitate flow (Jackson, 1996). This assumption is supported by Crust and
Swann (2013) who report an association of dispositional flow and mental toughness
and Jackson et al. (2001) who found positive associations between flow and the use of
psychological skills such as emotion and thought control, as well as maintaining an
optimal arousal level through adequate activation or relaxation. In addition flow was
shown to be correlated with the level of perceived ability (Jackson & Roberts, 1992)
and athletes with a low level of anxiety and a positive attitude towards one’s own
emotion were more likely to experience flow (Wiggins & Freeman, 2000).
So far, the current findings (e.g. the summary in Wagner & Keller, Chapter 3) are
mainly descriptive in nature and cannot offer causal explanations for flow occurrence.
Kimiecik and Stein (1992) note that “It is one thing to know, for example, that a flow
experience is accompanied by focused concentration, feelings of control, and clear
goals. It is quite another to know why or how the flow experience actually occurred…
(and) the mechanisms underlying the experience” (p.148). Despite all progress that has
been made “there is a degree of uncertainty as to when flow states occur” (Chavez,
2008, p.71). That’s why Swann (2016) highly recommends moving from describing
the factors (e.g. internal states, external influences, behaviors, skills, personality traits)
that are associated with the occurrence of flow to causal explanations how exactly
these factors influence flow occurrence and what mechanisms and processes lead to
flow experience in sport.
Attentional aspects are repeatedly suggested as crucial in order to get into a flow
state (e.g. Pates, Cummings & Maynard, 2002; Singer, 2002, cf. Wagner & Keller,
Chapter 3). While Jackson’s (1992) athletes report focus as very important to find
flow, Swann et al. (2012) also found concentration on the task at hand and action-
awareness merging to be the most reported aspects. Harris, Vine and Wilson (2017)
conclude that the best approach to understand the mechanisms underlying flow
experience in sport and to advance theoretical models is to focus on attentional
processes. But to date theoretical explanations are at an initial stage and empirical
findings are rare (cf. Wagner & Keller, Chapter 3), mainly from outside sport and they
are contradictory. E.g. Dietrich & Stoll (2010) argue that prolonged physical activity,
like long-distance running, leads to a temporal reduction of activity in the prefrontal
cortex (hypofrontality) which accounts for central flow characteristics, such as
effortless attention, time distortion, action-awareness merging. On the other hand, in a
study with runners using electroenzephalography, Wollseiffen et al. (2016)
demonstrated hypofrontality with increasing activity, but this did not correlate with
flow. Based on findings using functional near-infrared spectroscopy (fNIRS) Harmat,
deManzano, Theorell, Högman, Fischer and Ullén (2015) argue that a general
mechanism of hypofrontality to explain flow may be too simplistic, because in their
study no hypofrontality during flow was found. Nevertheless it seems that higher-
order attentional networks play an important role and flow is associated to reduced
activity of those neural networks that are linked to self-referential processing (Harris et

6
al., 2017), so that future explanations focusing on attentional processes seem
promising to explain flow occurrence and its underlying mechanisms.
Controllability of flow in sports
The aim of research concerning the controllability of flow is to raise understanding
if and how the frequency and intensity of flow experience can be systematically
increased. In a couple of studies scientists asked elite athletes about their perceived
control over flow and over the factors that influence the occurrence of flow (e.g.
Chavez, 2008, Jackson 1992, 1995, Sugiyama & Inomata, 2005). Aherne et al., 2011
sees Flow-experiences in sport as illusive and unpredictable (Aherne et al., 2011),
because it still cannot be predicted when exactely, for how long and how deep an
athlete enters a flow state, 66% of the elite athletes perceive flow to be within their
control, whereas 26,5% of the athletes find flow to be difficult or impossible to
control. 81% of the participants think they are able to restore flow after a disruption
(see Swann et al. 2012 for an overview), and elite golfer report that they are able to
prolong their flow experience through the use of positive distractions or the
dissociation from the task (Swann, 2016). However, findings remain unclear. They are
based on limited data and are somewhat contradictory, as some influencing factors, e.
g. concentration, optimal arousal, positive/negative attitude, motivation, are perceived
both controllable and uncontrollable, depending on the athlete. This again clearly
indicates that more research on the role of individual differences underlying flow
experience is needed. And even if some facilitators were more consistently perceived
as controllable, Swann et. al. (2012) points out that “just because these factors are
perceived to be controllable as well as related to flow does not mean that they cause
flow to occur, or guarantee its occurrence” (p. 816) and concludes that we first need to
get a detailed understanding of the mechanisms of flow occurrence and in a next step
can test how factors that seem to be within the control of an athlete can enhance flow.
Some studies investigated, if flow experience can be systematically enhanced
through psychological interventions, e.g. hypnosis (Lindsay, Maynard & Thomas,
2005), imagery (Nicholls et al., 2005), a combination of pre-competition imagery and
music (Pain, Harwood & Anderson, 2011) or a six-week mindfulness training (Aherne
et al., 2011). But the results were somewhat mixed. Again, from our position, a key
challenge seems to be that so far no sound explanation exists of how flow occurs, so
that at this point “interventions are, by necessity, quite speculative” (Swann et al.,
2012). Another reason for the somewhat mixed results could be the fact that the
interventions did not refer to those dimensions and factors that research so far has
found to be associated with flow occurrence. Future studies should take these
arguments into account and develop intervention settings that match the athlete’s
personality and include facilitating aspects or skills like preparation, focus on the task,
manipulation of arousal and goal-setting.

7
These recommendations are strongly supported by findings on goal-setting strategy
as potential causal mechanism of flow experience. While specific goals focus on
objective and measurable outcomes, open goals are rather exploratory, e. g. “see how
well I can do”. Setting specific goals is considered best practice to enhance
performance (Locke & Lathan, 2013, Maitland & Gervis, 2010). Recent qualitative
studies revealed that the type of goal pursued seems to influence whether flow or
clutch states occur. Athletes reported that open goals preceded flow, while specific
goals precede more effortful clutch states (Swann et al., 2017b). Schweickle, Groves,
Vella and Swann (2017) confirmed that the type of goals an athlete pursues appears to
influence the occurrence of flow. In an experimental setting, participants were
assigned to one of three goal condition (specific, open, do-your-best goals) and had to
perform a cognitive task. Those athletes who pursued open or do-your-best goals
reported significantly higher levels of flow than those athletes prescribed specific
goals, who in turn, reported significantly higher level of clutch state. The findings
seem to confirm that the type of goal-setting in advance of a task has an impact of
flow occurrence in the way that open goals may be a reliable intervention to induce or
achieve higher levels of flow.
Flow and performance in sports
Given the key characteristics of flow, e.g. strong focus on the task with a high level
of control and effortless, intuitive action, since the beginning of flow research, flow is
considered a highly functional state that is very likely to have a positive impact on
performance. Also an indirect effect of flow on performance is likely. Flow is
generally perceived as a positive experience. This leads to an increased motivation to
practice, which results in a better performance. However, the empirical findings in
sports are mixed. Some researchers found positive links of flow with performance,
some didn’t.
A key element in performance sport is for athletes to achieve peak performance,
whether it is winning a competition, beating an opponent, finishing an extremely
challenging event or achieving a personal best. While flow research has been mainly
focused on the characteristics of flow and its antecedents, surprisingly only little
investigations have been undertaken to analyze the effects of flow on performance in
sport. From the beginning flow theory has assumed a positive relationship between
flow and performance, and there are good reasons for this assumption. Given the key
characteristics of flow, e.g. strong focus on the task with a high level of control and
effortless, intuitive action, flow can be considered a highly functional state that is very
likely to have a positive impact on performance. This view is supported by Eklund
(1994, 1996) and Williams & Krane (1997), who consider the mentioned flow
characteristics to be significant drivers of performance in sports. Privette (1981) also

8
concludes in her work on excellence in sports that flow experience should have a
positive impact on performance, because "Csikszentmihalyi's term 'flow' [...] is an
elegant fit for the whole, graceful, and directed behavior athletes described as
characteristic of peak performance in sports" (p. 55). In addition to this direct impact
of flow on performance, also an indirect influence is shown (Schüler & Brunner,
2009). Flow is usually experienced as very pleasant. This can act as an incentive,
increasing the motivation to practice in order to experience flow again. The increased
practice leads to increased training effects which in turn enhances performance.
While from a theoretical point of view there are many reasons, for flow to have a
direct positive effect on performance, so far the empirical findings in sports do not
show a clear picture. Some researchers found positive links of flow with performance
(e.g. Jackson et al., 2001, Jackson & Roberts, 1992, Stavrou et al., 2007, Swann et al,
2017a). However, this contrasts with work in which the postulated direct relationships
between flow and performance could not be confirmed (e.g. Schüler & Brunner, 2009,
Stoll & Lau, 2005), although in the field of long-distance running Schüler and Brunner
(2009) found an indirect effect of flow on performance: flow during a marathon race
had a positive effect on the future motivation to run. An increase in training time was
related to a better performance during future competitions. In a recent study on the
effects of goal types on flow and clutch states, Schweickle et al. (2017) found that
participants scoring high on clutch state performed significantly better than those who
scored high on flow, who, however, reported a higher perceived performance despite
objectively performing worse.
Stoll and Lau (2005) see the reasons for the inconsistent findings in the fact that the
available studies are very heterogeneous. The theoretical foundations are not always
clear and problematic in terms of research methodology (small samples, problematic
operationalization of flow and performance. Henk (2014) shares this point of view and
explains that the flow measurements were carried out very differently. Sometimes
flow assessments took place during or immediately after an event, sometimes years
after a certain performance. Sometimes psychometric scales were used, sometimes
career-based or event-related interviews. Performance was measured either on the
basis of objective data, e.g. rankings or finish times, or based on individual pre-
competition expectations or through subjective post-event assessments (e.g. referring
to a performance which an athlete remembered better than average).
It is highly recommended to further investigate the effects of flow on performance.
But performance is not the final criterion in sports. As we have shown before, flow is a
positive experience associated with well-being and confidence but also able to
motivate people to exercise further. These are important findings we can use in the
field of leisure, health and prevention sports.
Part 2: Flow in primary and secondary prevention settings

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A current research question in health psychology is how to motivate individuals to
maintain exercise behaviour in order to gain the beneficial health effects connected to
long-term exercising in primary or secondary prevention settings. Preventive
healthcare strategies are described as taking place at the, primary, secondary, and
tertiary prevention levels. Primary prevention summarizes methods to avoid
occurrence of disease either through eliminating disease agents or increasing
resistance to disease. Examples include immunization against disease, maintaining a
healthy diet and exercise regimen, and avoiding smoking. Our main focus in this
section is the especially the question of maintaining of an exercise regimen and its
relation to the occurrence of flow. Secondary prevention summarizes methods to
detect and address an existing disease prior to the appearance of symptoms. An
example includes e.g. the treatment of hypertension with e.g. sports-therapy, but also
with regard to psychosomatic problems. In primary prevention settings, flow-
experiences are rarely reported or discussed.
Elbe, Strahler, Krustrup, Wikman & Stelter (2010) explored whether inactive
individuals (in comparison to active individuals) can experience flow, a rewarding,
psychological state, during an exercise intervention and if there are differences
according to the type of intervention they experienced. Furthermore, they investigated
if experiencing flow is connected to physiological improvements attained during the
exercise intervention. The 12- to 16-week interventions included six randomized
intervention groups (in a sense of primary prevention), two female and four male
groups performing continuous running, football, interval-running and strength
training. The results indicate that all six randomized exercise intervention groups
experience rather high levels of flow regardless of whether the intervention is a team
or individual sport. Differences in experiencing flow, worry and exertion as well as
physiological improvements could be found for the different types of sport and the two
genders, with the male football group having the highest score for physiological
improvement and the lowest score for worry. A connection between experiencing flow
and physiological improvement could not be found (Elbe et al., 2010).
Stein, Kimiecik, Daniel and Jackson (1995) investigated three psychological
antecedents of flow in sports in a recreational setting. They measured goals,
competence and confidence as well as flow in three different studies with tennis
players, basketball players in college activity classes and hobby-golf player. The first
study had the participants rate flow characteristics in a scale, whereas the second and
third study used the experienced sampling method to measure flow. In the “learning
environment” (basketball class), students in flow experienced greater enjoyment,
satisfaction, concentration and control than their counterparts in boredom, apathy, or
anxiety. In a more competitive environment (tennis and golf), athletes in flow or
boredom states had a better quality of experience than individuals in apathy or anxiety
states. They interpreted these results that contextual differences influence why an

10
athlete perceives a situation as optimal. And they conclude that the antecedents of
flow remain unidentified, neither goal, competence, nor confidence predicted the flow
experience.
Flow-experiences are also in the focus of sports therapeutic settings (such as an
approach in psychotherapy; Reinhard et al., 2008) as well as in the treatment of pain
patients (Persson, 2009), survivors of war with PTSD (Ley, Krammer, Lippert &
Barrio, 2017) and in occupational therapy (Emerson, 1998; Rebeiro & Polgar, 1999)
and nowadays also with regard to exergaming and/or virtual reality in therapy (Riva &
Castelnuovo, 2006). These settings clearly belong to secondary preventions.
Persson (2009) conducted an explorative study designed to further the
understanding of a creative activity group from a “doing perspective”. Play- and flow
theory were chosen as the primary theoretical reference emphasizing this "doing
perspective". Congruent elements from these theories provided the attention focus for
the identification of “play/flow” and “non-play/non-flow episodes” in the performance
of five chronic pain patients within one of the six group sessions included in the study.
Methods for data sampling used were videogram, microethnography-methods as well
as focused interviews. The results from the observations as well as from the interviews
corroborate that this activity group promotes playing and experiences of flow, which
was helpful in the coping-process with pain. This means that flow-experiences may
moderate functional coping-processes.
Ley et al. (2017) performed a single case study of a war and torture survivor, who
was diagnosed with posttraumatic stress disorder (PTSD) and depression, and who
was participant of the sport and exercise therapy program Movi Kune. Participant
observation was conducted as well as semi-structured interviews with the participant
and his psychotherapist. Data analysis resulted in the proposal of different processes:
Beside the focus on bodily sensations related to an exposure effect, contributing to
improvements in body awareness, coping behavior, and affect regulation, whereas the
focus on playing related to an improved performance, presence, enjoyment, and here
especially flow as well as mastery experiences, pointing toward distraction and
motivational-restorative effects. Again, especially the motivational effect of the flow-
experience seems also to be functional in a PTSD-therapeutical setting.
In a study with patients, suffering from depression, Reinhardt, Wiener, Heimbeck,
Stoll, Lau and Schliermann (2008) investigated, if flow-experiences are the
consequence of a downregulated prefrontal cortex and if this downregulation can be
induced by high-intensive endurance workload. This approach could be effective in a
running therapy context for the treatment of depression. One symptom of depression is
that patients suffer from rumination, which is dependent on prefrontal cortex activity.
Reinhardt et al. (2008) ran a study using the above-mentioned workload regulation to
induce flow to 31 adult volunteers with moderate depressive disorders. Using a load-
oriented and speed regulating bicycle ergometer, the participants were kept within an
individual demand level and cycled in this condition for 40 continuous minutes. Flow
state was measured using the Flow-Short Scale (Rheinberg, 2015) during the activity.

11
Effects of mood variations were assessed immediately before and after the training
using a profile of mood-questionnaire. According to the main results, the participants
reported (confirming study 1) a continuous, deep and stable flow experience. The
effects of mood variation can thus be illustrated in the form of an iceberg profile,
which means that negative emotions decreased, and positive emotions increased.
In summary, the here reported studies show clearly that flow-experiences can play a
central role in a health-psychological context. Based on the results of Schüler &
Brunner (2009), flow experience may contribute to the long-term maintenance of
exercising by positively rewarding the sport activity and thus enhancing the
probability to perform it again. With this, two kinds of well-being could be reached
simultaneously, the immediate positive experience quality connected to flow and the
beneficial health effects in the long run (Schüler & Brunner, 2009). If, and how flow
can mediate or moderate also physiological benefits in sports therapy settings remains
unclear. It can be hypothesized that flow inhibits more physical activity, which then
leads to other positive consequences.
Measuring flow in sports
Assessing flow is a key challenge. If we understand flow as a non-reflective
absorption in an activity where attention is focused entirely on the task execution, then
it follows that when being in a flow state, we can hardly think and respond to
questions about that flow state. This deliberate reflection and distraction of attention
away from the task executing can prevent, interrupt or terminate the flow experience
(De Manzano, Theorell, Harmat & Ullén, 2010; Deutsch, Debus, Henk, Schulz &
Thoma, 2009; Peifer, 2012; Rheinberg, 2004; Youssef, 2013). This assumption is
supported by the neurophysiological work on the default mode and self-awareness
networks (Lou, 2015; Jonson, Baxter & Wilder, 2002). Challenging task management
reduces the cortical activity of the network of self-awareness and thereby inhibits the
ability to introspect or self-reflect (Ulrich, Keller, Hoenig, Waller & Grön, 2014;
Ulrich, Keller & Grön, 2016; Harris et al., 2017). Furthermore, flow diagnostics in
sports is made even more difficult by the fact that flow usually seems to be a relatively
short, rare and from the view of athletes an unpredictable state (Aherne et al., 2011;
Swann, 2016). In addition, Nisbett & Wilson (1977) point out, that mental states and
processes are only partially accessible to self-reflection, so that Jackson & Kimiecik
(2008a) come to the following conclusion: "One of the greatest challenges in flow
research is finding ways to assess the experience itself accurately and reliably" (p.
395).
One possible solution could be the use of psychophysiological and neuroscientific
measurements (cf. Peifer & Tan, Chapter 8), which is increasingly the case in non-
sport domains, e.g. computer gaming (Harmat et al., 2015, Peifer et. al. 2014) or
arithmetic challenges (Ulrich et al., 2014, 2016). This would be of great advantage,

12
because the explicit questioning of the subjects would be dispensed and the occurrence
and intensity of flow could be measured directly, live and online during the activity
without any self-reflection and disorder of the activity (cf. Peifer & Tan, Chapter 8).
Keller (2016) reports first approaches in the context of experimental studies. The
activities, however, are again computer games and arithmetic tasks that require no or
only minimal physical activity and do take some minutes only. But the theoretical
basics explaining flow on a (neuro-)physiological basis are still under discussion.
Prominent models, like the transient hypofrontality theory (THT) (Dietrich, 2004),
seem to be too simplistic (Harmat et al. 2015). Studies using psychophysiological and
neuroscientific measurements have great potential but are at the beginning and have so
far revealed only few and partly contradictory empirical findings on the correlates of
flow (Harris et al. ,2017, cf. Peifer & Tan, Chapter 8).
In addition, psycho-/neurophysiological measurements are more difficult to realize
in sport settings for two reasons. On the one hand, the use of corresponding devices
may not be permitted due to the competition regulations or may just contradict the
requirements of the activity. Also, many of the technical possibilities are not yet
sufficiently mature to perform reliable live measurements during intensive physical
activity. That’s why in sport settings so far flow is mostly assessed retrospectively
(after an event), which means all information relies on subjective memory (Swann,
2016). The following approaches are usually used in sports in isolation or in
combination: interviews, experience-sampling and questionnaires.
Interviews
Studies by Jackson (1995, 1996), that are based on interviews, are among the first
and also most cited about flow in sports and exercise and have produced valuable
insights, followed by numerous works in different sport settings, e.g. golf (Swann et
al., 2012, 2015), swimming (Bernier et al., 2009), tennis (Young, 2000). Interviews
are still the method of choice when it comes to obtaining precise information from
athletes about their subjective flow experience (Stavrou et al., 2007). This may be of
particular value in exploratory research of previously unstudied sport settings, as well
as in refining our knowledge about flow (Swann, 2016). However, interviews also
have a big disadvantage. The greater the period between the experience and the
reflection about the experience, the greater is the danger of memory gaps and
distortions. Some interviews on flow refer to events that may have occurred years ago
so there is a real chance that athletes have forgotten certain details or their memory is
biased (Brewer, Van Raalte, Darwyn, Van Raalte, 1991). That’s why Jackman et al.
(2017) suggest conducting event-related interviews as fast as possible after the
activity. In addition interviews with an athlete should be conducted across multiple
events in order to get more detailed information about possible differences in flow
experience and thus a deeper understanding on personal and situational factors that
influence the occurrence of flow (Jackman et al., 2017, Stavrou et al., 2007).

13
Experience Sampling Method
In order to gain more detailed and reliable information, when and under which
specific conditions flow occurs with certain intensity, and what consequences this
might have, the Experience Sample Method (ESM) was developed (Csikszentmihalyi,
Larson & Prescott, 1977, Csikszentmihalyi & Larson, 1987). The overall goal was to
move the flow detection as closely as possible to the respective state, permitting to
assess flow states "online" or “real-time” during the activity, thus when it happens.
During ESM studies participants are equipped with electronic signal transmitters
(for example a pager or mobile phone), which are carried throughout the activity.
These signalers ask the participants at irregular intervals or randomly chosen time
points to briefly interrupt their activity and capture their flow, mood and other
information based on a a brief survey. Compared to retrospective interviews, this
experience data is obtained directly from the course of the action and activities are
interrupted only briefly, but can then be continued. This leads to the fact that the ESM
is relatively complex to carry out, but ecologically highly valid (Rheinberg & Engeser,
2018). While ESM has been used in a variety of flow studies worldwide.
ESM is only of limited use in sport (Swann, 2016). In many sport settings, wearing
a signaler or (randomly induced) interruptions of the activity are forbidden, or
obviously inconvenient or impossible. For these reasons, only very few ESM studies
or ESM-inspired research designs were conducted in sport, e.g. in rock climbing and
high-altitude mountaineering (Aellig 2004, Delle Farve, Bassi & Massimini, 2003) or
long-distance running (Schüler & Brunner, 2009).
Ufer (2017) set up a study design in the field of extreme ultramarathon races
avoiding the main disadvantages of the ESM and naturally integrating data acquisition
into the event. Flow was repeatedly assessed at various time points during and
immediately after completing several competitions lasting up to 250 kilometers, e.g. in
the Amazon rainforest, Kalahari Desert or at the polar circle in winter. Athletes didn’t
have to wear a signaler during the races. Instead, they were asked to report their flow
experience when finishing a section or at official checkpoints throughout the race.
Checkpoints are an important part of the race infrastructure: athletes naturally stop
their running in order to provide themselves with fresh food and water, treat blisters
etc. Also, they were asked by organizers and the medical staff how it is going, how
they feel, and it is checked whether their health condition allows them to continue the
race. Although “checkpoint management” is, like boxing stops in formula one, an
important part of these races, checkpoints seem well suited for assessing flow: athletes
are not disturbed and interrupted during their run. Instead, flow is assessed when they
naturally stop running and have to switch their attention away from running to more
(self-) reflective activities, e.g. responding to the medical doctors, reflecting what to
eat, body/equipment check, etc. Athletes were not asked to report their current flow
experience in the moment of the survey but retrospectively with respect to the last

14
running section in mind. This procedure avoided potential interference of the
questioning with the flow experience. Finally, repeated assessments during the events
allowed capturing flow very close to the experience and from a "fresh" memory. In
addition they also allow for longitudinal analysis.
Questionnaires
Most studies in sport, exercise and beyond used questionnaires to investigate flow
(Engeser & Schiepe, 2012). Validated psychometric scales are the preferred method of
choice when the goal is to capture the intensity of flow and to analyze correlations
between flow and other constructs. Numerous quantitative instruments have been
developed to assess flow, but those developed by Rheinberg, Vollmeyer & Engeser
(2003) and especially Jackson and colleagues (1996, 2002, 2004, 2008b) are the most
widespread.
In English-speaking countries, the Flow State Scale (FSS) and the revised version
FSS-2 have been most widely used to assess situational flow in sports and beyond
(Jackson & Marsh, 1996, Jackson & Eklund, 2002, 2004). It refers the nine
dimensions of flow (Cikszentmihalyi, 2002) and analogously consists of nine
subscales with 4 items each, so a total of 36 items. A short version of the FSS-2 (Short
Flow Scale) was also developed for brief assessments (SFS, Jackson et al., 2008a). In
addition to the situational flow experience, the Dispositional Flow Scale (DFS,
Jackson & Eklund, 2002, 2004, Jackson et al., 2008b) captures the construct "autotelic
personality," the general tendency to experience flow. The questionnaires have been
translated into Greek (Stavrou & Zervas, 2004), French (Fournier et al. 2007), and
Japanese (Kawabata, Mallet & Jackson, 2007).
In the German-speaking area, the Flow Short Scale (FKS, German version) was
developed by Rheinberg et al. (2003). The goal was to provide an instrument that can
detect flow in its various components and at the same time is compact enough to easily
use it in everyday life. In addition, the scale should be able to apply across different
situations for any activity. The resulting FKS consists of 10 items that take less than a
minute to complete and yet capture all components of the flow experience first
described by Csikszentmihalyi (1975). The instrument has been translated into various
languages: English, French, Italian, Danish, Czech, Turkish, Dutch (Rheinberg, 2015)
and tested in different settings, e.g. sport, work, learning, so that the findings also
permit comparison across different contexts (Rheinberg et al., 2003).
Nevertheless, it is difficult to define whether a person really was in a flow or not.
Quantitative measures result in mean scores. They provide information about the
intensity of the respective flow experience but do not answer the question of whether
flow was actually experienced or not (Moneta, 2012, cf. Moneta, Chapter 2). It is hard
to determine how high a value should be to distinguish a flow state from a non-flow
state or a micro flow from a deep flow (Deutsch et al., 2009, Swann, 2016). Kawabata
& Evans (2016) addressed this issue and suggest that a mean score of 3.4 and 3.3 for

15
the preconditions of flow (demand-skill balance, clear goals, unambiguous feedback),
measured by the FSS-2, may differentiate flow from non-flow experience. But in a
recent multi-measurement study using scales and questionnaires, the mean scores
suggested by Kawabata & Evans (2016) were not able to differentiate people that were
in a flow state from those who did not experience flow (Jackman et al. 2017). Another
problem is that in the course of an activity to which a survey response relates, the
experience can vary. It can be assumed that flow is not always experienced at a
constant level. But then how is the flow experience transferred into a single value?
Does an assessment refer to the moment with no or little flow? Or the time point with
intense flow? Or is a kind of average built? Stavrou et al. (2007, p. 454) summarize
the limits of quantitative scales: "Trying to quantify athletes' flow has certain
limitations, because it cannot portray the subjective nature of the phenomenon".
Last, not least, questionnaire development is based on central assumptions and
descriptions on flow and the scales actually used in flow research generally refer to
Csikszentmihalyi’s dimensions and characteristics of flow. But Jackman et al. (2017)
raised concerns about the discriminant validity of the existing flow scales. In recent
studies Swann et al. (2017a, b) discovered that during superior performance flow and a
similar, though different “clutch” state with overlappings of characteristics can be
experienced but existing scales do not differentiate between flow and clutch states.
That’s why Jackman et al. (2017) recommend the revision of existing scales or the
development of new instruments to better assess flow and differentiate flow from
clutch states.
Conclusion
All methods described above have advantages and disadvantages. “No single
measurement approach will be able to provide trouble-free assessments of the flow
experience” (Jackson and Kimiecik, 2008a, p.395). Psychophysiological and
neuroscientific measures may be an attractive way to assess an athlete’s flow
objectively “online” during intense exercise in the future. But so far, sound theoretical
foundations and/or technical devices that reliably record data during exercise are still
missing. The ESM is of limited use in many sport settings, because it is inconvenient
or can even turn dangerous to interrupt athletes from task execution for assessments.
But if the data capturing process can be integrated more “naturally” into the course of
an event and thus minimize distortions or interruptions, the ESM approach is an
interesting option to get experience-near data, because the data is assessed from an
external person, filling out the questionnaire, while the individuum can be active.
Questionnaires are most widely used but may lack discriminant validity because they
do not differentiate between flow and clutch states. Also they only present mean
scores but do not distinguish, if someone really was in a flow state or not. Interviews
offer in-depth information on athletes subjective flow experience but there is a risk of

16
memory distortion and data relies on the quality of self-reflection. We can conclude
that „a gold measurement standard for flow has yet to be reached” (Moneta, 2012, pp.
23-24). But whatever method is used, with all limitations, the assessment of flow
should always take place in an “event-focused” way (Swann, 2016), as close as
possible to an event, without disturbing or interrupting an athlete from task execution.
And in addition Jackson (2000) suggests that a mixed method approach could be an
appropriate way to capture the greatest breath of information in flow studies.
Part 3: Flow in Team Sports
Collective or team flow is a relatively new research topic in sport psychology. A
nice description of team flow delivers Sawyer (2006): “One might say that they have a
good chemistry, or that things are clicking or in sync. For just about any sports team,
one can speak of the group spirit, the team spirit, or the esprit de corps. A
commentator might say they gelled as a unit or that they displayed good teamwork.
All of these metaphors focus on the entire group and on their performance together as
an ensemble. Even if the individual performers are prepared and focused, a good
ensemble performance doesn’t always emerge.” (Sawyer, 2006, 157f). In competitive
team sports, different terminology is used for comparable phenomenon, like e.g. “the
hot hand phenomenon” or “playing in a momentum”.
Only few studies are published so far. Jackson (1995) was one of first studies
investigating flow not only in individual, but also in team sports. Nevertheless, in this
study, she studied the phenomenon not really in a collective perspective, because the
individual flow-experiences of the players were measured. Cosma (1999) was the first
researcher, introducing the term “Team Flow”. She studied five College Football-
Teams and found out that flow is higher and more stable, when players report acting in
a “playing tune”. Despite this finding, this study is problematic from a methodological
point of view. She modified the Flow-State-Scale 2 (Jackson & Eklund, 2002) in a
way, just modifying the items from an “I-perspective” in a “We-perspective” (e.g. “I
know clearly what I wanted to do” in “We knew clearly, what we wanted to do”) and
called this scale “Team Flow Short Scale” (TFSS). And the measurements happened
retrospectively, weeks after the games (and so the flow-experiences). Both above
mentioned studies did not measure a real collective experience. Nakamura and
Csikszentmihalyi (2002) also explored this phenomenon and called it “shared flow”.
They clearly circumscribed individual from “shared flow” and noted that nothing
really is known about “shared flow”, neither about the circumstances, nor about its
dimensions. Lazarovitz (2003) studied 114 female ice-hockey players, measuring
individual (FSS-2) and Team Flow (TFSS) and found differences in the experiences
flow between the players. Reinhardt (2017) studied one youth-soccer-team (18

17
players) over a whole season, measured the individual flow-experiences post-hoc each
game (using the Flow Short Scale, FKS, Rheinberg et al., 2003), documented the
demand-ability-fit and the results of each game. He could show that the players can
experience flow in the games. The latest study in sports was the study from Vurgun et
al. (2016). The aim of this study was to determine the flow states of elite handball
players and to examine its effects to other variables. 34 athletes competing in Turkish
Handball Super League participated in the study and as a result of a total of 17
matches, 142 participations were included into this retrospective analysis. They
measured Flow (FSS-2, Turkish version) and their perceptions of the difficulty levels
of the competition. As a result of the study, they found that female players in a team
context had higher flow experiences than male players in teams. Flow experiences of
handball players aged 30 and over were found to be significant at a higher level than
those of handball players aged 30 and under. They concluded that the flow-
experiences in teasm is dependant to the, duration of game, gender and age.
Summarizing the findings so far, the empirical data in the sport context is relatively
small and heterogenous.
Theoretical assumptions to explain team flow
Players of a team share common experiences (same games, same coach, same
results). Because of league structures in competitive team sports, all teams in one
league are comparable regarding their performance level. The same precondition
applies for all teams of a league. Correspondingly the relationship of demand and
ability could be comparable for all individuals of a team. Probably many players have
comparable demand-ability appraisals in one game. This would be the demand-ability-
fit, we know from individual flow experience precondition, which simply happens
cumulative. There is evidence to belief that the demand-ability fit shifts in group
activities and so effects performance in sports. Ryu and Parsons (2012) could show
that players of computer games in a group setting tend to make more risky decisions
than playing on their own. This also can be assumed for players in sport teams,
because the cognitive demands of these computer games are similar to these of teams
in sports. The shared information could be one reason that a player in a group setting
can expand his performance over his individual possibilities. In the following three
possibilities for the explanation of team flow will be discussed.
1. Opioids and Neurotransmitters: Cohen et al. (2010) showed: “compared with
training alone, group training significantly increases pain threshold, suggesting that
synchronized activity somehow heightens opioidergic activity. While it is possible
that the effect on pain threshold of being in a group is independent of (an additive
with) the opioid-mediated effect of exercise, we favour the simpler explanation that
group exercise stimulates greater opioid production.

18
2. “Risky-Shift-Phenomenon”: The above-mentioned explanation is one-dimensional
and explains possible shifts in an appraisal simply on changes in neurotransmitters
in social performance-related situations. In social psychology, “group polarization”
refers to the tendency for a group to make decisions that are more extreme than the
initial inclination of its members. These more extreme decisions are towards greater
risk if individuals' initial tendencies are to be risky and towards greater caution if
individuals' initial tendencies are to be cautious. The phenomenon also holds that a
group's attitude toward a situation may change in the sense that the individuals'
initial attitudes have strengthened and intensified after group discussion, a
phenomenon known as attitude polarization or “Risky-Shift” (Stoner, 1961, 1968).
3. Emotional Contagion: This is the phenomenon of having one person's emotions and
related behaviours directly trigger similar emotions and behaviours in other people.
One view developed by Hatfield et al. (1994) is that this can be done through
automatic mimicry and synchronization of one's expressions, vocalizations,
postures and movements with those of another person. When people unconsciously
mirror their companions' expressions of emotion, they come to feel reflections of
those companions' emotions (Hatfield et al., 1994). Emotions can be shared across
individuals in many different ways both implicitly or explicitly. For instance,
conscious reasoning, analysis and imagination have all been found to contribute to
the phenomenon (Hatfield et al, 1994). Emotional contagion is important to
personal relationships because it fosters emotional synchrony between individuals.
A broader definition of the phenomenon was suggested by Schoenewolf (1990) is
"a process in which a person or group influences the emotions or behaviour of
another person or group through the conscious or unconscious induction of emotion
states and behavioural attitudes" (Schoenwolf, 1990).
So far, we are still at the very beginning of understanding, describing and explain
team flow in sports. From our point of view there are different ideas of possible
mechanism as well as phenomenon of team flow discussed in the field. In this area, we
definitely need a clear research focus and more empirical work as well as theoretical
reflections to better understand team-flow in sports and exercise.
Part 4: Discussion and future perspectives
This chapter showed that flow research has a more than 25-years longing tradition
in the area of sports and exercise psychology leading to important insights. We
showed that flow experiences can be beneficial from a motivational point of view and
that it helps to stick with the rehabilitation regimen and that it can be hypothesized that
flow experiences are associated with other constructs known in positive psychology.
But one of the main interests in sport psychology – the possible relationship of flow
with performance cannot be answered clearly until today.

19
With regard to the “mechanism”, we have to state that there are different
assumptions. The more cognitive theory focuses on the skill-challenge fit as the
mechanism to produce flow. This could be shown in different empirical studies. The
transient hypofrontality theory, as a more neuro-cognitive approach, and its
explanation for the inhibition of flow experiences are inconsistent from an empirical
study point of view. The results of the studies reported here show indirect evidence in
favour of the hypothesis that prolonged exercise might result in a state of transient
hypofrontality. Only a few studies reported indirectly a downregulation of the
prefrontal cortex during exercise (e.g. Dietrich, 2004). Additionally, other neuro-
imaging measures such as optical imaging or EEG combined with other selective
neuropsychological measures in sports- and exercise-settings are needed to further
explore the complex interaction between exercise and mental function. Other more
physiological variables, like e.g. the heart-rate-variability might be worth considering
in the context of flow experiences in a more complex view.
As far as the “measurement problem” concerns, especially in sports and exercise
settings, there is also still discussion. Our suggestions are not new, but should be
discussed in the future. Initially, Csikszentmihalyi (1975) used qualitative data through
personal interviews to explore a new model for intrinsic rewarding behavior, which
led him to the development of the concept of flow. Further qualitative and quantitative
(i.e. questionnaires) research techniques were used, facing various challenges in
measuring the construct, conditions, and occurrence of flow (Swann, 2016). One
challenge to address these limitations is to measure flow as close as possible to the
moment of occurrence. Therefore, the Experience Sampling Method (ESM) was used
applying a questionnaire when receiving a signal. However, this method interrupts the
momentary experience and might not be as appropriate for sports as for other task
domains (Swann, 2016). Seifert and Hedderson (2010) took an event-focused
approach; they observed skateboarders in a skate park then approached them directly
and interviewed them individually about their experiences. Furthermore, Swann et al.
(2015) found that elite golfers were able to recognize flow in other players, concluding
that flow could be observable. Furthermore, the authors stated that “observations may
be a useful avenue for flow research” (p. 230). Observation may be useful in
appraising flow elements in sport and exercise through bodily expression (e.g. joy, a
sense of safety or fluency of movement; movement analysis methods of
Dance/Movement Therapy). EMS method could be combined with interviews in order
to appraise individual perceptions soon after the flow occurrence. Taken together, it
appears that the ESM method may be a better method of measuring flow experiences
in sports and exercise, especially if this data can be combined with observational data
as well as psycho-physiological data.
A complete new area in the flow-related sport psychology is the research in team
flow. There are only very few cross-sectional studies conducted and from our
knowledge just one longitudinal study (Reinhardt, 2017), who followed a youth soccer
team over one complete season and assessed (individual) flow and performance. He

20
could show that the players can experience flow in the games and that there is a
correlation between flow and performance of the team. Nevertheless, even this study is
weak from a point of methodological rigor. We need more studies with a field-
experimental study design to study this possible research question. Furthermore, we
need to clarify the possible mechanism, responsible for the occurrence of team flow.
Currently, we do not know if it is a more psychos-physiological explanation, if it is
connected to the “risky-shift-phenomenon” or it is simply emotional contagion. More
research in this area could be extreme beneficial for the advancement in flow research
in sports and exercise.
Study Questions
• What are the ten main factors influencing the occurrence of flow in elite sport?
Under which conditions do they facilitate, prevent or disrupt the flow?
The ten core factors that influence the occurrence of flow in elite sports are focus,
preparation, motivation, arousal, thoughts and emotions, confidence, environmental
and situational conditions, feedback, performance, team play and interaction Swan et
al. (2012). Depending on whether these factors occur prior or during a performance,
they can facilitate, prevent or disrupt the flow experience. If these factors appear in
their negative form before flow occurs, they prevent flow, if they appear during flow
they are likely to interrupt the experience. It is not yet clear what exactly makes each
of these factors negative, nor what level or intensity of a facilitator (e.g. of arousal or
concentration) is needed to promote flow.
• How does flow affect performance?
Given the key characteristics of flow, e.g. strong focus on the task with a high level
of control and effortless, intuitive action, since the beginning of flow research, flow is
considered a highly functional state that is very likely to have a positive impact on
performance. Also an indirect effect of flow on performance is likely. Flow is
generally perceived as a positive experience. This leads to an increased motivation to
practice, which results in a better performance. However, the empirical findings in
sports are mixed. Some researchers found positive links of flow with performance,
some didn’t.
• Explain how flow is measured in sports. What are the advantages/disadvantages
of the methods?

21
Psychophysiological and neuroscientific measures, like EEG may be an attractive
way to assess an athlete’s flow in the future. But so far, sound theoretical foundations
and/or technical devices that reliably record data during exercise are missing. The
ESM is an interesting option to get experience-near data but of limited use in many
sport settings, because it is inconvenient or can even turn dangerous to interrupt
athletes from task execution for assessments. Other methods, also using
questionnaires, but not in action, are easy to administer and most widely used. But
they may lack discriminant validity because they do not differentiate between flow and
clutch states (Jackman et al., 2017). Also they only present mean scores but do not
distinguish, if someone really was in a flow state or not. Interviews offer in-depth
information on athletes subjective flow. Whatever method is used, the assessment of
flow should always take place as close as possible to an event, without disturbing or
interrupting an athlete from task execution. A mixed method approach could be an
appropriate way to capture the greatest breath of information in flow studies (Jackson,
2000).
• What are the possible mechanisms in team-sports currently under discussion?
Currently there is a discussion about opioids and neurotransmitters, about the
“risky-shift-phenomenon” and about emotional contagion as possible mechanisms to
induce team flow experiences.
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