When Suddenly Nothing Works Anymore Within a Team – Causes of Collective Sport Team Collapse

Abstract

Collective team collapse occurs when multiple players of a sport team experience a sudden and extreme underperformance within a game. To date, minimal research has been conducted on the causes of collective team collapse. Thus, goals of this study were to explore perceived causes of collective team collapse in different sports and to define team collapse in contrast to negative momentum. To investigate factors causing and maintaining collective sport team collapse, an inductive, exploratory qualitative analysis of individual interviews was conducted. Semi-structured interviews were carried out with 10 athletes of professional German teams of various sports playing in between first and fourth division. Participants were interviewed about a team collapse event they had experienced with their team during the past year. Data were collected and analyzed using a grounded theory methodology. Collective team collapse appeared to be induced by a temporal cascade of causes rather than by single triggers. This cascade included antecedents, which represent factors that make the occurrence of a team collapse more likely; critical events, which include specific events within the game that trigger a team collapse; as well as affective, cognitive, and behavioral outcomes that foster a maintenance of the collapse. Within this theoretical framework, social factors, such as decreased performance contagion or emotional contagion, played crucial roles in causing a team collapse. These results illustrate that collective team collapse is more than the sum of individual choking of multiple players at the same time. In conclusion, a new definition, differentiating team collapse from negative momentum, is introduced. Furthermore, a process model of causes of collective team collapse is proposed. The results provide first insights into causes of collective collapse in a variety of team sports. The developed model is supposed to help future research to better connect to practice and to support athletes, coaches, and sport psychologists.

Introduction

Most team sport athletes are familiar with the following phenomenon: Their team’s game is going well and suddenly, from one moment to the other, performance drops so considerably that nothing seems to work anymore for the team. The 2017 Super Bowl describes one of the most significant examples of such a sport team collapse in recent years: The Atlanta Falcons led 28-3 against the New England Patriots during the second half and had a 98.9% statistically calculated chance to win the game, but unexpectedly lost 28-34 in overtime (Rafferty, 2017). The Falcons’ performance was described as one of the toughest losses in Super Bowl history, where one could observe a team falling apart. Such an incident is an example of collective team collapse, which occurs when a team is in the lead and abruptly loses control over the game (Boss and Kleinert, 2015). It describes situations where unexpectedly nothing seems to be working anymore within a team’s performance capability. Apitzsch (2006) defined team collapse as occurring “when a majority of the players in a team sport suddenly perform below expected level in a match of great, often decisive, importance in spite of a normal or good start of the match or when a team underperforms right from the start of a match” (p. 38).

Adler and Adler (1978) were among the first researchers to describe the sudden, extreme shifts in sport team performance with the term “momentum”. These changes in physical performance can be both positive and negative, where positive momentum is when everything seems to work well in a team, and negative momentum is when the team underperforms collectively (Den Hartigh et al., 2014). Momentum can shift from positive to negative as well as from one team to the other during a game (e.g., Cotterill, 2012; Den Hartigh et al., 2014). Recent research in the area of momentum in sport showed that negative psychological changes, such as collective efficacy and team cohesion, as well as interpersonal coordination seem to play a role in causing negative momentum (Den Hartigh et al., 2014). Furthermore, Boss and Kleinert (2015) discovered the social effect of performance contagion as an underlying mechanism of negative momentum with rowing pairs. These results are difficult to transfer to actual sport teams though, since they focused on teams consisting of two members, randomly assigned to each other. Group processes within teams consisting of more than two members, who have been part of a team for months or years, may be different and more complex. Various models of momentum have been developed so far. Taylor and Demick (1994) proposed the Multidimensional Model of Momentum, consisting of a momentum chain that explains the development of both positive and negative momentum. This momentum chain includes precipitating events, followed by changes in cognition, affect, and physiology, which cause behavioral changes that lead to an increase or decrease in performance. This change in performance combined with changes in cognition, physiology, affect, and behavior of the opponent team then causes a change in outcome.

Momentum constitutes a phenomenon that is closely related to collective team collapse (Cotterill, 2012), but existing research has failed to sufficiently distinguish between the two phenomena. Apitzsch (2009), the first known researcher to investigate collective team collapse, used Taylor and Demick’s (1994) momentum chain and extended it through qualitative data from players of a handball team that had just recently experienced collective team collapse. Apitzsch (2009) explains that two different causal chains, happening at two different points in time within a game, could evoke what he labels as collective collapse. The first chain, prior to the start of a match, includes either negative thoughts, leading to negative emotion and resulting in a passive playing style, or positive emotions, leading to positive thoughts and resulting in overconfidence and mistakes during the game. The second chain, occurring at the end of a game, involves a critical event within the game that leads to negative cognitions, which then cause passive behavior and subsequent negative performance. Apitzsch (2009) developed these causal chains through a qualitative case study exploring the causes of team collapse with a sport team. He found inappropriate behavior, failure of the role system, negative communication, opponent’s change in tactics, and scoring by the opponent to be major causes of the handball team’s collective collapse but misses to specify in detail what these factors stand for. Although Apitzsch’s (2009) case study provides some insight into team collapse, knowledge of factors causing team collapse across different teams and game situations is limited. In order to identify factors that make the occurrence of team collapse across various teams and team sports more likely, qualitative research with different situations and various types of sport is needed (e.g., Crust and Nesti, 2006; Apitzsch, 2009).

Several factors influencing momentum (Taylor and Demick, 1994) and possibly collective team collapse (Apitzsch, 2009) as well are related to psychological processes and the perception of momentum, which are often referred to as “psychological momentum” (Iso-Ahola and Mobily, 1980; Crust and Nesti, 2006; Gernigon et al., 2010; Mortimer and Burt, 2014). Iso-Ahola and Mobily (1980) defined psychological momentum as “an added or gained psychological power, which changes interpersonal perceptions and influences an individual’s mental and physical performance” (p. 391). Congruent to momentum, psychological momentum can be either positive or negative and Taylor and Demick (1994) argue that positive or negative shifts in performance (momentum) can only happen if they are recognized by the team (psychological momentum). The existence of psychological momentum has been discussed broadly in the literature (e.g., Taylor and Demick, 1994; Crust and Nesti, 2006; Mortimer and Burt, 2014). Cornelius et al. (1997), for example, argue that attributions of positive or negative psychological momentum are no more than mental labeling processes to evaluate or describe performance. In their model, negative psychological momentum is an outcome rather than a cause of bad performance. Vallerand et al. (1988) introduced the Antecedents–Consequences Model (ACM) of psychological momentum, suggesting that the impact of positive psychological momentum on performance depends on personal factors, such as motivation, as well as on situational factors, such as audience behavior. While the ACM distinguishes antecedents from consequences of psychological momentum, it focuses on positive psychological momentum only and does not consider negative psychological momentum, which is problematic (Apitzsch, 2009).

While empirical research on causes of momentum, psychological momentum, and collective team collapse is still developing, many studies have investigated the causes of individual performance failure (i.e., choking under pressure or simply “choking”). Choking can be defined as “performance decrements under circumstances that increase the importance of good or improved performance” (Baumeister, 1984). Various theories exist about causes of choking, which are related to concentration difficulties, including distraction (Wine, 1971), a high self-focus (Baumeister, 1984; Beilock and Carr, 2001), and shifts of attentional focus (Eysenck et al., 2007; Oudejans et al., 2011). In order to bridge the gap between individual and team sport performance failures, Hill and Shaw (2013) conducted a qualitative study examining individual choking in various types of team sports. By interviewing team sport athletes, Hill and Shaw (2013) found important games, expectations, individual responsibility, presence of an audience, and physical as well as mental errors to be important antecedents for the occurrence of individual choking within a team sport. Anxiety, distraction, and perceived control were mechanisms triggering choking within a team. Furthermore, moderators, such as team cohesion or motivational climate, as well as perceived consequences, such as a significant drop in performance or negative affect, were crucial for the occurrence of individual choking in teams. These findings offer initial insights into factors influencing individual choking in a team environment that could be similar to causes of the choking of a whole team. It, however, does not consider the reasons of a collective decrease in a team’s performance.

While individual choking is well explored already, research related to the collective collapse of an entire team is still limited. It further appears that existing research applies two different terms, namely collective team collapse, and negative momentum, to describe this phenomenon without differentiating between the terms. Momentum is even used to describe both the individual and collective underperformance of athletes. Thus, the current qualitative study does not only aim to investigate athletes’ perception of causes of collective sport team collapse, but also attempts to define team collapse in contrast to the seemingly similar construct of negative momentum. In order to overcome limitations of Apitzsch’s (2009) case study, a sample of athletes from different teams in a variety of sports was included, which we expect to result in a more global view of causes of team collapse.

Materials and Methods

Philosophical and Methodological Orientation

One purpose of the study was to gain an understanding of athletes’ lived experiences and perceptions of collective team collapse in their specific team sport environment, and a second to develop an inductive theory that displays the phenomenon in these specific situations. Considering this purpose and the limited empirical research exploring the causes of team collapse, a constructivist–interpretivist grounded theory methodology (Charmaz, 2006) was used to collect and analyze data and subsequently derive a substantive theory (Holt, 2016; Weed, 2017). Constructivists reject the idea of objectivity and assume that the view of the world and certain phenomena rely on individual perceptions of it (Weed, 2017). Since these individual perceptions are subjective due to personal experiences, it is impossible to gain a perfect, unbiased view of the world. Thus, a grounded theory methodology can be used to understand multiple biased perspectives of reality in order to achieve a view that is plausible and representative of the data. Charmaz (2006) described grounded theory as “a systematic, yet flexible methodology for collecting and analyzing qualitative data to construct theories that are grounded in the data themselves” (p. 2). Consequently, she proposed that it was both a method and product of inquiry (Sparkes and Smith, 2014). This methodology enables “an analytical interpretation of the participants’ worlds and the processes constituting how these worlds are constructed” (Charmaz, 2005, p. 508) to generate theory from data.

Participants

Participants consisted of 10 athletes (seven male, three female) from different teams within various sports (i.e., four volleyball, three basketball, two soccer, and one field hockey). Athletes’ ages ranged from 19 to 30 years (M = 24.30, SD = 3.74). Participants’ criterion for inclusion was 10 years or more of experience in the sport and varied between 10 and 20 years (M = 15.60, SD = 3.57). The time they were a member of their current team varied between 0.5 and 14 years (M = 4.95, SD = 4.49). All participants were playing in between first and fourth division in Germany and therefore either on a national or the highest regional level. The experience level of the athletes was required to ensure that a lack of skills and abilities was not the reason for the experienced team collapse.

Interview Guide

We developed a semi-structured interview guide to investigate athletes’ perceptions of causes of collective sport team collapse. The first author, with a background in psychology, and the second author, with a background in sport science, designed potential interview questions dealing with underlying factors of team collapse and with processes occurring within the team during the collapse event. During 4 × 4-h sessions, the first and second authors discussed the questions with the third author, who is experienced in qualitative research. The three authors then discussed the third author’s critique and review until consensus on a final version of the interview guide was reached.

The first section of the interview guide consisted of a short colloquial description of team collapse to ensure participants were envisioning the same phenomenon. It was developed during 2 × 4-h sessions by the first, second, and third authors. The description included several aspects mentioned to be important for team collapse in existing literature (Apitzsch, 2006; Boss and Kleinert, 2015), namely that the team’s performance decreased more than usual, that this happened unexpectedly and that nothing seemed to be working anymore within the team during the collapse. Participants then described a similar experience with their team preferably within the last 12 months or within the last 5 years at maximum to capitalize on memory recall. Even though we provided a lengthy timeframe (up to 5 years), all participants were able to recall a team collapse event within the last year. The second section (Questions 1–7) consisted of questions about details of the team collapse, such as, at what point during the game it took place or how many players were involved. The content of the third section (Questions 8–12) included questions about the impact the team collapse had on players and game. A sample question for this section was “To what extent did the team collapse influence the further course of play?” The last question (Question 13) specifically asked about influencing factors of collective team collapse and was posed last in order not to affect participants’ answers to previous questions. To conclude the interview, participants were asked whether there was anything else they found to be relevant regarding the topic of collective team collapse (Question 14). The full interview guide is included in the Supplementary Data Sheet 1.

Data Collection

Given the purpose of the study, two different sampling methods were used to recruit participants. The purposeful sampling method of criterion-based sampling was chosen as the principal sampling method to approach athletes of various German sport teams. In order to fulfill the sampling criteria, participants needed to: (a) be members of a team sport consisting of more than two players, (b) play in between first and fourth division, (c) have experience in playing the sport for 10 years or more, (d) have experienced a team collapse event with their current team, and (e) be willing to talk about the team collapse event. Athletes who fulfilled these criteria were recruited for the study and the purpose of the research was explained upon arrival for the interview. After implementation of the initial interviews, theoretical sampling was applied to recruit further participants. First results showed that key players and their performance seemed to play a crucial role in the team collapse process and that athletes attributed more responsibility to key players, who fulfill a leadership role in the team. Although there are several formal and informal leadership roles present within teams, and even though team captains do not necessarily fulfill a principal informal leadership role in their team, it is undeniable that captains hold a formal leadership role. Therefore, in order to include the perception of causes of team collapse of players with a leadership role in the team, team captains were predominantly recruited during theoretical sampling. The retrospective semi-structured interviews were carried out by seven different interviewers, whereby the first author interviewed three athletes and the second author interviewed one athlete. The additional five trained assistant interviewers were involved in interviewing due to organizational issues, such as the implementation of interviews in different parts of Germany at the same time. Furthermore, it was important for the interviewers to be knowledgeable in the sport to fully engage in the interview. All interviewers were trained professionally on semi-structured interview conduction for 12 h prior to carrying out any interviews. To further ensure consistency among the different interviewers, they tested the interview guide with two athletes each as a pilot testing phase, while being supervised by the first and second authors. Specific feedback on the interview conduction was provided before interviewers completed actual interviews with study participants. This procedure was repeated twice and occurring differences in the application of the interview guide were discussed between interviewers, and first and second author until consensus about the interviewing process was reached.

The duration of the interviews ranged from 20 to 40 min (M = 31.14; SD = 6.97). Interviews were carried out in German, which was the native language of all participants and interviewers. All participants were informed that participation was voluntary and that goals of the study were to identify underlying factors and mechanisms of the phenomenon of team collapse. They were assured the right to withdraw from the interview at any time without penalty. Participants were further informed that audio records would be used for research purposes only and that recorded data would be treated confidentially. Additionally, they were asked to sign a declaration of consent, stating that they had been informed about the purpose of the study and agreed with audiotaping of the interview. All participants gave written informed consent in accordance with the Declaration of Helsinki. The study did not involve any invasive or potentially dangerous methods and therefore, in accordance with the German Research Foundation (DFG) and in accordance with the guidelines of the Department of Sport and Health Sciences at the Technical University of Munich, did not require a formal ethics approval.

Data Analysis and Trustworthiness

All interviews were audio recorded and manually transcribed verbatim, resulting in 146 pages of single-spaced text. The first two authors analyzed the interview transcripts following Charmaz (2006) suggestions on an inductive thematic grounded theory analytical procedure. Both authors read the interview transcripts multiple times to enhance familiarity with the content. During initial coding, interview data were analyzed using incident-to-incident coding and in vivo codes (Charmaz, 2006). An example for initial coding is given on the basis of the following quote: “Passes don’t arrive anymore, throws don’t reach the basket, you don’t achieve stops, talking of defensive stops, and everything becomes difficult and then you think. Then you get this panic and this panic doesn’t help at all and so the collapse continues.” While the first part of this quote was coded as unforced error and bad defense, the second part was coded as anxiety. During focused coding (Charmaz, 2006), concepts generated through open coding were reassembled into categories and subcategories to better explain the perceived causes of team collapse. The categories unforced error and bad defense for example were classified as subcategories in the superior category of unforced error accumulation. Theoretical integration included the investigation of relationships between categories and sub-categories in order to gain an understanding of the connections between categories. In the presented example, unforced error accumulation was linked to player anxiety. Throughout the process of initial and focused coding, constant comparison was applied, continuously comparing new data with already developed concepts, categories, and relationships between categories. Simultaneously, theoretical memos were used during initial and focused coding and contained various interpretations and relations between the identified categories in the form of graphical mind maps. Memos were further used to guide integration of categories into a theoretical framework in seeking to plausibly explain the relationships between causes of team collapse. Data saturation was identified when interviews did not provide any new information for the development of further categories. Theoretical saturation occurred when fresh interview data did not reveal any new properties of the established categories of the theoretical process model (Charmaz, 2006). Data saturation and theoretical saturation were reached after eight interviews, which is why we stopped interviewing after 10 participants.

Data collection and analysis followed the suggestions of Smith and McGannon (2018) for conducting rigorous qualitative research. Therefore, methods used in the past to demonstrate methodological rigor, such as member checking, inter-rater reliability, and the notion of universal criteria, have been omitted in the analytical process as they were “shown to be ineffective for verification, trustworthiness, or reliability purposes” (Smith and McGannon, 2018, p. 1). In order to support the analytical process and enhance methodological rigor, assumptions made by researchers were regularly compared to newly gathered data (Weed, 2017). In addition, graphical illustrations of the developing model were used during data analysis to help researchers think theoretically instead of descriptively (Holt, 2016). The third author, who was not involved in data analysis initially, acted as a “critical friend” (Sparkes and Smith, 2014; Smith and McGannon, 2018) and challenged the abstracted qualitative categories as well as the theoretical model developed by first and second author. In this role, he provided feedback on the classification of categories from an independent, external expert perspective. Categories and the developed theoretical model were then discussed extensively between first, second, and third author. The resulting process model was furthermore evaluated post hoc using “fit, work, relevance, and modifiability” as quality criteria (Weed, 2017, p. 153). It was evaluated to fit the complex phenomenon of team collapse as experienced by the participants and to work through explaining the relationship between various causes of team collapse. The phenomenon was also judged to be relevant for teams competing in a league system and the developed model was found to be suitable for future adaptions.

Results and Discussion

To gain a better understanding of causes of collective team collapse, we analyzed athletes’ perceptions of the phenomenon and possible causes of it. We included interview responses from all 10 participants in the results. The interview analysis showed that athletes described collective team collapse as being evoked and maintained by a cascade of causes rather than by specific single triggers. Participants found these causes to be in a temporal order, which is why the results of the interview analysis are also presented in a sequential order. Some factors seemed to be present before the underperformance of the team and tended to make the team prone to a team collapse. These factors were labeled as antecedents. Other factors seemed to describe a specific event within the game triggering the actual team collapse, which were classified as critical events. Furthermore, participants named factors that seemed to be a result of the critical event, leading to the further maintenance of the team collapse. These factors maintaining the collapse were further divided into affective, cognitive, and behavioral outcomes. Figure 1 shows a schematic illustration of the relationship between these factors in the form of a process model. The process model of collective sport team collapse collapse illustrates the results of our analysis and our interpretation of the data, but not necessarily the characteristics of the phenomenon of collective team collapse. With the depiction of our results, we chose a linear representation to account for a general trend in the athletes’ narration, implying a temporal difference between antecedents and outcomes of team collapse. A process model represented this data best since it incorporates the temporal differences between facilitators of collective team collapse reported by athletes. As indicated by group dynamics research, however, group phenomena are often subject to cyclical and dynamic rather than linear processes. While this seems to be contradictory to our representation, we want to emphasize that dynamic processes may still play a major role within our temporal, linear framework, but were not subject of our investigation in this study. Future research needs to further explore the specific processes within the phenomenon of collective team collapse.

FIGURE 1

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