Imagery use in esports: future research directions and unique considerations

Description

Examining who uses imagery (participant characteristics), where (location), when (situation), why (function), what (content), and how (imagery characteristics) imagery is used in esports would follow what started the proliferation of imagery research in sport (Munroe et al., 2000), exercise (Giacobbi et al., 2003; Hausenblas et al., 1999; Short, Hall, et al. 2004) and dance (Nordin & Cumming, 2005). These research studies had a simple qualitative design, starting with a definition of imagery and asking participants to describe their imagery use. The results were typically presented as a hierarchical tree describing each component. Collectively, the results of these studies share some of the same findings, but each area also had its unique aspects of imagery.

One criticism of these studies is that, at the time, there was a tendency to fit the results into Paivio’s (1985) imagery framework. For example, skill-related images (“what”) were similarly categorized as serving an “improve skills” (“why”) function. What we know now is that images of skills, strategies, and emotions could all be used to enhance confidence (Short, Monsma, et al., 2004). That is, different athletes used the same image for different functions, and a single image had multiple functions for a single athlete (see also Short, Zostautas, et al., 2006). This finding that an image could be used for more than one function was substantiated by many (Callow & Waters, 2005; Calmels et al., 2003; Fish et al., 2004; Nordin & Cumming, 2005; Ross-Stewart & Short, 2009; Short et al., 2002). Thus, it would be imperative to ask additional questions regarding imagery meaning and outcome.

Other ideas for descriptive research relate to the “how” part of the applied model. Imagery characteristics like modality, perspective, angle, agency, deliberation, speed, duration, frequency, and color can all be explored (Moritz, 2023a). As for the “who” part of the applied model, it is likely that imagery use varies according to competitive level, experience, skill level, gender, age, etc. We recommend keeping descriptive research simple – delimited to one characteristic – like “At what speed do esports athletes use imagery?” This research question could be replicated using different genres of games (fighting games, racing games, sports games, digital card games, real-time strategy games, first person shooter games, third person shooter games, multiplayer online battle arena games [MOBAs], etc.).

Just as a diverse range of game genres fall under the umbrella of “esports,” so too can players’ practices of imagery vary widely. MOBAs such as League of Legends and tactical shooters such as Counterstrike are team-based by convention, but fighting games such as Street Fighter are almost exclusively solo efforts. In their articles, Vealey and Wright (2023) and Moritz (2023b) highlighted differences between individual and team confidence-building in esports imagery and such a distinction can offer intra-game differences of results (focusing on an individual team member’s imagery as opposed to a shared team visualization within a given esport), but differences across esports genres merit further study. How, for instance, might solo players of fighting games, real-time strategies, and digital card games differ in their imagery practices from players of cooperative team games such as MOBAs, tactical shooters, and team-based sports sims such as Rocket League? How does an individual player of Rocket League or Smash Bros. differ in their imagery practices when moving from a solo competitive (singles) format to a team-based one (doubles, etc.) – or vice-versa? For that matter, how do players who compete as individuals but share a team with others differ in how they use imagery? Teams such as Channel Fireball in Magic: The Gathering or Golden Guardians in Smash Bros. may or may not engage in imagery practices differently when they practice together than when they compete individually.

Explanation

Explaining why people use imagery is the next goal. To progress beyond descriptions of imagery use, the creation or revision of valid and reliable imagery-related measures is needed. The descriptive studies mentioned above set up the content for most imagery use questionnaires. Measures like the Sport Imagery Questionnaire (SIQ: Hall et al., 1998), the Exercise Imagery Questionnaire (Hausenblas et al., 1999) and the Dance Imagery Questionnaire (Nordin & Cumming, 2006) were created and used extensively to examine the relationships among imagery use and many different outcomes (e.g., performance, confidence, anxiety; for reviews see Cumming & Williams, 2013; Martin et al., 1999; Short, Ross-Stewart, et al., 2006). Similarly, researchers adapted these measures to look at how others used imagery – like coaches (e.g., Ross-Stewart et al., 2014; Short, 2012; Short et al., 2005, Short et al., 2007) and athletic trainers (Monsma et al., 2011).

The main criticism of this line of research was the confounding of imagery content and function in the measures used (see Short, Monsma, et al., 2004; Short, Ross-Stewart, et al., 2006). These measures were used to assess the frequency with which athletes use certain images (“what”) based on the assumption that these images were reflective of certain functions (“why”) (Murphy et al., 2006; Short, Monsma, et al., 2004). Abma et al. (2002) stated that a limitation of the SIQ is that it does not tap into the athletes’ perception of the purposes and goals of each type of imagery, and it assumes and requires that imagery content can be neatly classified into one of five categories. In other words, they recognized that the SIQ did not explain or take into account the athletes’ perceptions of the functions of the images and that there may be more imagery “functions” than the five on the SIQ. Furthermore, studies on the direction of the images on these measures showed that some of the items were perceived by athletes as debilitative (or harmful or hurtful to the intended outcome) (e.g., Ross-Stewart & Short, 2009; Short, Monsma, et al., 2004 and ineffective Weinberg et al., 2003). Advances were made to clarify the meaning of the data gathered by these measures – that is, to explore how often athletes used imagery (frequency), why they used an image (function) and what the outcome of the image was (positive or negative/help or hurt performance/facilitative or debilitative/effective or not effective).

Understanding the growing pains of how imagery was done in sport, exercise, dance and rehabilitation settings is important for new imagery research in esports. The key to effective measurement is to carefully create the measures for a desired purpose and to label the measures accordingly. For example, developing a measure asking esports athletes to rate how often they use a particular image could tap into the “most popular images among esports athletes” type of questionnaire. But implying that certain images serve a confidence-boosting function would have to be corroborated by another question asking “why” the images are used. It seems messy and complicated, but this method is what Ross-Stewart and Short (2009) did to examine which images were most effective for building, maintaining and regaining confidence in sport. They did not make the assumption that the image content was representative of a specific function; instead, they tied the content to a function: “how often do you use this image to build your confidence?” These types of results (i.e., trends that a specific image was associated with a particular function and/or outcome of imagery) would be valuable for designing interventions for practical and research purposes.

Explanatory research may involve determining causation using experimental designs. The basic research question is “what causes the behavior?” and translated to imagery research, the question typically involves researchers trying to understand how imagery works. How can just seeing something in one’s mind actually help accomplish these things? A simple answer is that we can generate information from memory that is essentially the same as an actual experience and consequently, imaging events can have an effect on our nervous system similar to that of real, or actual, experience (our brains can’t tell the difference between “real” and “imagined” stimuli; Weinberg & Gould, 2019). It is beyond the scope of this article to describe the explanations for how imagery works, but there are five popular theories (psychoneuromuscular theory, symbolic learning theory, bioinformational theory, triple code model and psychological explanations). With respect to future research in esports, it is likely that imagery operates in the same ways.

Instead, looking at the relationships among variables using mediation, moderation, path analysis and the like might be more viable research endeavors. For example, does imagery increase confidence which in turn increases performance? Experimental research looking at the effectiveness of variables related to imagery interventions would also be appropriate – for example, are imagery scripts more effective when recorded and listened to in male or female voices?

Prediction

When we have observed with some regularity that two behaviors or events are systematically related to one another, we can use that information to predict whether an event or behavior will occur in a certain situation – and to intervene if necessary. There is considerable research linking imagery use to multiple cognitive, behavioral and affective outcomes in sport, exercise, dance and rehabilitation settings (for reviews see Cumming & Williams, 2013; Martin et al., 1999; Short, Ross-Stewart et al., 2006). It is very likely that these relationships, such as the relationship between imagery use and confidence, will be the same in esports.

Intervention (Control and changing behavior)

Once we are able to describe, explain and predict behavior, we are in a position to control or change behavior through intervention. For example, if we know that certain competition sites trigger anxiety responses for esports athletes, then we can try an imagery script designed to reduce anxiety in these settings. One of the most popular areas of study has how to use imagery to increase confidence (or efficacy) (for a comprehensive review see Feltz et al., 2008). Investigating imagery intervention characteristics like content, duration and frequency are also important. Imagery interventions have varied from single sessions that are under 1 min to longer training like two to three times a week for 12 weeks. Discovering effective imagery interventions to control debilitative behaviors and to facilitate positive ones in various situations is exciting. Behavior change models can be applied as well – for example, how imagery fit into the Transtheoretical Model was considered by Short, Hall, et al. (2004), and Leffingwell et al. (2001) considered how the TTM could be useful for developing interventions according to the stages of change.

Unique considerations

Differentiating between direct and indirect images may be important for esports imagery research. Sports imagery research is usually centered on images of oneself where imagery is a form of mental practice that enables rehearsal of skills, situations and feelings in oneʼs mind (Nordin & Cumming, 2005). However, in some settings, like dance, images are labeled as indirect because they do not directly depict skills and situations but instead involve external objects that have a relationship to a motor skill or idea (Short et al., 2001). For example, a ballerina might image herself being a swan for a performance of Swan Lake. Students may be instructed to image the power of a kangaroo jumping to prepare oneself to jump as high as possible, or to image the red line of a thermometer rising rapidly to the top to increase one’s energy level (or dropping for a decrease). The objective of metaphorical images is to enhance the quality of movement by relating it to the characteristics of comparable things. Such metaphorical images complement verbal instructions and help people with affective, behavioral or cognitive changes. However, metaphorical images might be used in different ways in esports, especially in fantasy games.

Studies of imagery would also benefit from examining the potential slippage between the perspective of the player and the perspective of their in-game avatar. That is, to what extent do esports players using imagery take the perspective they would in the chair on competition day, and to what extent does their imagery place them in the player-character’s perspective instead? This distinction may seem trivial for first-person shooters, but it potentially becomes more complex in fighting games, MOBAs, and sports sims. Existing research such as Callow and Roberts (2010) discusses athletes’ imaging in third person; perhaps esports players who already see their character in third person reap benefits from reorienting their perspective to first person at the site of their in-game avatars?