This article was downloaded by: [North Carolina State University]On: 19 August 2013, At: 21:17Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

Research Quarterly for Exercise and SportPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/urqe20

Visual Search Strategy, Selective Attention, andExpertise in SoccerA. M. Williams a & K. Davids ba School of Human Sciences, Liverpool John Moores University, USAb Department of Exercise and Sports Science, Manchester Metropolitan University, USAPublished online: 08 Feb 2013.

To cite this article: A. M. Williams & K. Davids (1998) Visual Search Strategy, Selective Attention, and Expertise in Soccer,Research Quarterly for Exercise and Sport, 69:2, 111-128, DOI: 10.1080/02701367.1998.10607677

To link to this article: http://dx.doi.org/10.1080/02701367.1998.10607677

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) containedin the publications on our platform. However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor and Francis shall not be liable forany losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use ofthe Content.

This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Research Quarterly for Exercise and Sport©1998 by the American Alliance for Health,Physical Education, Recreation and DanceVol. 69, No.2, pp. 111-128

Visual Search Strategy, Selective Attention, and Expertisein Soccer

A. M. Williams andK. Davids

This research examined the relationship between visual search strategy, selective attention, and expertise in soccer. Experienced (n= 12) and less experienced (n = 12) soccerplayers moved in response tofilmed offensive sequences. Experiment 1 examineddifferences in search strategy between the two groups, using an eye movement registration system. Experienced players demonstratedsuperior anticipation in 3-on-3 and l-on-I soccersimulations. There were no differences in search strategy in 3-on-3 situations.In l-on-I simulations, the experienced players had a higher search rate, involving morefixations of shorter duration, and fixatedfor longer on the hip region, indicating that this area was important in anticipating an opponent's movements. Experiment 2examined the relationship between visual fixation and selective attention, using a spatial occlusion approach. In 3-on-3 situa­tions, masking information ''Pick up" from areas other than the ball or ball passer had a more detrimental effect on the experi­enced players' performances, suggesting differences in selective attention. In l-on-L situations, occluding an oncoming dribbler'shead and shoulders, hips, or lower leg and ball region did not affect the experienced players' performances more than the lessexperienced group. The disparities in search strategy observed in Experiment 1 did not directly relate to differences in informationextraction. Experiment 3 used concurrent verbal reports to indicate where participants extracted information from while viewing3-on-3 sequences. Experienced players spent less time attending to the ball or ball passer and more time on other areas of thedisplay. Findings highlight the advantages of integrating eye movements with more direct measures of selective attention.

Key words: perceptual skill, team games

Con temporary research examining skill-based differ­ences in visual search strategy in sport has high­

lighted important discriminating characteristics betweenexperts and novices (for a review, see Williams, Davids,Burwitz, & Williams, 1993). For example, expert per­formers show systematic differences in the location ofocular fixations across the available features of the dis­play, suggesting enhanced selective attention processes(e.g., Ripoll, Kerlirzin, Stein, & Reine, 1995; Vickers,1992; Williams, Davids, Burwitz, & Williams, 1994). More­over, although findings are equivocal, differences havebeen observed in search rate, with experts typically us-

Submitted: January 6, 1997Accepted: September 22, 1997

A. M. Williams is with the School of Human Sciences at LiverpoolJohnMoores University. K. Davids is with the Department ofExercise andSports Science at Manchester MetropolitanUniversity.

ROES: June 1998

ing a more efficient search pattern involving fewer fixa­tions of longer duration (e.g., Goulet, Bard, & Fleury,1989; Helsen & Pauwels, 1993; Ripoll et al., 1995). Thesedifferences are assumed to be indicative of the expert'smore refined perceptual strategy. Experts have a moreextensive task specific knowledge base, which can beused to interpret events encountered in circumstancessimilar to those previously experienced (see Anderson,1983; Starkes & Allard, 1993). These knowledge struc­tures direct the performer's search strategy towardsmore pertinent areas of the display based on situationalprobabilities (i.e., expectations) and the more effectiveprocessing of contextual information (see Williams,Davids, & Williams, in press).

Although these studies have been successful in iden­tifying important discriminating characteristics, thereare a number of criticisms. Almost without exception itis assumed that visual orientation, as implied from eyefixation characteristics, is directly related to visual atten­tion and information extraction (see Abernethy, 1988;Williams et aI., 1993). However, it is possible that targetobjects in the environment may be fixated without infor-

111

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams andDavids

mation extraction (e.g., Papin, Metges, &Amalberti, 1984;Stager & Angus, 1978; Kundel, Nodine, & Toto, 1984).Thishas been referred to as the difference between "looking,"which implies fixation on the fovea, and "seeing," whichintimates the active pick up and processing of informa­tion (Van der Heijden, 1986; Neumann, Van derHeijden, & Allport, 1986). Furthermore, it appears thatattention can be relocated in the visual field without dis­tinctive eye movements to change the point of fixation(see Remington, 1980; Sanders & Houtmans, 1985;Shulman, Remington, & McLean, 1979). Subjects maylook at, or foveate, an object but extract information fromthe periphery. Also, these shifts in attention can occurwithout the loss ofinput information normally associatedwith saccadic eye movements, possibly resulting in par­ticipants giving priority to information extraction via theparafovea and periphery in dynamic environments(Abernethy, 1985, 1988). This argument is supported byan increasing body of evidence which suggests that in­formation processed through peripheral vision plays animportant role in perceptuomotor performance (e.g.,Davids, 1984; Paillard, 1982; Williams, Davids, Burwitz,& Williams, 1992).

These criticisms imply that more direct measures ormanipulations of information pick up, such as concur­rent verbal reports or spatial occlusion, should be usedin conjunction with eye fixation data when assessing dif­ferences in search strategy. Because eye movement reg­istration techniques only provide information regardingfoveal orientation, concurrent verbal report and eventocclusion procedures can clarify the relationship betweenvisual fixation and information extraction and help todevelop our understanding of the role of nonfovealstimulation in the visual search process (for a more de­tailed review, see Williams et aI., 1993). Despite theseadvantages, fewstudies have attempted to use these meth­ods to address some limitations with eye movement reg­istration techniques (for exceptions, see Abernethy &Russell, 1987a, 1987b; Abernethy, 1990).

Further criticisms include the use of unrealisticstimuli involving static slide presentations and smallscreen displays. Previous studies have tended to use penand paper or verbal response measures rather than at­tempting to develop more realistic testing conditionswhich require subjects to move in response to action se­quences (see Williams et aI., 1992). These simplistic orartificial laboratory tasks may negate the experts' advan­tage, cause them to function differently by denying themaccess to information they would normally use, or causethem to use different information to solve a particularproblem (Abernethy, Thomas, & Thomas, 1993). Con­sequently, there is a need to develop meaningful andrealistic protocols which closely replicate the performer'shabitual environment.

Moreover, few studies have examined visual searchstrategy within dynamic "open play" simulations in sport,

112

in which participants are presented with emerging of­fensive or defensive patterns of play. Due to the difficul­ties involved in producing realistic film displays whichsimulate the performer's normal view of the action, mostresearch has concentrated on relatively "closed" skillssuch as the tennis serve, the penalty kick in soccer, orputting in golf (e.g., Goulet et aI., 1989; Tyldesley,Bootsma, & Bomhoff, 1982; Vickers, 1992). An excep­tion is a recent study by Williams et aI. (1994) whichexamined differences in visual search strategy using l I­on-Ll soccer action sequences filmed from a defender'sperspective. The results indicated that experienced de­fenders were less inclined to "ball watch" and showedgreater awareness of the positions and movements ofplayers"off the ball." Further differences were noted insearch rate, with experienced players exhibiting morefixations of shorter duration.

The higher search rates demonstrated by the expe­rienced soccer players contradicted previous research insport (e.g., Goulet et aI., 1989; Helsen & Pauwels, 1993;Ripoll et aI., 1995). Helsen and Pauwels (1993) showedthat expert soccer players used fewer fixations oflongerduration when presented with simulated offensive se­quences involving a restricted number of players (i.e.,"set play" situations). Theoretically, because the saccadiceye movements which separate visual fixations are inac­tive periods of information processing, a more selectiveand efficient strategy should be characterized by fewerfixations oflonger duration (Williams et aI., 1993). Ex­perts would be expected to have lower search rates dueto a reduced information processing load or becausethey require less sensory input to create a coherent per­ceptual representation of the display (Abernethy, 1990).This expectation has not always been corroborated byresearch findings from the sport and exercise sciences.The inconsistency is due, in part, to the difficulty in com­paring directly between research studies because ofdif­ferences in the operational definition of a fixation andin the sensitivity of the eye movement system employed(Abernethy & Russell, 1987b). Further problems arisebecause of the nature and difficulty of the task, the typeofvisual display presented to observers, and the experi­mental description and instructions given prior to test­ing (for a more detailed review, see Abernethy, 1988).

However, this contradiction may also arise becauseparticipants implement different search rates in differ­ent situations. For example, games players may be char­acterized by higher search rates when attempting torecognize patterns of developing play, such as a team'sattacking or defensive structure, whereas lower searchrates may be employed in more specific contexts involv­ing a restricted number of players. Thus far, few studieshave examined how search strategy alters as a functionof task constraints. This is because existing research hastended to employ a "shot gun" approach, preferring toexamine performance on a single task rather than adopt-

ROES: June 1998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

ing a more pragmatic strategy in which the task con­straints have been manipulated as an independent vari­able (Abernethy et aI., 1993). When defenders areattempting to determine the opposition's general offen­sive structure, such as in the 1l-on-I 1 film sequences,higher search rates would be required to be aware of themovements and positions ofa large number of players.In these dynamic circumstances, the area ofplay may betoo large for defenders to rely on peripheral vision topick up information from teammates and opponents; in­stead players are constrained to move the eyes to fove­ate important areas of the display. In contrast, insituations involving a restricted number ofpotential in­formation sources (e.g., defensive 3-on-3 situations onthe edge of the penalty area in soccer), lower searchrates may be required, enabling players to use nonfovealretinal stimulation (i.e., parafovea and periphery) toextract task specific information. Similar arguments havebeen proposed by Ripoll (1991) who suggested the dif­ference between experts and novices is that the formerdirect their gaze to a position in which many events canbe viewed integratively during one single eye fixation(i.e., synthetic analysis), while novices gaze at eventsaccording to their chronological order of appearance(i.e., analytic analysis). It is therefore reasonable to hy­pothesize that the experts' synthetic search process is aproduct of their greater reliance on peripheral vision toextract task-specific information. In team sports such assoccer, experts may focus central vision on the ball orthe player in possession of the ball while using periph­eral vision to scan the display for relevant information.Although this argument has been proposed by numer­ousauthors (e.g., Abernethy, 1991; Ripoll, 1991), it hasnot, as yet, been verified empirically. Evidence is re­quired to clarify this issue, because it has important im­plications for theoretical development and trainingvisual search strategy in sport.

This research had several objectives. First, we exam­ined differences in anticipation and visual search strat­egy during defensive 3-on-3 and l-on-I situations insoccer. These are typical training situations which mayform the context for players to learn to use eye move­ments to pick up task-related information. It was hypoth­esized that, because of their enhanced soccer specificknowledge base, experienced soccer defenders woulddemonstrate superior anticipation and more pertinentvisual search strategies. Second, we examined the rela­tionship between visual fixation and selective attentionin these 3-on-3 and l-on-I situations, using spatial occlu­sion and concurrent verbal report techniques. We pre­sumed that visual fixation would not be directly relatedto selective attention in these situations because of theinvolvement of the parafovea and periphery in the vi­sual search process. Third, we attempted to examinewhether similar or different scan patterns would be ob­served in small-sided situations (i.e., 3-on-3, I-on-I) com-

ROES: June 1998

Williams andDavids

pared with previous research undertaken using l l-on­11 simulations. Weconsidered that the nature of the taskwould be an important constraint on the type of searchpattern used by team games players. Specifically, we hy­pothesized that participants would use a less extensivesearch pattern, characterized by lower search rates, insmall-sided situations because of an increased role forperipheral vision in picking up task specific information.A related question was whether these relationships al­tered as a function of task experience. Finally, the re­search improved on previous methodology by using arealistic "life size" film display and movement-based re­sponse measures to assess differences in anticipation andvisual search strategy in sport. We felt that this more life­like task would maintain situation specificity and expe­dite any conceivable differences between theexperienced and less experienced players.

Experiment lA: Anticipation and Visual SearchStrategy in 3-on-3 Situations

Method

Participants

Participants were 12 experienced (M = 24.0 years,SD = 4.1) and 12 less experienced male soccer players(M = 23.3 years, SD = 4.0). The experienced players hadbeen playing soccer for 13.4 years, including an averageof754 (SD = 179.5) competitive matches. They included5 professional soccer players and 7 semiprofessional play­ers. The less experienced group had been playing soc­cer for an average of4.1 years (SD = 2.5) with an averageof65 matches (SD = 52.7). They were all recreationalplayers. Participants gave their informed consent priorto taking part in these experiments. This research wasconducted according to the guidelines established by theAmerican Psychological Association (1982).

Test Film

Participants were presented with 20 offensive soccersequences. These involved 3-on-3 situations in whichthe participants were required to imagine themselves asa covering defender or "sweeper" playing in a centralposition between the penalty area and center circle.Each sequence included two central defenders markingtwo offensive players and a defensive midfield playermarking an offensive midfield player. The film clipslasted approximately 6 s and included an offensive pat­tern ofplay ending with one of the following outcomes:(1) a pass being made to the participant's right or leftside; (2) the ball apparently being played over the

113

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams and Davids

participant's head into the space behind; or (3) an of­fensive player dribbling the ball directly toward the par­ticipant. An intertrial interval of 6 s was built into thefilm construction.

The offensive patterns were selected from actualsoccer matches and then realistically simulated by skilledoffensive and defensive players. The simulation wasfilmed at eye level (1.7 m) and from a position behindthe players (6 m) using a video camera (Panasonic F-15),an 8-mm focal length lens, and a SVHS video recorder(Panasonic AG7450; Panasonic, Osaka, Japan). This po­sition provided a visual display most representative ofasweeper or covering defender's view ofthe action. Twelvedifferent soccer players participated in the filming ses­sion, thus providing a different combination of offen­sive and defensive players every trial. Three experiencedsoccer coaches viewed the offensive sequences indepen­dently to ensure that each film clip was realistic and rep­resentative ofactual game play. Only those film clips onwhich the coaches were in complete agreement wereused in the test film.

Apparatus

An Applied Science Laboratories 4000SU eye move­ment registration system (Applied Science Laboratories,Bedford, MA)was used to collect visual search data. Thisis a video-based monocular system which measures eyeline ofgaze with respect to a helmet-mounted scene cam­era. The system works by detecting two features, the pu­pil and the corneal reflex (reflection of a light sourcefrom the surface of the cornea), in a video image of theeye. The relative position of these features is used to com­pute visual gaze with respect to the optics. Displacementdata from the left pupil and cornea were recorded by asmall camera, processed by computer, and superimposedas a cursor on the scene camera image to highlight thepoint of gaze. This image was then recorded for furtheranalysis using a video camera. The data were then sub­jected to a frame-by-frame analysis using a UK standardvideo recorder (Panasonic AG7330; Panasonic, Osaka,Japan) at 50Hz. The accuracy of the system (i.e., the dif­ference between true eye position and measured eyeposition) was ± 1°visual angle. System precision (i.e., theamount of instrument noise in the eye position measurewhen the eye is perfectly stationary) was better than Y2°in both horizontal and vertical directions (for a moredetailed review of the apparatus, see Applied ScienceLaboratories Eye Tracking Systems Handbook'),

Procedure

Prior to presentation of the test film, participants'choice reaction time (CRT) was measured. They werepresented with the same view of the soccer field in thetest film but with no players included in the display. Fol-

114

lowing a random foreperiod, participants responded asquickly and accurately as possible, when a stimulus waspresented. The stimulus was a red circle presented inthe right, left, top, or bottom of the screen. The partici­pants stood on a central pressure pad and respondedby stepping on to the response pad corresponding to theposition of the red circle (i.e., right, left, front, or backresponse pad). These response pads were positioned atright angles, 1 m away from the central pressure pad onwhich the participants were standing. Participants werepresented with 3 practice trials and 18 test trials. CRTwas measured as the time from the stimulus presenta­tion to the completion of the participant's response,recorded using a series of timing circuits and a com­puter", This task served to familiarize participants withthe response in the anticipation test and provided thebaseline measure ofCRT used as a covariate in the sub­sequent performance analysis.

The test procedure was then explained and the hel­met-mounted optics fitted on the participant's head. Theeye movement recorder was calibrated using a nine-pointreference grid so that the recorded indication of fixa­tion position corresponded to the participant's visualgaze. Previous research (e.g., Williams et al., 1994)showed that the system required only occasionalrecalibration and was checked only after the practice tri­als and following presentation of the first 10 test trials.Also, participants were asked to fixate on a marker posi­tioned in the center of the projected film image imme­diately after completing their response, enabling a rapidcalibration check prior to each trial. All participants re­ported that the helmet was comfortable and did not in­terfere with performance.

Following initial calibration of the equipment, par­ticipants received six practice trials to ensure their fa­miliarity with the testing procedure. In particular, it wasstressed that they should anticipate pass destination asquickly and accurately as possible. No further instruc­tions were given, as search strategy can be modified byexperimental instructions (Yarbus, 1967). The test filmwas projected onto a 3.5-m x 3-m screen using a videoprojection system (GEC Imager LCD 15E; GEC, NewYork, NY). Participants stood 5 m away from the screenso that the film image sub tended a visual angle of ap­proximately 40° in the horizontal and 35° in the verti­cal direction. This provided a realistic environment,with players' images being presented "life size" onscreen. Participants viewed each pattern of playas itdeveloped and responded as quickly and accurately aspossible by moving right, left, forward, or backward tosimulate the interception of the pass. They were re­quired to step on the same response pads as in the CRTexperiment. Immediately following initiation of their re­sponse, the film was occluded to prevent participantsgaining feedback on task performance (maximum oc­clusion time = 10 ms).

ROES: June 1998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Analysis

Four response measures were obtained from theanticipation test:

Initiation Time (IT). This was the time from the startof the film clip to the initiation of the participant's re­sponse (in ms). The initiation of response was recordedwhen the participant lifted his foot off the central pres­sure pad.

Movement Time (MT). This was the time from the ini­tiation of the participant's movement to responsecompletion (in ms). It was the time from the participantlifting his foot off the central pressure pad and steppingon to one of the four response pads positioned on thefloor.

Response Time (RT). This was the time from the startof the film clip to the completion of the participant'sresponse (in ms).

ResponseAccuracy (RA).This was obtained by compar­ing the participant's response to the actual pass destina­tion (in %).

Because of between-group differences in CR"P andthe relationship between speed (IT, MT, RT) and accu­racy (RA) measures," a one-way multivariate analysis ofcovariance (MANCaVA) was used to analyze perfor­mance scores. In this analysis, Group (experienced-lessexperienced) was the between-subjects variable, CRT thecovariate, and IT, MT, RT, and RA the four dependentvariables.

Analysis of Visual Search Data

Fixation Order. This was the search sequence ,or pat­tern, used by the participants. Previous research has in­dicated that the most important search pattern whenanticipating pass destination in l l-on-11 situations is toalternate fixations between the player in possession oftheball and other potential sources of information in thesimulation (see Williams et aI., 1994). This search strat­egy is regarded as advantageous in such a highly dynamiccontext, because it enhances the participant's awarenessofother players' positions and movements, thus increas­ing their appreciation of possible passing options (Will­iams et aI., 1994). Consequently, the number of times pertrial that participants alternated their fixations betweenthe player in possession of the ball, some other area ofthe display, and then back to the player in possession ofthe ball was taken as the dependent variable. These datawere analyzed using a one-way analysis of variance(ANaVA) in which Group (experienced-less experi­enced) was the between-subjects factor.

Fixation Location. The dependent variable fixationlocation referred to the areas of the display on which theeye fixated when predicting pass destination. The screenwas divided into four areas: players positioned on theright of the screen; players on the left side of the screen;the upper body (i.e., above the waist) and the lower body

ROES: June 1998

Williams and Davids

(i.e., below the waist and including the ball) of the playerin possession of the ball. This analysis provided percent­age values for the mean time spent per trial within eachlocation. These data were analyzed using a factorialANaVA in which Group (experienced-less experienced)was the between-subjects factor and fixation location(player position right-player position left-upper body­lower body and ball) the within-subjects variable.

Search Rate.Search rate was represented by the meannumber ofvisual fixations and the mean fixation dura­tion per trial. Mean fixation duration was the averageofall fixations that occurred during the film trials. A fixa­tion was defined as a condition in which the eye re­mained stationary for a period equal to, or in excess of,6 video frames (120 ms). Mean fixation duration and thenumber of fixations were analyzed using separate one­way ANavAs in which Group (experienced-less experi­enced) was the between-subjects factor.

Results

Anticipation Test

MANCaVA showed a significant difference betweenthe two groups on the anticipation test, Wilks' A = .44,F(4, 18) = 5.54, P< .01. The experienced players werebetter at anticipating pass destination than their less ex­perienced counterparts. Follow up discriminant analysisshowed that the IT variable (standard coefficient = -8.41)more clearly distinguished between groups than the RT(standard coefficient = 5.96), RA (standard coefficient =2.11), and MT variables (standard coefficient = -.44).Thiswas supported by separate univariate analysis of the fourdependent variables, which showed a significant differ­ence on the IT, F(I, 21) = 7.36,p < .05 (effect size [ES] =1.09), and RTvariables only, F(I, 21) = 7.68,p < .05 (ES= 1.06). Table 1 displays the mean group performancescores across the dependent variables.

Visual Search Data

Fixation Order. ANaVA showed no significant differ­ences between the two groups in search order, F( 1, 22)= .01,p > .05 (ES = .03). There were no differences inthe frequency of alternation of fixations between theplayer in possession of the ball and other areas of thedisplay. The mean frequency of this search pattern pertrial was similar for the experienced (M = 1.03, SD = .39)and less experienced (M = 1.04; SD = .20) participants.

Fixation Location. Factorial ANaVA revealed no sig­nificant main effect for group, F(I, 22) = .08, P> .05.An initial Mauchly's Sphericity test revealed a violationof the sphericity assumption for repeated measuresANaVA, X2(5) = 83.17,p < .001. Consequently, the lo­cation main effect and the Group x Location interaction

115

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams andDavids

were analyzed using a MANOVA-type procedure as rec­ommended by Schutz and Gessaroli (1987). This analy­sis indicated that no Group x Location interaction, Wilks'A = .96, F(3, 66) = .04, P> .05. However, a significantdifference was shown for the location main effect, Wilks'A = .05, F(3, 66) = 24.96, P< .001. Post hoc Scheffe analy­sis showed that participants spent most time fixating thelower body of the player in possession of the ball or theball itself, p < .001. Also, more time was spent fixatingthe player's upper body and the right side of the screencompared with the left side of the display, p< .05. Thesedifferences are represented in Figure 1.

Search Rate. Separate one-way ANOVAs showed nosignificant differences between groups in mean fixationduration, F(l, 22) = 3.15, p » .05 (ES = .72), or in themean number of fixations per trial, F(l, 22) = 0.21, p>.05 (ES = .19). The mean fixation duration for the ex-

perienced players was 865.83 ms (SD= 145.22) comparedwith 973.50 ms (SD = 151.67) for the less experiencedparticipants. Similarly, the experienced players em­ployed an average of 4.17 (SD = .62) fixations per trialcompared with 4.02 (SD= .90) for their less experiencedcounterparts.

Discussion

The results highlighted the experienced soccer play­ers' superior anticipatory performance. They demon­strated significantly faster ITs and RTsbut were no moreaccurate than the less experienced players. The visualsearch data showed no differences between groups inthe allocation of fixations to display regions, search or­der, or search rate. Because the experienced players re-

Table 1.Meangroup performance scores for experienced and lessexperienced players onthe 3-on-3 anticipation test

Group CRT (rns] IT(ms) MT(msl RT(msl RA(%lM SO M SO M SO M SO M SO

Experienced(n= 12) 715.0 61.7 3,906.2 292.8 297.5 29.5 4,203.7 295.1 81.3 10.9

Less experienced(n= 12) 638.3 56.1 4,256.5 347.9 280.0 32.2 4,536.5 332.3 78.5 20.8

Note. CRT =choice reaction time;IT=initiation time;MT=movement time; RT =response time; RA =response accuracy; M=mean; SO =standard deviation.

70..-----------------------------------,

60

50

40

30

20

10

o+----'----

Experienced Less Experienced

IOBPA .BPB .Left ORight IFigure 1. Mean distribution of fixation locations as a percentage of total trial timeper group in the 3-on-3 situations. (SPA =upper body ofplayer in possession of the ball; BPB =lower body of player in possession of the ball including the ball; LEFT =left side of the screen;RIGHT =right side of the screen.)

116 ROES: June 1998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

sponded more quickly to the film sequences, the sug­gestion is that there were discrepancies between infor­mation pick up and visual search strategy, as impliedfrom foveal orientation to the display. The experiencedplayers' superior anticipation may depend less on howthe display is overtly searched through eye movementsand more on their ability to extract better quality infor­mation per fixation or their enhanced ability to extracttask specific information through peripheral vision. Thisdistinction between visual orientation and informationextraction highlights the limitations in using eye move­ment recording alone to provide definitive informationabout selective information pick up. Clearly, more directmeasures of information extraction and cue depen­dence, such as spatial occlusion or concurrent verbalreports, are also needed to isolate the perceptual strat­egies employed by performers (cf., Abernethy & Russell,1987a,1987b).

Finally, there were no differences in fixation dura­tion or the number of fixations employed. Previous re­search involving Ll-on-l l situations (see Williams et al.,1994) was contradicted suggesting that lower search ratesmay be more effective in these 3-on-3 situations. The ini­tial hypothesis, that lower search rates may be preferablebecause of the increased role ofperipheral vision in pick­ing up task specific information, was supported. Furtherevidence to support this conclusion is presented in Ex­periments 2 and 3.

Experiment 1B:Anticipation and Visual SearchStrategy in 1-on-1 Situations

Method

Participants and Test Film

Participants were the same as those in the 3-on-3condition. Participants were presented with 20 offensivesoccer sequences involving l-on-l simulations in whichparticipants were required to imagine themselves as achallenging defender on the edge of the penalty area.Each sequence involved an offensive player dribbling theball directly toward the participant on screen. The par­ticipant was required to anticipate quickly and accuratelywhether the attacker would attempt to dribble past himon his right or left side. Participants were asked to moveas if they were about to tackle or block the attacker. Eachfilm clip lasted approximately 4 s. An intertrial intervalof 6 s was built into the film construction.

The action sequences were filmed from a front-onposition such that the attacking player was dribbling di­rectly toward the camera. This position provided a visualdisplay most representative of a defender's view of the

RaES: June 1998

Williams andDavids

action. While filming the sequences, the attacking play­ers were asked to imagine that the camera was a de­fender they had to dribble the ball past. No restrictionswere placed on the dribblers with regard to making faint­ing movements to mislead the participants. The drib­blers were highly skilled and included four right- and twoleft-footed players, thus providing some variety in drib­bling style and technique. Three experienced soccercoaches viewed the film sequences to ensure they wererealistic and representative of actual game play. Onlythose film clips on which the coaches completely agreedwere used in the test film.

Apparatus and Procedure

The apparatus was the same as in the 3-on-3 condi­tion. Prior to presentation of the test film, participants'CRT was measured. This involved using a similar test asin the 3-on-3 condition but with only two response al­ternatives. In this test, the stimulus was presented on theright or left side of the screen only. Participants stoodon a central pressure pad and were required to respondby stepping quickly and accurately on to the right or leftresponse pad, as appropriate. Participants were pre­sented with 3 practice trials and 18 test trials. CRT wasmeasured as in the 3-on-3 condition.'

The habituation and calibration procedures werethe same as the 3-on-3 condition. The test film was thenpresented using the same video projector and screen asin the 3-on-3 condition. Participants were required tostep on the right or left response pad as appropriate andthe test film was occluded immediately after the initia­tion of movement. The entire test session lasted approxi­mately 30 min.

Analysis--Dependent Variables and Visual Search Data

The same four dependent variables recorded dur­ing the 3-on-3 condition were measured. These variableswere analyzed as in the 3-on-3 condition."

Fixation Order. Fixation order was initially analyzeddescriptively through a series of transition matrices.These indicated the number of occasions a given fixa­tion location was immediately preceded or followed byfixations from each of the other display areas. Follow­ing an inspection of these matrices, the dependent vari­able fixation order was taken as the number of times pertrial that participants alternated their fixations betweenthe area below the attacker's knees, including the ball,the area between the knees and midchest region, andthen back again to the ball or lower portion of thedribbler's body. These data were analyzed as in the 3­on-3 condition.

Fixation Location. Fixation location was obtained bydividing the screen into three areas: the area below theattacker's knees, including the ball; the attacker's torso

117

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams andDavids

(i.e., above the knees and below the shoulders); and theattacker's head and shoulders. Data were analyzed as inthe 3-on-3 condition.

Search Rate. This was analyzed as in the Son-S condition.

Results

Anticipation Test

MANOVA showed a significant difference betweenthe two groups on the anticipation test, Wilks' A = 0.48,F(4, 18) = 4.82, P< .01. The experienced players werebetter at anticipating the direction of an opponent'sdribble than their less experienced counterparts. Dis­criminant analysis showed that the IT variable (standardcoefficient = -30.88) more clearly discriminated betweengroups than the RT (standard coefficient = 28.70), MT(standard coefficient = -10.03), and RA variables (stan­dard coefficient = .89). However, separate univariateanalysis of the four dependent variables showed a sig­nificant difference on the RT, F(l, 21) = 4.55, P< .05(ES = .74), and RAvariables only, F(l, 21) = 7.88, P< .05(ES = 1.17). Table 2 shows the mean group performancescores across the dependent variables.

Visual Search Data

Fixation Order. ANOVA showed no significant differ­ences between the two groups in search order, F(I, 22)= 3.84, p » .05. However, the mean frequency values in­dicated that the experienced players (M = .28, SD= .20)alternated their fixation between the lower leg-ball re­gion and the area between the knees and midchest morethan the less experienced participants (M= .11, SD= .17)(ES = .94).

Fixation Location. Factorial ANOVA revealed no sig­nificant main effect for Group, F( 1, 22) = .43, p» .05, orfor the Group x Location interaction, F(2, 44) = 2.24, P> .05. However, a significant difference was shown forthe location main effect, F(2, 44) = 25.48, p< .0001. Posthoc Scheffe analysis showed that participants spent moretime fixating on the lower body of the offensive player

or the ball, p< .001. More time was spent fixating on thedribbler's torso (i.e., above the knees and below themidchest region) compared with the head and shoulderareas, p< .001. Although there were no significant dif­ferences in fixation location between groups, the expe­rienced players fixated longer on the area between thedribbler's knees and shoulders (M = 33.2%, SD = 21.4)compared with the less experienced group (M= 15.7%,SD = 13.6). Moreover, calculation of the effect size (ES= 1.08) showed this was a meaningful difference betweenthe two groups (see Cohen, 1992). The nonsignificantfindings may be explained by the relatively small groupsize and the high standard deviation values. These dif­ferences are represented in Figure 2.

SearchRate. Separate one-way ANOVAs showed a sig­nificant difference between groups in mean fixationduration, F(l, 22) = 4.32, P< .05 (ES = .85), and in themean number of fixations per trial, F( 1, 22) = 4.71, P<.05 (ES = .91). The experienced players had a lowermean fixation duration (M= 1,104.62, SD= 332.41) com­pared to the less experienced participants (M = 1555.0,SD = 673.60). The experienced players also employedmore fixations per trial (M = 2.60, SD = .83) than theirless experienced counterparts (M = 1.90, SD = .72).

Discussion

Findings showed that the experienced players werebetter at anticipating the direction of an opponent'sdribble. They had faster RTs and were more accurate intheir decisions compared to the less experienced group.Moreover, there were some interesting differences in vi­sual scanning behavior. First, the experienced playersspent more time (although not statistically significant)fixating on the area between the dribbler's knees andmidchest region (M = 33.5%; SD = 21.5) compared withthe less experienced group (M = 15.7%; SD= 13.5). Al­though the overall mean frequency values were low, dis­crepancies were evident in search order, with theexperienced players tending to alternate their fixationsmore frequently between the ball and hip region com­pared with the less experienced players. The area above

Table 2. Mean group performance scores for experienced and less experienced players onthe l-on-l anticipation test

Group

Experienced (n = 12)Less experienced (n = 12)

CRT [rns]M SO

524.0 48.9518.2 54.3

IT(ms)M SO

2,979.0 105.03,070.6 140.5

MT(ms)M SO

200.8 27.1216.7 49.4

RT(mslM SO

3,179.8 11 0.33,286.3 131.5

RA(%)M SO

92.5 7.576.8 17.4

Note. CRT =choice reaction time; IT=initiation time; MT=movement time; RT =response time; RA =response accuracy; M =mean; SO =standard deviation.

118 ROES: June 7998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams andDavids

the knees and below the midchest region seems impor­tant in anticipating an opponent's movements. Interest­ingly, other research has identified the hip area as animportant information source in anticipating the direc­tion ofsoccer penalty kicks. Tyldesley et al. (1982) showedthat when experienced soccer players were required toanticipate ball direction from slides of a player in the actof shooting at goal, 60% ofinitial fixations were directedat the hip region. Similarly, Williams and Burwitz (1993)reported that experienced goalkeepers focused on thehip region when attempting to determine the directionof a penalty kick. They suggested that the "opening" ofthe shooter's hips provided important information re­garding the placement of the penalty kick. It is possiblethat similar motion invariants are used by the experi­enced defender to anticipate the direction of anopponent's dribble. The opening of a right-footeddribbler's hips could suggest a move to the right, whereasmovement to the left may be characterized by a more"closed" or central orientation of the hips relative to thedefender. Alternatively, perhaps the experienced playersfocused on the hip region because of its proximity to thedribbler's center of gravity. When the dribbler movesright or left, there must be a displacement in the centerof gravity in the corresponding direction. This transfor­mation may provide the defender with important infor­mation regarding the direction ofan opponent's dribble.Focusing on the hip region may be more viable than at­tempting to pick up information from the dribbler'slower leg or shoulder areas. These areas are often usedby skilled dribblers to provide spurious information, thus

leading to false positives in the language of signal detec­tion theory. It is probably for this reason coaches gener­ally advocate that defenders focus on the ball to theexclusion of other display areas in these situations.

In contrast to the 3-on-3 situations, the experiencedplayers adopted a higher search rate when facing a drib­bler. They employed a search strategy which comprisedmore fixations (2.9 vs. 1.9) of shorter duration (1,104.6vs. 1,555.0 ms) than their less experienced counterparts.Thus, experienced players are characterized by highersearch rates, supporting previous research involving 11­on-ll simulations (Williams et aI., 1994). The task con­straints may necessitate that performers use foveal ratherthan peripheral vision to extract task specific informa­tion. Because the approaching dribbler takes up onlyaround 5-10° of their visual field, perhaps the performeris constrained to using foveal vision to pick up informa­tion from key parts of the body, resulting in a corre­sponding increase in search rate.

Experiment 2A: Visual Search Strategy andSelective Attention in 3-on-3 Situations inSoccer

This experiment examined the relationship betweenvisual search strategy and selective attention in 3-on-3and Lon-I situations, using a spatial or event occlusionapproach. The assumption is that if performance dete­riorates when a particular area or information source is

80 -y-------------------------------------,

40 .

70 .

0+----

30 .

50 .

20 .

60 .

10 _..

Experienced

I_Mid _Top o Bottom ILess Experienced

Figure 2. Mean distribution of fixation locations as a percentage of total trial time per group in the 1-on-1 situations. (MID = area betweenthe dribbler's knees and mid chest region; TOP =dribbler's head and shoulders; BOnOM =area below the dribbler's knees including the ball.)

ROES: June 1998 119

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams and Davids

occluded, then it can be inferred that this region pro­vides unique information that cannot be picked up else­where. The scale of performance decrement is linkedto the systematic removal ofspecific information sourcesvia spatial occlusion techniques (for a more detailed re­view, see Abernethy, 1985).

Method

Participants and Test Film

Participants were the same as in Experiment 1. Thetest film comprised 10 randomly selected action se­quences from Experiment 1. The order of presentationof these film clips was rearranged on a random basis tominimize order effects. Moreover, to further minimizethe possibility of any learning or familiarization effects,Experiment 2 was undertaken some 3 months after thecompletion of Experiment 1. To examine whether anylearning effect had been apparent, performance in thecontrol condition (E1) in this experiment (see Table 3)was compared with that observed under the same condi­tions in Experiment 1 (see Table 1). The results showedno improvement in performance for either group acrossthe two experiments, indicating that learning or famil­iarization effects were not apparent.

A spatial occlusion approach was used to obscurerelative amounts ofinformation pick up from areas otherthan the ball or ball passer. This was achieved by black­ing out selected areas of the display using a digital pro­duction mixer (Panasonic WJ-MX15; Panasonic, Osaka,Japan). The sequences were presented to participantsunder two randomly ordered conditions ofspatial occlu­sion, thus making a total of 20 film clips. In occlusioncondition E1, irrelevant display areas were masked byestablishing a narrow black border around the entireviewing image. As a result, the film image subtended aviewing angle of 35° in the horizontal and 30° in the ver­tical direction. Because this was a control condition tocompensate for any confounding effect arising from the

film disruption, care was taken not to obscure any infor­mation from the positions and movements of players.The second occlusion condition E2 involved masking allareas of the display other than the ball or ball passer.This was achieved by creating a viewing square that sub­tended a visual angle of approximately 6° in the hori­zontal and 5° in the vertical direction.

Procedure andAnalysis

The procedure was as in Experiment 1. To simplifythe analysis and because RT was a combination oflT andMT, only two dependent variables were included,namely: response time (RT) and response accuracy(RA). Because of the between group differences in CRT2and the relationship between speed (RT) and accuracy(RA) measures," a split plot MANCOVA was used in ana­lyzing group performance scores. In this analysis, Group(experienced-less experienced) was the between-subjectsvariable, viewing condition (E1-E2) the within-subjectsfactor, RT and RA the dependent variables and CRT thecovariate.

Results

MANCOVA showed a significant difference in thegroup, Wilks' A = .70, F(2, 20) = 4.17, p « .05, and view­ing condition main effects, Wilks' A = .25, F(2, 20) =

29.07, P< .0001. Also, the Group x Viewing conditioninteraction was significant, Wilks' A= .61, F(2,20) = 6.17,P< .01. Discriminant analysis for the group main effectshowed that the RT variable had a higher standard co­efficient (standard coefficient = 1.28) than the RA vari­able (standard coefficient = -.92). This was supported byunivariate analysis which showed a significant differenceon the RT variable only, F(l, 21) = 4.36, P< .05. More­over, discriminant analysis for the viewing conditionmain effect showed that the RA variable had a higherstandard coefficient (standard coefficient = -1.38) thanthe RT variable (standard coefficient = 1.28). However,

Table 3. Mean group performance scores for experienced and less experienced players under both E1 and E2 occluded viewingconditions onthe 3-on-3 anticipation test

E1 E2Group RT(ms) RA(%) RT(ms) RA(%)

M SO M SO M SO M SO

Experienced (n =12) 4,269.2 269.8 80.8 13.1 4,403.2 196.8 62.5 15.4Less experienced In =12) 4,563.9 276.1 77.5 12.2 4,605.2 268.4 70.0 15.9

Note. RT = response time; RA = response accuracy; E1 = occlusion of irrelevant display areas; E2 = occlusion of areas otherthanthe ball­ball passer; M=mean; SO =standard deviation.

120 ROES: June 1998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

univariate analysis revealed that both RT, F(1, 21) = 5.33,P< .05, and RA variables were significantly different, F( 1,21) = 13.36, P< .01. Discriminant analysis on the Groupx Viewing condition interaction showed that RA (-1.36)was more discriminating than the RT variable (standardcoefficient = 1.31). Separate univariate analysis revealedthat neither the RT, F(l, 22) = 1.49, p> .05, or the RAvariables were significantly different on the Group xViewing condition interaction, F(l, 22) = 2.35, P> .05.Post hoc Scheffe analysis showed that the experiencedplayers were more accurate under the El (M = 80.83%,SD = 13.1) compared with E2 viewing conditions (M =

62.5%, SD = 15.4), P< .05 (ES = 1.28). No differenceswere found in RT for the experienced players across thetwo viewing conditions, p » .05 (ES = .56). In contrast,there were no differences in RA (ES = .53) or RT (ES =

.15) for the less experienced participants across the twoviewing conditions, p» .05. Finally, the experienced play­ers showed significantly quicker RT values than the lessexperienced group under both El (ES = 1.08) and E2(ES = .86) viewing conditions, p< .05. These results arehighlighted in Table 3.

Discussion

The results showed that masking areas other thanthe ball or ball passer affected the experienced players'performance more than the less experienced group. Theexperienced players were less accurate under the E2 oc­clusion compared with the El control condition. In con­trast, occluding peripheral areas of the display had noeffect on the less experienced players' performance.Apparently, the experienced players extracted more in­formation from areas other than the ball or ball passerwhen attempting to anticipate pass destination. Mask­ing these areas deprived participants of informationfrom the positions and movements of players "off theball," suggesting that the experienced players madegreater use of these information sources, compared withtheir less experienced counterparts (cf., Williams et al.,1994). Furthermore, because there were no differencesin the orientation of foveal vision to these areas of thedisplay in Experiment 1, it appears that the experiencedplayers made greater use of peripheral vision to extractthis information. Although novices were constrained inthe same way by the 3-on-3 task, they were not skilled atusing peripheral vision to pick up information as evi­denced by the fact that the spatial occlusion didn't havea significant influence on performance.

The results showed that the experienced playersdemonstrated better performance under both the Eland E2 viewing conditions. Not only did they use theirperipheral vision more effectively to extract task-specificinformation, but they also derived better quality in­formation per foveal fixation. The experienced players

RQES: June 1998

Williams andDavids

were able to more effectively utilize information ema­nating from the ball kicker's passing technique to an­ticipate the ball destination. The ability to extract betterquality information per fixation, coupled with the abil­ity to more effectively acquire information via periph­eral vision, contributes to their superior anticipation inthese contexts.

Experiment 28: Visual Search Strategy andSelective Attention in t-en-t Situations inSoccer

Method

Participants and Test Film

Participants were the same as in Experiment 1. Thetest film comprised 10 action sequences from Experi­ment 1. These trials were selected randomly and in­cluded two right- and two left-footed dribblers. Theaction sequences were presented to participants underfour randomly ordered conditions of spatial occlusion,making a total of 40 film clips. To ensure there were nolearning or order effects, performance in the controlcondition (E4) in this experiment (see Table 4) was com­pared with that observed under the same conditions inExperiment 1 (see Table 2). The results showed no im­provement in performance for either group across thetwo experiments, indicating that learning or familiariza­tion effects were not apparent.

The occlusion was achieved by digitally editing anopaque rectangular box over the appropriate displayarea using a digital production mixer (Panasonic ~­MXI5; Panasonic, Osaka, Japan). The event occlusionconditions included masking the dribbler's head andshoulders (El), hips (i.e., above the knees and below themid chest region) (E2), lower leg (i.e., below the knees)and ball region (E3), and an irrelevant area of the dis­play (E4). The occlusion of an irrelevant area of the dis­play was intended as a control condition to account forany effects arising from the film disruption and subse­quent participant distraction.

Procedure andAnalysis

The procedure was as in Experiment 1. RT and RAwere included in this analysis. Because of the relation­ship between speed (RT) and accuracy (RA) measures,"a split plot MANOVA was used in analyzing group per­formance scores. In this analysis, Group (experienced­less experienced) was the between-subjects variable,viewing condition (EI-E2-E3-E4) the within-subjects fac­tor, RT and RA the dependent variables.

121

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams and Davids

Results

MANOVA showed a significant difference betweenthe groups, Wilks' A = .47, F(2, 21) = 11.60, p« .001, andviewing conditions, Wilks' A = 0.41, F(6, 17) = 3.93, P<.05. There was no significant Group x Viewing conditioninteraction, Wilks' A = .74, F(6, 17) = .98, p » .05. Dis­criminant analysis for the group main effect showed thatthe RT variable had a higher standardized coefficient(standard coefficient = 1.14) than the RA variable (stan­dard coefficient = -1.12). However, univariate analysisshowed a significant difference on both the RT, F(1, 22)= 5.06, P< .05, and RA variables, F( 1, 21) = 4.40, P< .05.Discriminant analysis for the viewing condition maineffect showed that the RT variable for the E2 occlusionhad the highest standardized coefficient (standard co­efficient = .95). Furthermore, univariate analysis re­vealed the RT variable for the E2 occlusion was the onlysignificant variable, F(3, 66) = 6.21, P< .001. Post hocScheffe analysis demonstrated that both groups of par­ticipants were quicker in the E1 and E4 viewing condi­tions compared with E2 and E3, p< .05. There were nodifferences between the E1 and E4 or between the E2and E3 conditions respectively, p» .05. These results arehighlighted in Table 4.

Discussion

The results showed that masking the dribbler's hips(E2) and the lower leg and ball region (E3) had a greatereffect on the experienced and less experienced players'performance than the other occlusions. It seems thatthese areas contained information used by the partici­pants in anticipating the direction of an opponent'sdribble. Findings supported the earlier eye fixation datawhich suggested that the experienced and less experi­enced players primarily focus on these two display areas.In contrast, occluding the dribbler's head and shoulders(E1) did not affect the players' performance relative to

the E4 control condition, suggesting that these areas donot provide essential information for anticipating anopponent's dribble.

Although the findings supported the eye fixationdata collected in Experiment 1, there were some con­tentious issues. First, the eye fixation data showed thatboth groups of players predominantly fixated on thelower leg and ball region when attempting to anticipatethe direction of an opponent's dribble. However, mask­ing these areas of the display did not affect their perfor­mance any more than the occlusion of the hip region.It appears that either performers utilize informationfrom more than one source to anticipate an opponent'smovements, or that when the lower leg and ball regionsare masked, players are able to obtain useful informa­tion from the hip region. Perhaps the two locations pro­vide overlapping and consequently, mutually redundantperceptual invariants in these situations. Second, Experi­ment 1 suggested that the experienced players madegreater use ofinformation extracted from the hip regionto anticipate the direction of dribble. However, occlud­ing this area of display did not affect their performancemore than the less experienced group. It is possible thatexperienced players were able to acquire the same in­formation from other sources, or that they fixated onthe hip region because it was the most appropriate po­sition to locate foveal vision to enable them to use pe­ripheral vision to extract task specific information.

Experiment 3: Visual Search Strategy,Selective Attention and Information Extractionin 3-on-3 Soccer Situations

To verify the findings obtained using eye movementand spatial occlusion techniques, concurrent verbal re­ports were employed to examine differences in selectiveattention in the 3-on-3 simulations. Concurrent verbalreport procedures require participants to verbalize the

Table 4. Mean group performance scores for experienced and less experienced players underthe four spatial occlusion conditions onthe 1-on-1 anticipation test

El E2 E3 E4Group RT(ms) RA(%) RT(ms) RA(%) RT(ms) RA(%) RT(ms) RA(%)

M SO M SO M SO M SO M SO M SO M SO M SO

Experienced(n =12) 3,232.5 62.7 90.0 8.5 3,273.7 65.2 90.7 11.8 3,252.6 53.8 92.5 9.6 3,188.1 119.8 90.0 11.2

Less experienced(n= 12) 3,276.7 120.7 81.6 12.3 3,337.2 105.2 78.3 26.0 3,359.3 169.6 85 14.8 3,265.7 78.6 76.0 17.9

Note. RT =response time; RA =response accuracy; E1 =occlusion of head and shoulders; E2 =occlusion of hip region; E3 =occlusion oflower leg and ball; E4 =occlusion of an irrelevant display area; M =mean; SO =standard deviation.

122 ROES: June 1998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

area of the display they consider particularly informative.Consequently, a more direct measure of attentional allo­cation and information extraction is provided (Bainbridge,1990; Ericsson & Simon, 1993). Although there have beencriticisms, there is much agreement that verbal reportscan provide valuable insights into higher mental pro­cesses (for a detailed review of the arguments, seeBrinkman, 1993; Green, 1995; Williams & Davids, 1997).

Method

Participants and Test Film

Participants were the same as in Experiment 1. Par­ticipants were presented with the same film clips used inthe 3-on-3 anticipation test. However, the sequence ofpresentation of film clips was rearranged on a randombasis to minimize order effects. Also, to further minimizethe possibility of any learning or familiarization effects,Experiment 3 was undertaken 1 month after the comple­tion of Experiment 2. In this experiment, the offensivemidfield player who made the eventual pass or dribblewas surrounded by a reference square during the entiretrial to be clearly highlighted. The reference square sub­tended a visual angle ofapproximately 6° in the horizon­tal and 5° in the vertical direction. This square did notmask the player'S actions on screen.

Procedure

The same test procedure as in Experiment 1 wasused. Participants viewed each pattern of playas it de­veloped on screen and responded by moving right, left,forward, or backward in relation to the action. Whileeach action sequence unfolded, participants were re­quired to concurrently verbalize the area of the displayfrom which they were extracting information. That is,they were asked to verbalize the area of the screen theywere attending to at that specific moment in time. Tosimplify this process, the screen was divided into threeareas: (l) box-the reference square which highlightedthe player who would make the eventual pass and for alarge portion of the trial the ball; (2) right-right sideof the screen, (3) left-left side of the screen. Partici­pants' verbalizations were recorded using a video cam­era (Panasonic F15) and recorder (Panasonic AG7450;Panasonic, Osaka, Japan) and were later transcribedverbatim for analysis. The camera was positioned to si­multaneously record participants' verbal comments andthe film image displayed on the screen. This enabledparticipants' verbal reports to be coupled with the filmedaction sequences for further analysis. Participants thenreceived 12 practice trials to ensure familiarity with theverbalization procedure. Trials in which there was abreakdown in verbalization processes were discarded. As

ROES: June 7998

Williams andDavids

participants found the verbalization procedure to beuncomplicated, few trials were actually rejected. The testsession lasted for 30 min on average.

Analysis-Dependent Variables and Verbal Report Data

Two dependent measures were obtained: RT and RA.Location of Visual Attention. The location of visual at­

tention was regarded as the number ofverbalizations pertrial recorded for each of the three separate locations(i.e., box, right, and left side of the screen) as a percent­age of the total number of verbalizations.

Verbal Search Order. This dependent variable was de­fined as the number of verbalized shifts in attention pertrial from the box to the right or left side of the screenthen back to the box.

Results

Anticipation Test

Performance on the anticipation test was analyzedusing a one way MANCOVA. In this analysis, Experience(experienced-less experienced) was the between-subjectsfactor, RA and RT the dependent variables, and CRT thecovariate. The results showed a significant difference inperformance on the anticipation test across the twogroups, Wilks' A = 0.67, F(2, 20) = 4.74, P< .05. Discrimi­nant analysis revealed that RT had the highest standard­ized coefficient (standard coefficient = -1.17) andconsequently, discriminated more clearly between groupsthan RA (standard coefficient = 0.26). Furthermore,univariate analyses showed that the experienced soccerplayers had quicker RT values, F(l, 21) = 9.61, P< .01(ES = 1.27), while there were no differences in RA be­tween groups, F(l, 21) = 3.11, r> .05 (ES = .57). Themean RT score for the experienced participants was4,433.45 ms (SD= 325.31) compared to 4,791.88 ms (SD= 228.72) for the less experienced participants, whereasthe mean RA values were 77.52% (SD= 13.76) and 84.2%(SD = 9.39) respectively.

Verbal Reports

Location of Visual Attention. Differences in the orien­tation ofvisual attention, as inferred from verbal reports,were examined using a split plotANOVA in which Group(experienced-less experienced) was the between-subjectsvariable and the three locations (box-right-left) thewithin-subjects variables. The results are represented inFigure 3. Findings showed no significant difference be­tween groups, F(l, 22) = 1.77, r> .05. 11. An initialMauchly's Sphericity test revealed a violation of the sphe­ricity assumption for repeated measures ANOVA, X2 (2)= 14.45, P< .001. Consequently, the location main effect

723

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams and Davids

and the Group x Location interaction were analyzed us­ing a MANOVA-type procedure as recommended bySchutz and Gessaroli (1987). This analysis showed signifi­cant differences in the location main effect, Wilks' A =

.14, F(2, 21) = 62.82, p< .0001, and in the Group x Loca­tion interaction, Wilks' A = .67, F(2, 21) = 5.02, P< .05.Post hoc Scheffe analysis on the Group x Location inter­action showed that the less experienced players spentmore time attending to information inside the box area(M= 66.74%, SD= 11.42) compared with the experiencedplayers (M = 50.92%; SD = 11.02), P< .05 (ES = 1.41).There were no differences between groups in the allo­cation of attention to the right and left sides of the dis­play, r> .05.

Search Order. Differences in the frequency of alterna­tion of visual attention between the box and the right orleft side of the screen were examined using a one-wayANOVA in which Group (experienced-less experienced)was the between-subjects variable. Findings showed nosignificant differences between groups, F(l, 22) = 0.56,r> .05 (ES = .09). The experienced players (M = 1.03,SD = .39) did not alternate their attention between thebox and right or left side of the screen more frequentlythan the less experienced players (M = 1.06, SD = .22).

However, because the less experienced players mademore verbalizations per trial (M = 7.44, SD = 1.35) thanthe experienced participants (M = 6.16, SD = 1.48), themean number of changes in the locus of attention pertrial was calculated as a percentage of the total numberof verbalizations. Data were analyzed using a one-wayANOVAin which Group (experienced-less experienced)was the between-subjects variable. The results showed asignificant difference between groups, F(l, 22) = 4.38,

p < .05 (ES = .95), with more of the experienced play­ers' verbalizations (M = 71.45%, SD = 12.64) being di­rected toward different display areas (i.e., box, right, left)compared to the less experienced players (M = 58.44%,SD= 14.64) .

Discussion

The results indicated differences between groups inthe allocation of visual attention. In Experiment 1, eyefixation data showed no differences between groups inthe distribution of visual fixations to selected areas ofthe display. According to this method, participants fo­cused primarily on the box, with infrequent fixations onthe right or left side of the screen. However, the verbalreports showed that the experienced players distributedtheir attention evenly between the box and the right andleft sides of the screen. Moreover, they attended to in­formation inside the box area for a shorter time period(M = 50.92%) than the less experienced players (M =

66.74%). The implication is that, although the experi­enced players were visually fixating the box area, theywere using peripheral vision to extract task specific in­formation from other areas of the display. They seemedable to use the box as a central reference or fixationpoint while simultaneously scanning peripheral visionfor the players' positions and movements. This moreextensive search strategy was highlighted by the fact that,although they had fewer verbalizations per trial, 71.44%of these comments involved a change in the locus ofattention compared to only 58.44% for the less experi­enced players. There were no differences between eye

70 -.--------------------------------------,

'$. 10

0+---

Experienced

I_Box _Right o Left ILess Experienced

Figure 3. Mean distribution of verbalizations to selected areas of the display in terms of percentage of totalviewing time in 3-on-3 situations.

124 ROES: June 1998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

movements and verbal reports for the less experiencedplayers, suggesting that visual fixation is indicative of in­formation extraction in these situations. They made lessuse of peripheral vision to extract task specific informa­tion, preferring instead to use foveal vision to fixate onthe ball or the player in possession of the ball.

Conclusions and Summary

This research had several objectives. First, we exam­ined skill-based differences in anticipation and visualsearch strategy in the typical micro states encounteredin soccer (3-0n-3 and l-on-l). These situations are greatlyemphasized as coaching contexts in modern practices,because they represent typical subphases of the game(e.g., see Hughes, 1994). It is, as yet, unclear whetherteam games players are constrained to implement thesame search strategies in small-sided practice conditionscompared to full-sided games. Second, the researchaimed to examine the relationship between visual fixa­tion, as inferred from eye movement recording, and se­lective attention, as implied through spatial occlusionand concurrent verbal report methods. Third, we exam­ined the relationship between task constraints and thevisual search pattern employed to extract task specificinformation. In particular, we were interested in thesearch strategies adopted by experienced and less expe­rienced players in the different micro states of the gamecompared with visual search data collected previouslyusing ll-on-ll simulations. Furthermore, we examinedthe assumption that peripheral visual processing wouldhave a greater emphasis in the micro state simulationsdue to fewer, but highly pertinent, perceptual informa­tion sources being concentrated in the simulations.

Anticipation and Visual Search Strategies in theSubphases of Soccer

Previous work had only investigated this relationshipin ll-on-ll simulations, despite the fact that the gamemay be broken down into offensive and defensivesubphases involving smaller units of players. The resultsshowed that the experienced soccer defenders demon­strated superior anticipation in 3-on-3 and l-on-l simu­lations, supporting previous research involving penaltykick and l l-on-l I simulations (Williams & Burwitz, 1993;Williams et al., 1994). Although alternative theoreticalinterpretations could be proposed based on neural net­work or dynamical system models (for a detailed review,see Williams, Davids, & Williams, in press), the experi­enced player'S superior performance is thought to belinked to the organization of task specific knowledge inlong-term memory (see Starkes & Allard, 1993; Ander­son, 1983). According to Anderson (1983), experts areable to encode and retrieve task-specific information

ROES: June 1998

Williams and Davids

based on a set of condition-action links called produc­tions. These productions, which are sometimes referredto as "if...then...do" statements (see McPherson & Tho­mas, 1989), are responsible for initiating an appropri­ate response under specified conditions. Also importantis the expert's ability to "chunk" separate stimuli (e.g.,individual player positions) into meaningful wholes(e.g., patterns of play). This enhanced ability to recog­nize meaningful associations between players' positions,results in more rapid identification of playing patternsand the eventual anticipation of pass destination (Will­iams & Davids, 1995).

The experienced players' superior anticipation wasnot mirrored by differences in visual search strategy inthe 3-on-3 simulations. There were no differences in thelocation of visual fixation, search order, or search rate.Both experienced and less experienced participants pre­dominately fixated on the ball or ball passer with fewerfixations to the left or right of the screen. In contrast,systematic differences in visual search strategy wereshown between groups in the l-on-l simulations. Theexperienced players tended to fixate longer on the hipregion, indicating that this area was important in antici­pating the direction of an opponent's dribble. Also, theyemployed more fixations ofshorter duration (i.e., highersearch rates) and tended to alternate their fixations morefrequently between the hip and lower leg or ball regions.

Visual Orientation, Visual Attention, and InformationExtraction

Although significant differences in anticipation wereobserved in the 3-on-3 simulations, it is notable that thesewere not based on different search patterns between theexperienced and less experienced participants. A lackofbetween-group differences in the orientation offovealvision to the display suggested that the experienced play­ers were more sensitive to peripheral visual informationfrom the changes in positions of teammates and oppo­nents. Experiments 2 and 3 were conducted to shedmore light on this specific issue. In Experiment 2, weshowed that occluding areas other than the ball or ballpasser affected the experienced players more signifi­cantly than their less experienced counterparts. Further­more, we demonstrated that the experienced playerswere more successful in picking up information underfull and occluded viewing conditions. This indicated thattheir perceptual skill was based on the quality of infor­mation extraction within each fixation and the moreefficient use of peripheral vision to gain accurate infor­mation for decision making. The experienced playersused foveal vision to extract more pertinent formationfrom the passing player'S posture (e.g., orientation ofthe hips, shoulders, and lower leg region), while usingperipheral vision to obtain confirmatory informationbased on the movements of the offensive players "off the

125

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams andDavids

ball." This latter suggestion was confirmed by Experiment3, which showed clear discrepancies between the eyemovements used to pick up information and the verbal­ized "map" of visual attention reported by the experi­enced players. The experienced players spent less timevisually fixating peripheral areas of the display comparedwith the amount of time they reported visually attend­ing to these areas via concurrent verbal reports. With theless experienced players, "what they see is what they get."That is, a distinct relationship existed between the locusof eye fixation and the locus of attention as reported bythese participants.

Clearly, as experience accrues, skill in "anchoring"the fovea to an appropriate area of the display is con­strained by the specific demands of the task leading toan enhanced orientation to important sources of infor­mation in the periphery. These findings support the con­clusions of the (few) previous studies which haveexamined the relationship between task experience, vi­sual fixation, and the locus of attention in the contextof racquet sports (e.g., Abernethy & Russell, 1987a,1987b; Abernethy, 1990). Previous arguments on thelimitations of eye movement registration techniques inidentifying the important sources of information wereextended, by the current research, to the context of teamball games. Also, the significance of the effects of taskexperience on the skill of orienting the visual systemappropriately to optimize information pick up from theperiphery was verified in a team game situation.

Although both groups sought information from theball and the lower leg of the oncoming dribbler in thel-on-l simulations, the experienced group appeared tobe extracting more information from the hip region. In­terestingly, the spatial occlusion technique did not pro­vide evidence to support this suggestion, becauseoccluding the hip region did not affect the experiencedplayers' performance more than their less experiencedcounterparts. The implication is that the experiencedplayers were able to pick up similar information fromother areas of the display, such as the orientation of thelower leg and foot relative to the ball, to which the lessexperienced group were clearly less attuned. When thehip was occluded, perhaps the experienced players ac­quired comparable information from the lower leg,making information from the hip region somewhat re­dundant.

Visual Search Strategy and Task Constraints

The third objective was to examine whether thesearch strategy employed was constrained by the tasksituation. Specifically, we compared the search strategiesin subgroup (i.e., 3-on-3) and individual (i.e., l-on-l)task contexts with those obtained in an earlier study em­ploying II-on-11 film simulations (see Williams et al.,1994). In Ll-on-I l simulations, we showed that experi-

126

enced players employed a search strategy comprisingmore fixations (M = 10.30; SD= .97) of shorter duration(M =933.94 ms; SD=99.34) than less experienced play­ers who had fewer fixations (M= 8.72; SD= .94) of longerduration (M = 1163.16 ms; SD = 206.26). This more ex­tensive search strategy is advantageous in the l1-on-11context, because defenders have to be aware of a num­ber of sources of information, including the location ofthe ball, their own position in relation to pitch markingssuch as the edge of the penalty area, the movements ofkey offensive players attempting to penetrate the spacesbetween and behind defenders, and the positions ofteammates attempting to defend the critical areas ofthefield (Hughes, 1994). This extensive number of percep­tual information sources, located disparately across alarge area of the field, constrains the experienced ob­server to utilize more frequent fixations than in the mi­cro state contexts. The task constraints, as expressed bythe number of perceptual information sources, are lesssevere in the 3-on-3 simulations, and this results in agreater emphasis on the role of peripheral vision. Inthese situations, perceptual skill involves employing a"visual pivot" in order to diffuse attention according tothe specific requirements of the task. Experienced play­ers maintain foveal fixation on the player in possessionof the ball while using peripheral vision to move theirattentional focus around the display. This type of ap­proach has several advantages. First, the saccadic eyemovements which separate each foveal fixation are in­active periods of information processing; thus, in time­constrained circumstances, a search pattern with fewerfoveal fixations may be regarded as a more efficientsearch pattern. Second, previous research suggests it ismuch faster to switch attention from one area of thedisplay to another, covertly using peripheral vision ratherthan overt eye movements (see Nougier, Stein, &Bonnel, 1991; Posner & Raichle, 1994). Also, there isevidence to suggest that we can use peripheral vision toprocess movement related information more rapidlythan foveal vision (Milner & Goodale, 1995).

Finally, in the l-on-I situations, observers need highlyprecise information from the offensive player's move­ments (i.e., changes to hip, lower leg, and foot orienta­tion) to specify the direction of dribble. Consequently,because the hip and lower leg or ball regions appear toprovide the significant information in these situations,performers need to fixate on these areas to pick up thekey motion invariants. This type of detailed informationmay be provided only poorly by the peripheral visual sys­tem, therefore constraining the observer to use fovealvision most of the time.

In sum, this research furthers our understanding ofvisual search behavior in dynamic sports contexts by us­ing soccer-related tasks under naturalistic conditions. Theuse of a verbal report protocol, along with the manipu­lation ofvarious sources of perceptual information avail-

ROES: June 1998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

able to the observer, indicated that perceptual skill in­volves the precise orientation of the visual system priorto information pick up. Empirical evidence was providedto show that experienced performers make more appro­priate use of peripheral vision under certain task con­straints in team games. The implication is that eyemovement registration techniques are somewhat limitedto indicating the locus offixation and not necessarily thelocus of attention in dynamic team game contexts. Amajor task for researchers is to clarify the relationshipbetween the location of perceptual sources of informa­tion, the specific task constraints, and the type of visualbehavior employed by performers. Finally, regarding thedevelopment of experimental protocols, investigatorsneed to create controlled experimental simulationswhich include three-dimensional viewing conditions andsources of perceptual information other than vision, forexample, auditory information from movements, ballcontacts in passing, and vocal information from oppo­nents and teammates.

References

Abernethy, B. (1985). Cue usage in "open" motor skills: A re­view of available procedures. In D. G. Russell & B.Abernethy (Eds.), Motormemory and control: The Otago sym­posium (pp.110-122). Dundein, NZ: Human PerformanceAssociates.

Abernethy, B. (1988). Visual search in sport and ergonomics:it's relationship to selective attention and performer ex­pertise. Human Performance, 4, 205-235.

Abernethy, B. (1990). Expertise, visual search, and informa­tion pick-up in squash. Perception, 19, 63-77.

Abernethy, B. (1991). Visual search strategies and decision­making in sport. InternationalJournal ofSportPsychology, 22,189-210.

Abernethy, B. & Russell, D. G. (1987a). Expert-novice differ­ences in an applied selective attention task. Journal ofSportPsychology, 9, 326-345.

Abernethy, B. & Russell, D. G. (1987b) The relationship be­tween expertise and visual search strategy in a racquetsport. Human Movement Science, 6, 283-319.

Abernethy, B, Thomas, K. T., & Thomas,]. T. (1993). Strate­gies for improving understanding of motor expertise (ormistakes we have made and things we have learned!!). Inj. L. Starkes & F. Allard (Eds.), Cognitive issues in motorex­pertise (pp. 317-356). Amsterdam: Elsevier SciencePublishers.

American Psychological Association (1982). Ethicalprinciples inthe conduct of research with human participants. Washington,DC: Author.

Anderson,]. R. (1983) The architecture of cognition. Cambridge.MA: Harvard University Press.

Bainbridge, L. (1990). Verbal protocol analysis. In]. R. Wil­son & E. N. Corlett (Eds.), Evaluation of human work: Apractical ergonomic methodology (pp. 161-179). London:Taylor and Francis.

Williams andDavids

Brinkman,]. A. (1993). Verbal protocol accuracy in fault diag­nosis. Ergonomics, 36, 11, 1381-1397.

Cohen,]. (1992). A power primer. Psychological Bulletin, 112,155-159.

Davids, K. (1984). The role of peripheral vision in ball games:Some theoretical and practical notions. Physical EducationReview, 7,26-40.

Ericsson, K. A. & Simon, H. A. (1993). Protocol analysis: Verbalreports as data. Cambridge, Massachusetts: MIT Press.

Goulet, C., Bard, C., & Fleury, M. (1989). Expertise differencesin preparing to return a tennis serve: a visual informationprocessing approach. Journal of Sport and Exercise Psychol­ogy, 11,382-398.

Green, A.]. (1995). Verbal protocol analysis. The Psychologist,8(3), 126-129.

Helsen, W. & Pauwels,]. M. (1993). The relationship betweenexpertise and visual information processing in sport. In].L. Starkes & F. Allard (Eds.), Cognitive issues in motorexper­tise (pp. 109-134). Amsterdam: North-Holland.

Hughes, C. (1994). TheFootball Association book oftactics and skills.London: Queen Anne Press.

Kundel, H. L., Nodine, C. F., & Toto, L. (1984). Eye movementsand the detection of lung tumors in chest images. In A.G. Gale & F.johnson (Eds.), Theoretical and appliedaspectsof eye movement research (pp. 297-304). Amsterdam: NorthHolland.

Milner, D. A. & Goodale, M. A. (1995). The visual brain in ac­tion. Oxford, UK: Oxford University Press.

McPherson, S. L. & Thomas,]. R (1989). Relation of know1­edge and performance in boy's tennis: Age and expertise.Journal of Experimental Child Psychology, 48, 190-211.

Neumann, 0., Van der Heijden, A. H. C., & Allport, D. A.(1986). Visual selective attention: Introductory remarks.Psychological Research, 48, 185-188.

Nougier, V., Stein,]. F., & Bonnel, A. M. (1991). Informationprocessing in sport and orienting attention. InternationalJournal of SportPsychology, 22, 307-327.

Paillard,]. (1982). The contribution of peripheral and centralvision to visually guided reaching. In D.]. Ingle, M. A.Goodale, & R]. Mansfield (Eds.), Analysis of visual behav­ior (pp. 367-385). Cambridge, MA: MIT Press.

Papin,]. M., Metges, P., & Amalberti, R (1984). Use of NACeye mark by radiologists. In A. Gale & F.johnson (Eds.),Theoretical and applied aspects of eye movements research (pp.323-330). Amsterdam: North Holland.

Posner, M. I. & Raichle, M. E. (Eds.) (1994) Images ofmind. N.Y:Scientific American Library.

Remington, R W. (1980). Attention and saccadic eye move­ments. Journal of Experimental Psychology: Human Perceptionand Performance, 6, 726-744.

Ripoll, H. (1991). The understanding-acting process in sport:The relationship between the semantic and the sensorimo­tor visual function. InternationalJournal of SportPsychology,22, 221-243.

Ripoll, H., Kerlirzin, Y, Stein,j. F., & Reine, B. (1995). Analy­sis of information processing, decision making, and visualstrategies in complex problem solving sport situations.Human Movement Science, 14(3), 325-349.

Sanders, A. F. & Houtmans, M.]. M. (1985). Perceptual pro­cessing modes in the functional visual field. ActaPsychologica, 58, 251-261.

127

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3

Williams andDavids

Schutz, R W. & Gessaroli, M. E. (1987). The analysis of repeatedmeasures designs involving multiple dependent variables.Research Quarterly for Exercise and Sport, 58, 132-149.

Shulman, G. L., Remington, R. w., & McLean,]. P. (1979).Moving attention throughout visual space. Journal of Ex­perimentalPsychology: Human Perception and Performance, 5,522-526.

Stager, P. & Angus, R (1978). Locating crash sites in a simu­lated air-to-ground visual search. Human Factors, 20, 453­466.

Starkes.]. L. & Allard, F. (1993) (Eds.). Cognitive issues in motorexpertise. Amsterdam: North-Holland.

Tyldesley, D. A., Bootsma, R]., & Bomhoff, G. T. (1982). Skilllevel and eye movement patterns in a sport orientatedreaction time task. In H. Rieder, H., H. Mechling, & KReischle (Eds.), Motor learning and movement behavior: con­tribution to learning in sports (pp. 290-296). Cologne, Ger­many: Hoffmann.

Van der Heijden, A. H. C. (1986). On selection in vision. Psy­chological Research, 48, 211-219.

Vickers,]. N. (1992). Gaze control in putting. Perception, 21,117-132.

Williams, A. M. & Burwitz, L. (1993). Advance cue utilizationin soccer. In T. Reilly,]. Clarys, & A. Stibbe (Eds.), Scienceand football II (pp. 239-244). London: E. & F. N. Spon.

Williams, A. M. & Davids, K (1995). Declarative knowledge insport: A by product of experience or a characteristic of ex­pertise? Journal of Sport and Exercise Psychology, 17(3), 259­275.

Williams, A. M. & Davids, K (1997). Assessing cue usage inperformance contexts: A comparison between verbal re­port and eye movement methods. Behavioral Research Meth­ods, Instruments, and Computers, 29, 364-375.

Williams, A. M., Davids, K, & Williams,]. G. (in press). Visualperception and action in sport. London: E. & F. N. Spon.

Williams, A. M., Davids, K, Burwitz, L., & Williams,]. G. (1992).Perception and action in sport.Journal ofHuman MovementStudies, 22, 147-205.

Williams, A. M., Davids, K Burwitz, L., & Williams,]. G. (1993).Visual search and sports performance. TheAustralianJour­nal of Science and Medicine in Sport, 22, 55-65.

Williams, A. M., Davids, K, Burwitz, L., & Williams,]. G. (1994).Visual search strategies in experienced and inexperiencedsoccer players. Research QuarterlyforExercise and Sport, 65(2)127-135.

Yarbus, A. L. (1967). Eye movements and vision. New York: Ple­num Press.

Notes

1. Available from Applied Science Laboratories, 175Middlesex Turnpike, Bedford, Massachusetts, 01730-1428.2. This CRT variable is actually a combination of deci­sion time (DT) and movement time (MT). Consequently,a more accurate term for this measure would be responsetime (RT). To examine whether there were between­group differences in four-choice reaction time (CRT), aone-way MANOVA was conducted whereby Group (ex-

128

perienced-less experienced) was the between-subjectsfactor and DT, MT, and RT the dependent variables. Theresults showed a significant difference in performancebetween groups, Wilks' A = .65, F(3, 20) = 3.58, P< .05.Separate univariate analysis of the three dependent vari­ables revealed a significant difference for DT, F(1, 22) =

6.83, p< .05, and RT,F(1, 22) = 10.15, p« .01. There wereno differences between groups on the MT variable, F(l,22) = .72, r> .05.3. Pearson product-moment correlations revealed thefollowing between the four dependent variables: IT-MT,r(24) = -.38, p» .05; IT-RT, r(24) = .99, p< .0001; IT-ACC,r(24) = .73, P< .0001; MT-RT, r(24) = -.30, P< .05; MT­ACC, r(24) = -.35, P< .05; RT-ACC, r(24) = .72, P< .0001,and where IT = initiation time, MT = movement time,RT = response time, and RA = response accuracy.4. Differences in performance on the two-choice reac­tion time (CRT) test were examined using a one-wayMANOVA in which Group (experienced-less experi­enced) was the between-subjects factor and DT, MT, andRT the dependent variables. The results showed no sig­nificant difference in performance between groups,Wilks' A = .96, F(3, 20) = .25, p » .05.5. Pearson product-moment correlations revealed thefollowing correlations between the four dependent vari­ables: IT-MT, r(24) = -.20, p » .05; IT-RT, r(24) = .95, P<.0001; IT-ACC, r(24) = .08, p » .05; MT-RT, r(24) = .11, P> .05; MT-ACC, r(24) = -.16, p» .05; RT-ACC, r(24) = .10,r> .05; and where IT = initiation time, MT = movementtime, RT = response time, and RA = response accuracy.6. Pearson product-moment correlations revealed thefollowing correlations between the dependent variables:El RT-ACC, r(24) = .53, P< .01; E2 RT-ACC, r(24) = .54,P< .01; and where RT = response time, RA = responseaccuracy, El = occlusion of irrelevant display areas, E2 =

occlusion of areas other than the ball-ball passer.7. Pearson product-moment correlations revealed thefollowing correlations between the dependent variables:El RT-ACC, r(24) = .38, p » .05; E2 RT-ACC, r(24) = .61,p< .01; E3 RT-ACC, r(24) = .42, p< .05; E4 RT-ACC, r(24)= .01, p> .05; and where RT = response time, RA = re­sponse accuracy, El = occlusion of head and shoulders,E2 = occlusion of hip region, E3 = occlusion of lower legand ball, E4 = occlusion of an irrelevant display area.

Authors' Note

Please address all correspondence concerning this articleto A. M. Williams, Research Institute for Sport and Exer­cise Science, School of Human Sciences, LiverpoolJohnMoores University, Mountford Building, Byrom Street,Liverpool, L3 3AF, UK.

E-mail: m.williams@lhjm.ac.uk

ROES: June 1998

Dow

nloa

ded

by [

Nor

th C

arol

ina

Stat

e U

nive

rsity

] at

21:

17 1

9 A

ugus

t 201

3