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    The 2012 World Congress on Performance Analysis in Sport

    11,21,21 Will G Hopkins, Rita M Malcata, Sian V Allen, Kirsten N Spencer

    Sportscience 16, 32-37, 2012 (

    1 Sport Performance Research Institute New Zealand, Millennium Campus, AUT University, Auckland, NZ; Email. 2 High Performance Sport New Zealand, Millennium Campus, AUT University, Auckland, NZ. Reviewers: Peter O'Donoghue, Cardiff School of Sport, Cardiff Metropolitan University, Cardiff, UK; Nic James, London Sport Institute, Middlesex University, London, UK.

    This biennial boutique conference at the University of Worcester in England

    was outstanding value for the growing cadre of sport-performance analysts,

    although there were few definitive experimental studies. Keynotes: media

    channels; top soccer analysts; movement patterns in AFL; 400-m hurdles.

    Noteworthy Methodologies: automatic tracking and analysis; barcode scanning

    for real-time analysis; luck- and error-free performance measure; summing

    performance indicators. Basketball: performance rates; space creation; defen-

    sive plays; automatic tracking; iPad app; critical episodes; entropy in game

    scores. Combat Sports: trunk protector in taekwondo; real-time coding in judo;

    punches and judging errors in boxing; movements in fencing. Equestrian: body

    build and fitness; split times; motivation; saddle design; Pilates. Handball: time-

    outs; game stats; movements; actions; fitness; skills; referees' accuracy and

    movements. Racket Sports: serves, groundstrokes, set victories and intensity

    in tennis; affect in badminton; strokes and footwork in table tennis; movements

    in Padel; intensity and rule changes in squash; analysis in "real" tennis. Rugby:

    movements; turnovers; tackling; positional profiles; rucks; actions; kicks;

    scrums; tries. Soccer: environmental effects; home advantage; normative pro-

    files; spatial-temporal relationships; offensive actions and plays; releasing

    players; goals; kicks; small-sided games; barcode scanning; goal keepers'

    actions and training; coach behaviors and effectiveness; role of analysis; ca-

    reer achievements; plays causing injuries Volleyball: setters' actions; defensive

    actions; attack tempo; serves; attack areas and winning teams in beach volley-

    ball; training. Other Individual Sports: strength in shot-put; movements in

    rhythmic gymnastics; pack size in triathlon; body sway in biathlon; environment

    in rowing; neural-net modeling of javelin; scoring system in trampoline; a golf

    coach-analyst; shot difficulty in golf; helper riders in Tour de France; analysis

    needs in canoe/kayak. Other Team Sports: actions, plays and efficacy of anal-

    ysis in netball; movements and decision-making in AFL; skills in Gaelic football;

    actions and batting in cricket; intensities and actions in ice hockey; playing time

    in water polo. Sports Medicine and Science: biomechanics of ACL injury; fati-

    gue in biathletes; academic performance and sport. KEYWORDS: competition,

    information technology, elite athletes, kinematics, kinetics, talent identification,

    tests, training.

    Reprint pdf ? Reprint docx ? Reviewer's Commentary

    The archetypal English country township of where you now find many worshippers, and Worcester was the venue for this biennial con-some of us make our lives meaningful by ana-ference of the International Society of Perfor-lyzing sport performance.

    mance Analysis of Sport (ISPAS). The day Derek Peters and his team from the Universi-

    before the conference started, three of us had ty of Worcester provided a conference venue the good fortune to wander into Worcester ca-and logistics that were exceptional value for thedral in time for choral evensonga moving money, while two key members of ISPAS, experience made even more poignant by the Peter O'Donoghue and Nic James, organized almost complete absence of a congregation. The and ran the scientific show with aplomb. We zeitgeist moves on, the cathedral of sport is look forward to the next conference in 2014,

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Hopkins et al.: WCPAS Conference Page 33

    wherever it might be. Any sport scientist inter-formation technology was the main message in ested in performance analysis (aren't we all?) Tony Kirkbride's enthralling keynote on media

    should join the society to keep up with devel-channels for performance analysis. Real-time opments. Visit the ISPAS website for more. or near real-time competition data of some In the summaries below, we have included high-profile sports events are available free, but presentations only if there was a measure of high-quality data feeds require subscriptions performance or other data or insights relevant to with providers such as Opta. At the level of the science or practice of performance analysis. your own athlete or team, real-time interactivity We have used the word movements to mean between analyst, coach and athlete is also be-distances covered or speeds of athletes that can coming a reality in what Tony called Martini-II. be quantified from videos, accelerometers or Barry Drust and Andy Scoulding provided global-positioning satellite (GPS) devices, insights into performance analysis in two top

    while actions and plays refer to events or strat-soccer teams of the English premier league. egies that require coding of a live or recorded he role of performance analyst has evolved T

    video data stream by an analyst. from that of simple match reporter to an indis-Alas, the keynote presentations did not have pensable source of information on monitoring abstracts, so we have summarized only those of training, pre- and post-match analyses, and we could attend. We have also provided para-scouting for new players. The purpose of train-graph summaries of a few noteworthy generic ing monitoring is load management, providing methodological developments, but otherwise useful information for coach and strength and only the sport and the relevant aspect of per-conditioning staff. Pre- and post-match analyses formance are listed under relevant headingsrely on the quality of information and delivery. you will have to read the abstracts to get the Piero, OPTA, Prozone, Amisco are some of the findings. Download the book of abstracts and analysis tools in current use. Scouting for play-use the advanced search form in Acrobat (Ctrl-ers has been made easier with players' profiling. Shift-F) to find the abstract via the podium Current challenges (and opportunities for up-number (e.g., POD 1.1) or poster number (e.g., coming analysts): how to extract relevant in-POST 1.1.1). The abstracts are sometimes in a formation from the deluge of data now availa-foreign form of English that limits their utility. ble, and how to integrate it into day-to-day Some research presentations at the confe-practice.

    rence could be described as "games I have Brian Dawson's keynote on movement pat-

    coded". Up to a point that's acceptable: this terns in team sports drew on his experience conference is partly a professional workshop with Australian-rules football (AFL). The

    providing performance analysts with a valuable data from GPS devices have established rela-opportunity to share and reflect on their expe-tionships between training/game loads and riences. But it was disappointing that the de-injury risk and have helped make training ses-signs of the original-research studies were al-sions more specific to demands of the game, but most all descriptive: we could find only a hand-relationships between measures of movement ful of studies involving an experimental mani-and competition performance are at best poor. pulation in which a performance measure was a Wynford Leyshon delivered a coach perspec-moderator, mediator or outcome variable (POD tive for his keynote on the use of performance

    15.2, 16.4, 16.5; POST 1.1.5, 2.1.5), and all but analysis in international 400-m hurdles. He

    one was a time series rather than more defini-used a case study of a London Olympian to tive crossovers or parallel-groups controlled demonstrate how analysts can best present race trials. Maybe such high-quality research is hap-analysis data in order to help and engage pening but is too valuable to present at confe-coaches. Parameters of most interest to him rencessee the end of the next section. included touchdown times and differences in

    pacing due to changes in stride patterns, which Keynotes he referred to as "differential at change-down". Accurate, meaningful content-rich data "any-Noteworthy Methodologies time, anyplace, anywhere" (the Martini prin-

    ciple of marketing in the 1970s) via smart-Reports of automated tracking and analysis

    phones and other recent developments in in-are always interesting, because hand coding of

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Hopkins et al.: WCPAS Conference Page 34

    videos consumes huge amounts of time and stracts or a journal! See for example this article

    only rudimentary analyses can be done for real-about the role of analyst Ken Quarrie in the All time or near real-time feedback to coach and Blacks' victory in the 2011 Rugby World Cup. players. Recent improvements were presented Basketball in a system that tracks players with data from

    two overhead cameras, the Sport Performance Performance Indicators

    Analyzer (POD 6.1, 6.3, 6.6). Plays in basket-POD 1.3 Performance rates (sum of good

    ball were classified correctly only ~80% of the minus bad actions) of 287 players in the time, and only ~90% with post-game manual male World Championships.

    processing. This system is promising but still POD 1.4 Little difference in space-creation

    some way from routine implementation. dynamics between age groups in 46 semi-Monetary constraints often influence the level final matches of a state championship. of performance analysis that is available to a POD 3.5 Defensive plays in 80 matches of a team. An inexpensive option may be an inven-national league.

    tive real-time notational analysis system POD 6.1, 6.3, 6.6 Automated tracking of

    where analysts use barcode scanning to code players with two overhead cameras in 4 up to 15,000 different game events (POST games of a national professional A league. 1.4.1). In initial trials analyzing soccer matches, POD 12.4 An iPad application for live match scanners failed to read 0.9% of barcodes. An analysis (presenter absent). iPad application to configure, code and ana-POST 2.2.12 Defense-offense transitions in

    lyze live match performance also looks encour-nine regional under-14 matches. aging for the budget-conscious performance Other analyst, but the presenter failed to attend (POD POD 1.1 Critical episodes in 80 matches from 12.4). a national league. A "luck- and error-free" measure of team-POD 1.2 Entropy as a measure of uncertainty sport performance has been derived by assign-in game scores in "18 NBA and 14 ACB ing a score to every action on the basis of what regular seasons". happened before and after the action (POD 3.6). POST 2.2.11 Time between scores in five The approach has been commercialized. NBA seasons. When you have all those so-called perfor-

    mance indicators for your team, do they really Combat Sports

    tell you anything about team performance? Performance Indicators According to Ed Burt and Mike Hughes, "nu-POD 11.2 Actions and scoring with introduc-merous studies have assessed performance tion of electronic trunk protector in n=? using action variables but have largely failed to taekwondo international bouts. consistently identify a link between individual POD 11.3 System for real-time coding of judo performance indicators and match outcome." So on palm-tops and smart-phones established they tried adding up counts and scores of vari-n=? bouts. ous actions with weightings they assigned on POD 11.5 Combinations of punches in 8 bouts the basis of their own understanding of the from each of 3 weight divisions of boxing. importance of the actions in the game of rugby POD 11.6 Movements of elite female foil union. Reassuringly, performance scores in 26 fencers in 100 international bouts. national-level matches of a national-league Other team and in 12 Six Nations matches showed "a POD 11.1 Errors in judging in 10 Olympic very strong correlation with match outcome" boxing bouts. (POST 1.2.10). We presume the scoring system

    could be adapted easily to the rating of individ-Equestrian ual players. It's also very likely that linear or

    Performance Indicators neural-net models derived with large data sets

    POD 16.2 Body build and fitness of 16 female will be even more successful. It's even more

    riders at three competitive levels. likely that such scoring systems have already

    POD 16.3 Split times and performance in 27 been worked out in rugby and other sports and

    successful clearance rounds and 49 with that you will never see them in conference ab-

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Hopkins et al.: WCPAS Conference Page 35

    faults in a national (?) championship. of 12 recreational male squash players.

    POST 2.3.6 Movements in one elite tennis Other

    match. POD 16.1 "Large scale" survey of motivation POST 2.3.9 Changes in rally length and score in under-18 riders. with rule changes between a 2003 and 2010 POD 16.4 Effect of two saddle designs on squash championship posture in a crossover with nine experienced POST 2.3.8, POD 6.2 Analysis system for real riders. tennis (the peculiar progenitor of tennis). POD 16.5 Effect of Pilates training on posture

    in an uncontrolled study of 10 riders. Rugby

    Handball Performance Indicators

    POD 6.4 GPS for position-dependent move-Performance Indicators

    ments in 98 players from eight premier POD 8.1 Descriptive stats from 344 team clubs. timeouts in a national league. POD 15.2 GPS for movements of 40 expe-POD 8.3 Game statistics of winners and losers rienced vs novice players in small-sided in five European men’s handball champion-games. ships. POD 15.3 Network analysis for role of two-POD 8.5, POST 1.2.9 Movements and actions man tackles in producing turnovers in 20 of 69 players in three women's qualifying matches of the World Cup. games of the European championships. POD 15.4 Tackling in matches of a Super 15 POST 2.2.5 Actions and plays in six games of rugby season. Valencian handball. POD 15.5 Positional profiles in 28 home vs Other away games in the English championship. POD 8.2 Accuracy of referees (10) and their POD 15.6 Rucks in 15 Six-Nations matches. examiners (3). POST 1.2.10 Scores for actions predicting POD 8.4 Fitness and skills of 108 players at outcome in 26 national-level matches and in college level. 12 Six-Nations matches. POD 8.6 Movements of referees in the nine Other finals of a national league. POD 15.1 Kinematics of n=? kicks of 5 expert

    rugby and 5 expert Gaelic football players. Racket Sports

    POST 1.2.11 Clean and unclean scrums in 46 Performance Indicators World-cup matches. POD 7.1 First-serve success and other indica-POST 1.2.12 Tries scored per unit of posses-tors in 1929 Grand Slam tennis matches. sion time (or its inverse?) in 15 Six-Nations POD 7.2 Duration of groundstroke as predic-games. tor of aggressive or defensive shot in 567 POST 1.2.12 Scoring and actions in the top rallies in women's tennis. and bottom nations of the World Cup. POD 7.4 Gender and affect (and implications

    for coaching) for eight mixed-pairs county Soccer badminton players. Performance IndicatorsPlayer POD 7.5 Strokes and footwork in 10 male and POD 4.4 Effects of temperature, playing sur-five female top-30 table tennis matches. face, travel, and recovery time on perfor-POD 14.3 Movements in two top-level matches mance indicators in four years of the US ma-of Padel tennis. jor league. POST 2.3.4 Posture in 2470 ground strokes in POD 5.1, POD 5.5, POST 2.1.1 Home advan-four matches of men's Masters Cup tennis. tage in Brazilian, Norwegian and English POST 2.3.5 Set-victories momentum in three national leagues. years of Grand Slam tennis. POD 5.2 Normative profiling of young foot-POST 2.3.7 Serve outcomes in a Grand Slam ballers in 30 matches. vs national junior tennis tournament. POD 5.3 Players’ spatial-temporal relation-Other ships in two national matches. POD 7.3 Physiological intensity of shot types POD 5.4, POD 9.1, POD 13.1 Offensive plays

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Hopkins et al.: WCPAS Conference Page 36

    Other of two international teams in 24 national

    games. POD 2.4 Perceived role of performance anal-POD 9.2 Placing of the corner kick and out-ysis from interviews of 8 players and three come in 19 under-17 matches. managers in one professional club.

    POD 9.3, POD 13.4, POST 1.1.4 Movements POD 4.5 Effect of environmental tempera-and plays in small-sided games at various ture on home advantage in 346 international levels. matches.

    POD 9.6 Attacking actions and plays in 60 POD 9.5 Release of players to World Cup and matches of three national leagues. ensuing clubs' performance. POD 13.5 Analysis of goals in 41 matches of a POST 2.1.11 Career achievements of 154

    youth academy team. international under-17 players. POD 12.6 Differences in movements of five POST 2.1.12 Quantification of injuries and

    semi-elite players between GPS, manual identification of high-risk plays in 160

    tracking, and video-based analysis systems. youth football matches. POST 1.1.1 Effect of relative numbers of play-

    Volleyball ers in attackers' and defenders’ plays in

    10 international games and n=? lower-level Performance Indicators

    practice games of futsal. POD 3.4 Successful actions of the setter in 24 POST 1.1.3 Poor relationships between 22 championship games.

    action variables and outcomes in 277 na-POD 10.5 Defensive actions in five national tional championship matches. league games.

    POST 1.1.5 Effect of zone vs man-to-man de-POST 1.2.2 Determinants of attack tempo in

    fenses on plays in a trial of 12 under-17 19 high-level male games. elite players in small-sided games. POST 1.2.3 Winning serves in n=? champion-POST 1.4.1 Barcode scanning for notational ship games.

    analysis validated with soccer matches. POST 1.2.4 Successful areas of attack in 10 POST 2.1.2 Normative profiling of 136 corner games of men’s professional beach volley-kicks in 12 matches in a professional league. ball.

    POST 2.1.4 Time and pitch zone of 439 goal POST 2.2.1, POST 2.2.4 Actions of winning scoring opportunities in semi-elite women’s teams in 31 sets of female beach volleyball.

    games. Other POST 2.1.5 Effect of limiting ball touches on POST 1.2.5 Retrospective survey of training of spatial interaction in a trial of 18 under-17 229 female and male adult players during elite players in small-sided games. earlier stages of development. POST 2.1.8 Network analysis to identify at-

    tacking plays in two teams of a premier Other Individual Sports

    league. Performance Indicators Performance IndicatorsGoal Keeper POD 14.2 1RM strength and shot-put perfor-POD 2.5 Analysis system for the goal keeper mance of 29 females and 24 males at nation-developed from 15 interviews. al collegiate level. POD 9.4 Comparison between training (1 wk) POD 14.4 Movement elements, synchronicity and match actions (92 games) of goal kee-and space utilization of rhythmic gymnasts pers. in three international championships. POST 2.1.3 Network analysis for role of goal-POST 2.3.2 Pivots and other movements of keeper in 61 passing sequences in three eight rhythmic gymnasts in a national final. matches of premier league. POD 14.6 Pack size and finishing position in Coach 305 world-championship triathlon races. POD 2.2 Behavior of three head coaches to-POD 11.4 Body sway and shooting accuracy in ward 48 effective and non-effective players 117 biathletes. of various ages. in 72 training sessions. POST 1.4.2 Effects of environment (wind and POD 2.3 Observation effectiveness and know-waves) on boat speed in an international ledge of players and the game in interviews rowing regatta (presenter absent). of eight national-league coaches. POST 1.4.3 Predicting javelin performance

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Hopkins et al.: WCPAS Conference Page 37

    from 438 throws of 20 national-level ath-ning and 30 losing teams in male (?) domes-letes using neural network modeling. tic 20-20 cricket.

    POST 1.4.10 Subjective marking vs objective POST 1.2.8 Movement intensities via heart computerized scoring of 13 national-level rates in 15 ice-hockey players.

    trampolinists. POST 2.2.6 Actions in three under-18 national-

    level ice-hockey matches. Other

    POST 2.2.9 Players' playing time at the water POD 2.1 Case study of experience of a golf polo World Championships. coach as a performance analyst. POST 2.2.10 Momentum in shooting during 20 POD 14.1 "ISOPAR" method to estimate dif-national netball matches. ficulty of any position on a golf course.

    Other POD 14.5 "Help intensity" and incentives in

    Tour de France cyclists since 1947. POD 2.6 Time constraints and efficacy of

    POST 1.4.8 A kinematic analysis of the Yurc-performance analysis in n=? coaches and henko vault in 18 female gymnasts. teams of National v International netball.

    POST 2.3.3 Needs analysis from n=? inter-POD 3.1 Development of a test simulating an views of coaches and athletes in canoe and innings of cricket batting.

    kayak slalom. POD 10.1 Accuracy of umpires’ decisions in

    POST 2.5.8 EMG activity during acrobatic netball.

    back handspring performance in five gym-Sports Medicine & Science nasts.

    POD 4.3 A biomechanical model for move-Other Team Sports ments causing ACL injury.

    Performance Indicators POD 4.1 Monitoring fatigue in 11 trained

    biathletes with an orthostatic heart-rate test. POD 3.2 Using small-sided games to increase

    POD 10.6 Retrospective survey of sporting and exposure to actions and plays for develop-

    academic performance of 242 athletes of ment of young netballers.

    mainstream and elite sport schools. POD 3.3 Analysis of movements and perfor-

    mance in Australian-rules football. Acknowledgements: Teesside University, High Perfor-POST 1.2.7 Accuracy of decision-making in mance Sport NZ and Will's consulting account all contri-

    buted to some expenses for this conference tour, while 13 games of Australian-rules football.

    AUT University provided salary for Will and Kirsten. POD 10.3 Analysis of kicking and striking

    skills in Gaelic football. Published October 2012 ?2012 POST 1.2.6 Sixty kinds of actions of 29 win-

     Sportscience 16, 32-37, 2012

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