Introducton Match analyss s used to nvestgate techncal and tactcal behavors wthn judo studes, and t can also be appled to mprove athletc performance. Ths type of data can be used n a varety of means to provde a descrptve profle of a group, or for gvng feedback about actons of the athlete and hs/her opponents. In the same way, ths nformaton could help n plannng tranng sessons. For example, Gorostaga (1988) cleared orentatons about tme structure and metabolc demands to specfc ftness tranng. In addton, the goal of ths analyss s to understand the way n whch sport sklls are performed, and can provde the bass for mprovng advantage n combats (adapted from Lee, 2002; Barrs & Button, 2008; Calmet, 2009; Nevll et al., 2008). Franchn et al. (2008), for nstance, compared elte and super elte athletes and demonstrated that a greater number of throwng technques and the use of more drectons of attack seem to be mportant to ncrease unpredctablty n judo matches. Durng the coachng process, great emphass s placed on the ablty of coaches to detect and recall all crtcal technque ncdents at a judo champonshp performance, and ths has been carred for many decades n judo (Adam & Couturer, 1976; Matsumotoet al., 1978; Branco, 1979). Pawluk (1966) has quantfed throw down technques and ts scores from two groups of weght categores n the European Tournament of 1966. Results demonstrated that the heavy category used 15 dfferent technques, whle the lght category had 13 varatons. However, the last group dsplayed a wder range of actvtes, wth 638 techncal executons n combat when compared wth the heavy group, wth 440 executons. Judo match analyss has been developng a systematc process ncorporatng scentfc prncples and methods snce about forty years ago, wth the publcaton of texts lnkng scentfc prncples to coachng practce (Pawluk, 1966; Łaksa & Sewor, 1972). Calmet & Ahmad (2004) developed a system for notatng the drecton of attacks n judo matches, and observed that the number of technque varatons used durng compettons was hgher for senor athletes than for chldren. Besdes, hgh-level athletes used 4.7 ± 0.8 attack drectons, whch were more than both senor and chldren groups. However, despte the mportance of ths study regardng the applcablty of the hand notaton system, t s not possble to descrbe matches wth a large number of detals and a hgh quantty of data usng ths method (Hughes & Franks, 1997).
Knowledge of contextual factors, such as tme structure, number of appled technques and drectons, qualty of attacks awarded wth ponts and development of grp forms (v.g. Sterkowcz & Franchn, 2001; Calmet et al., 2006) can potentally affect combat performance. In addton, computerzed notatonal systems enable us to process large sets of data very quckly and wth more accuracy. Judo teams from dfferent countres have been tryng to nvestgate tecncal-tactcal behavors; however, t has been shown that coaches cannot accurately observe and recall all the detaled nformaton requred for a complete nterpretaton of a judo match (adapted from Lee, 2002). There have been many developments n techncal-tactcal analyss determned by the dfferent nterests and needs of scentsts and judo coaches, amng to dentfy crtcal events, often referred to as performance ndcators n judo players (Adam & Couturer; 1976; adapted from Nevll et al., 2008). In general, prevous research about notatonal analyss has reported how the use of computerzed analyss can ncrease precson n results (v.g. Calmet & Ahmad, 2002). However, ncorrect use of computers could nduce error possbltes from ether operator or software (Hughes & Frank, 1997). Added to ths, certan characterstcs are essental n order to carry techncal and tactcal judo analyss; wthout them, lttle credt can be attested for ths type of collected data. Knowledge about the true or crteron value of the analyss and between the observed values are the most mportant ndcaton of qualty. Another mportant characterstc of consstent results s the objectvty n ntra and nter observatons measure, whch concerns the reproductblty of the observed value when the measurement s repeated (Hopkns, 2000; Baumgartner et al., 2006). Despte of the establshed crtera for data acquston, none of the currently avalable techncal-tactcal judo studes have reported nstrumental objectvty n software applcaton (Matsumoto et al., 1978; Hensch, 1997; Sagnol & Bscott, 1997; Sterkowcz e Franchn, 2001; Calmet & Ahmad, 2004; Calmet et al., 2006, Ploszaj, 2007). Snce, as we dscussed, the man attrbutes of software for techncal analyss qualty nclude the reproductblty of the crtera establshed, wth a profound mpact on notatonal analyss of sport (Hughes & Franks, 1997), the purpose of ths paper s to present the objectvty measures of a new computer software for judo matches, called FRAMI.
Methods Procedures Match sample, Partcpants and Objectvty testng In order to verfy objectvty measures, two dfferent levels of champonshps (223 regonal matches and 350 state matches of all categores n juvenle, junor and senor classes from both sexes) were taped usng four Sony cameras model DCR-DVD508 durng the year 2008. For a guarantee of ecologcal valdty, each camera was responsble for one match area, n the same way as coaches and match analysts have prevously done. All partcpants were nformed about the procedures used n the record, and provded ther nformed consent. Next, data objectvty was assessed through ntra and nter-observer testng procedures. Ths nvolved three judo experts, wth more than ten years of practce and degrees n Physcal Educaton, who analyzed judo matches wth ths software after havng receved tranng from 5 to 10 hours about ts use. In ths tranng, experts learned commands on keyboard used for obtanng nformaton on the techncal and tactcal characterstcs from each athlete. For example, n order to record an acton by the blue athlete t was necessary to type F8 on the keyboard (blue athlete), a subcommand tab and choose the varable grp to nsert the code for the confguraton of the grp. The frst expert selected 10 combats (20 athletes) between 573 matches n a randomzed form. The same matches were dvded and the other two experts chose n randomzed arrangement the same 10 combats for analyss. In nterobserver comparson, the frst expert analyzed 20 athletes performances, the second expert analyzed the same 20 athletes and the thrd expert analyzed the same 20 athletes. After ths procedure, the last expert analyzed the same sample two more tmes for ntra-observer testng, wth a 24h nterval between measures (Hopkns, 2000; James et al., 2007).
Identfcaton of judo performance ndcators Indcator nformaton obtaned from prevous studes (Matsumoto et al., 1978; Calmet & Matet, 1987; Gorostaga, 1988; Franchn & Sterkowcz, 2003; Calmet & Ahmad, 2004) was used to formulate the lst of techncal and tactcal behavors used n the computerzed match analyss. Ths group of varables was composed of tme structure (total combat tme, standng combat tme, pause tme, groundwork combat tme, movement wthout contact, grppng tme and tme of techncal aplcaton); executon and orentaton of attack technques; quantfcaton of receved and appled scores and penaltes, and varaton of grppng types. Next, each varable was gven two operatonal defntons, the frst to ad n the dentfcaton of each behavor type (e.g. executon of a standng attack technque was an attempt to throw down the opponent, followng the offcal Kodokan classfcaton for judo technques current n 2008). The second operatonal defnton was to determne whether ths technque or another acton resulted n scores accordng to the offcal referees opnon (Taylor et al., 2008; Internatonal Judo Federaton, 2008). Development, verfcaton and testng of FRAMI-Software Wth the research approved by the Ethcs Commttee, ths software was developed n the School of Physcal Educaton and Sport - Unversty of São Paulo, and wrtten usng Delph C++, from Borland Software Corporaton. The program was verfed durng the makng. The prmary reason for early nvestment n verfcaton actvty was to catch potental errors early before the cost of ther correcton escalated. The requrements of verfcaton actvtes were to determne verfcaton approach, adequacy of requrements, and to generate functonal test data. For desgn verfcaton actvtes there was an attempt to determne consstency of desgn wth requrements, adequacy of desgn, generate structural and functonal test data. After that, the verfcaton actvtes n the constructon stage resded n determnng consstency wth desgn, adequacy of mplementaton, general structural and functonal test data, and applyng test data. The last verfcaton actvty was to check and commensurate the level of redevelopment, n the operaton and mantenance stage (Adron et al., 1982). Data was collected by experts for the duraton of each match usng the performance ndcators descrbed.
Statstcal Analyss Concordance Correlaton Coeffcent The objectvty and valdty of ths software were examned usng the sample concordance and correlaton coeffcent (CCC), suggest by Ln (1989) and calculated wth: 2 Sj ˆ ϕ j =, = 1,2,3, j= 1,2,3, (1) 2 2 2 S + S + ( X X ) exst X n n X k k= = 1, n j X j n X jk k= = 1, n j S n 2 ( X k X ) 2 k= 1 =, n 1 S n 2 ( X jk X j ) 2 k= 1 j =, n 1 ( X k X )( X jk X j ) k= 1 Sj = n 1. wth X k : the k observaton of expert-observaton, n : total observatonal number, = 1,2,3 j= 1,2,3 For estmatng the agreement between the three experts, t was used ths generalzaton of coeffcent above, suggested by Barnhart et al., (2002): exst 2 Sj = 1 j= + 1 ˆ ϕ0 = J J, = 1,2,3, j= 1,2,3 e J = ( J 1) 2 S + J ( X 2 X ) (2) S 2, S, X j e X j = 1 J 1 J = 1 the same defned before. 3 experts The coeffcents assume values between -1 and 1, as the closer t gets to 1, the more concordance wll exst between experts for ths specfc varable. The same procedure was used wthn expert concordance. Transformaton of varables In order to compare the analyses of the temporal structure groups, varables were gauged, beng dvded by the total match tme on the values of each athlete, evaluated by each observer. Ths allowed contnuous varables for the use of the Concordance Correlaton Coeffcent. Therefore, apart from Total Match Tme, a transformaton was carred on for each varable n ths study. For the varables of the group Tme on Each Type of Grp the transformaton was analogous, and the values were dvded by the Total Grp Tme.
Transformatons made on the group Frequency were dfferent for each varable: Number of Pauses, Number of Groundwork Match Tmes and Number of Free Movement Tmes, dvded by Average Pause Tme, Average Ground Fght Tme and Average Free Movement Tme for each athlete, respectvely. Average Tme was calculated from the average of tmes observed on the three evaluators. The other three varables of the group (Number of Transton Tmes, Number of Technques Used and Number of Scores) were dvded by the Average Fght Tme for each athlete, as well as all varables of the Groups of Attempted Technques, of the Orentaton group and the specfcatons of technques from the groups Leg (Ash-waza), Hp (Kosh-waza), Arm (Te-waza) and Sacrfce (Sutemwaza) technques. Bootstrap technque In order to obtan a dstrbuton of the estmated coeffcent and correspondng error measure, the Bootstrap resample technque was used to estmate a dstrbuton of probablty for a better analyss of resemblances on the observatons ntra- and nter-evaluators (Efron & Tbshran, 1993). For each varable, the resample consdered only those athletes from whch one value was observed by at least one evaluator. That beng, the N sze of the bootstrap samples was equal to the total of athletes wth the occurrng varables n queston. From the dstrbuton for each varable, the followng crteron was establshed: the observatons of the evaluators were consdered strong n concordance when the quantle, from whch all samples obtaned a coeffcent value above 0.70, was under or equal to 30%; moderate when ths quantle was between 30% and 60%; and, n the cases when the quantle was superor to 60%, the concordance was consdered weak. The same procedure was carred on for the ntra-evaluator observatons.
Results The ndex and classfcaton of tme structure data are shown on Table 1. Objectvty results showed a strong classfcaton between experts and wthn expert. Table 1.: Index and classfcaton between experts and wthn expert on tme structure analyss. Tme structure Between experts Wthn expert Index Classfcaton Index Classfcaton Combat tme 0.990 Strong 0.999 Strong Tach-waza tme 0.890 Strong 0.993 Strong Pause tme 0.912 Strong 0.986 Strong Ne-waza tme 0.838 Strong 0.999 Strong Movment wthout contact 0.895 Strong 0.992 Strong Tach to Ne-waza transton 0.879 Strong 0.975 Strong Grppng tme 0.838 Strong 0.991 Strong Techncal applcaton 0.848 Strong 0.974 Strong Tach-waza standng technques; Ne-waza groundwork technques The ndex and classfcaton of techncal analyss data are shown on Table 2. In ths group of varables, two groups dd not appear n the analyss. In addton, most of the groups had absolute or strong classfcaton. Just one group was classfed as moderate.
Table 2.: Index and classfcaton between experts and wthn expert on techncal analyss Techncal group Between experts Wthn expert Index Classfcaton Index Classfcaton Leg technques 0.972 Strong 1 Absolute Hp technques 1 Absolute 1 Absolute Arm technques 0.754 Moderate 1 Absolute Sacrfce technques 0.958 Strong 0.957 Strong Arm lock technque 1 Absolute 1 Absolute Pnnng technque Chokng technque Not observed Not observed The ndex and classfcaton of techncal drectons analyss data are shown on Table 3. Ths group showed absolute or strong classfcaton for the most part of varables. Just n two cases the weak classfcaton appeared. Table 3.: Index and classfcaton between experts and wthn expert on techncal drectons analyss Technc Drectons Between experts Wthn expert Index Classfcaton Index Classfcaton Back 1 Absolute 1 Absolute Back Left 0.121 Weak 1 Absolute Left -0.314 Weak 1 Absolute Front Left 0.824 Strong 1 Absolute Front 0.891 Strong 1 Absolute Front Rght 0.915 Strong 0.915 Strong Rght 1 Absolute 1 Absolute Rght Back 1 Absolute 1 Absolute
The ndex and classfcaton of confguratons of grp used data are shown on Table 4. Table 4.: Index and classfcaton between experts and wthn expert on confguratons of grps used. Between experts Wthn expert Index Classfcaton Index Classfcaton Left Collar 0.979 Strong 0.994 Strong Rght Sleeve 0.633 Moderate 0.974 Strong Left Collar and Rght Sleeve 0.958 Strong 0.995 Strong Left Back and Rght Sleeve 0.874 Strong 0.914 Strong Rght Collar 0.965 Strong 0.997 Strong Left Sleeve 0.875 Strong 0.787 Moderate Rght Collar and Left Sleeve 0.909 Strong 0.982 Strong Rght Back and Left Sleeve 0.020 Weak 0.939 Strong Rght Sleeve and Left Sleeve 0.941 Strong 0.994 Strong Rght Collar and Left Collar Rght Collar and Rght Sleeve Left Collar and Left Sleeve Not observed Not observed Not observed
Fgure 1: Number of varables per classfcaton Dscusson Objectvty s an mportant requrement for effectve coachng analyss n accurate and relable data. Prevous research has ndeed studed techncal and tactcal aspects n judo matches, especally tme structure and nterrelatonshps between events wth judo performance. However, techncal and tactcal judo measures have not tradtonally been avalable ncludng these essental factors. Match analyss has been a long-hand procedure and requres several experts. In ths research, however, experts carred observatons n the same condtons, and match analyses were almost totally dentcal: 86.11% of the results were strong or absolute (fgure 1). A large number of researches accurately reported the tme structure analyss of judo matches, ndcatng that t can be an effectve referental for the tranng process. They developed partcular consderatons such as, for nstance, a subjectve analyss of acton ntensty (Castarlenas & Planas, 1997; Montero, 1995; Skorsk et al., 1987; Sterkowcz & Maslej, 1998; Van Malderen et al., 2006). In the current study, experts dd repeated observatons and Table 1 shows a strong classfcaton between them. The table also shows a smlar result wthn experts, wth a strong concordance, whch accurately reflects specfc concepts about tme structure. In the same way, the protocol was able to detect small but mportant changes n tme structure, such as the techncal applcaton tme.
Judo matches are dynamc systems, whose evoluton captures nvarance and change n the collectve behavor of judo players (e.g. Calmet & Ahmad, 2004; Sterkowcz, 1998). Several authors descrbed observatonal techncal analyss, such as one of the frst judo studes about match technques and tactcs, carred by Matsumoto et al. (1978). Ths techncal analyss enables coaches n the techncal evaluaton process both for the opponent and for hs/her athlete, whch can ad match strategy, and s also useful n the teachng-learnng process. Most of the groups of varables presented on Table 2 had absolute or strong classfcaton. Just one group was classfed as moderate, whch demonstrates a good result despte the fact that we used one camera per area, lke coaches usually do. In spte of ths ecologcal valdty, the acquston of data was affected by some nterferences, manly the postonng of the referee between the camera and the athletes. The same case occurred wth the analyses of drecton of attacks. Despte ths natural lmtaton, our study managed to evaluate the ndex and classfcaton of techncal drectons analyss data by the experts. Results showed absolute or strong classfcaton for the most part of varables, and n just two cases a weak classfcaton appeared. Prevous nvestgatons have suggested that one of the most crucal aspects n the combnaton of performance ndcators s the drecton of attacks. However, ths aspect s stll not clear n the lterature. Another prmary goal of judo s the control of space between opponents, and the most effectve means to control an opponent s to control the grp (Weers, 1997). Nevertheless, few studes were conducted analyzng ths component. Adoptng a varable grp rases the level of uncertanty for the opponent and allows more moton varatons durng the match, creatng more offensve and defensve abltes for the athlete to adjust to new stuatons. In the present study, we conducted the crteron of grp wth 12 varatons; however, three were not observed. The data for ndex and classfcaton of grp confguratons, shown on Table 4, suggests that ths group of varables can be analyzed wth combnatons from sleeve, collar and grp on back, whch was dvded n rght and left sdes. In eght dferent confguratons, seven had a strong concordance wthn expert observatons and one had moderate concordance. In addton, few dfferences appeared between experts, n eght dfferent types of grps just one obtaned a weak concordance and one moderate. Although the present research had lmtatons assoced wth vdeo shootng (e.g.: parts of the athletes bodes could stand n front of the full gp vew) sx types among eght obtaned a strong concordance between experts.
Concluson Certan requrements are essental for a good match analyss. In ths research, we tred to present two of the most mportant characterstcs of techncal and tactcal measurements, the nter and ntra objectvty requrements. The present study showed a hgh objectvty n the experts analyss, even wth a small tme of tranng n the FRAMI software. Results revealed overall a strong concordance between and wthn evaluators comparsons. When all the 42 crtera are consdered, expert reples were mostly dentcal (86.11% were strong or absolute). Therefore, ths software can clarfy the understandng of techncal and tactcal judo match analyss wth very good accuracy. The use of an nstrument capable of tracng techncal-tactcal profles of judo athletes s an nterestng approach to understand how athletes use ther sklls n the attempt to wn a competton. Therefore, a computer software that analyzes techncal and tactcal aspects can be useful for the development of tactcal tranng and strateges n order to overcome actons used by opponents. References Adam, J.P., Couturer, G. (1976). Vers une approche nouvelle du judo de haut - nveau. Pars: Sport et plen ar. Adron, W.R., Branstad, M.A., Chernavsky, J.C. (1982). Valdaton, Verfcaton, and Testng of Computer Software. Computng Surveys, v. 14(2): 159-191. Barnhart, H.X., Haber, M., Song, J. (2002). Overall concordance correlaton coeffcent for evaluatng agreement among multple observers. Bometrcs, v.58: p.1020-1027. Barrs, S., Button, C. (2008). A Revew of Vson-Based Moton Analyss n Sport. Sports Medcne, v.38 (12): p.1025-1043. Baumgartner, T.A., Jackson, A.S., Mahar, M.T., Rowe, D.A. (2006). Measurement for Evaluaton. (8 th ed., pp.544). McGraw: New York. Bober, T., Rutkowaska-Kucharska, A., Kulg, L. (1982). Investgaton of the consstency of movements of elte judo athletes. In: Kom, PV, et al. (Eds.). Ex Sport Bol. Champagn, Hum Knetcs. p. 176-182. Branco, J. C. (1979). A observação no judô: recolha efectuada nos campeonatos naconas de 1979 (por categora de peso). Ludens, v. 3 (4): p. 30-52.
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