Match Analysis of Elite Adolescent Team Handball Players

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MATCH ANALYSIS OF ELITE ADOLESCENT TEAM HANDBALL PLAYERS MOHAMED SOUHAIEL CHELLY,1,2 SOUHAIL HERMASSI,1,2 RIDHA AOUADI,1,2 RIADH KHALIFA,1,2 ROLAND VAN DEN TILLAAR,3,4 KARIM CHAMARI,2,5 AND ROY J. SHEPHARD6 1

Research Unit ‘‘Evaluation and Analysis of Factors Influencing Sport Performance,’’ Higher Institute of Sport and Physical Education of Ksar Said, Tunis, Tunisia; 2Higher Institute of Sport and Physical Education of Ksar Said, Tunis, Tunisia; 3 Research Center for Sport, Health and Human Development, Vila Real, Portugal; 4Department of Teacher Education and Sports of Sogn and Fjordane University College, Sogndal, Norway; 5Tunisian Research Laboratory ‘‘Sport Performance Optimisation,’’ CNMSS, Tunis, Tunisia; and 6Faculty of Physical Education and Health, University of Toronto, Toronto, Ontario, Canada

ABSTRACT

INTRODUCTION

Chelly, MS, Hermassi, S, Aouadi, R, Khalifa, R, Van den Tillaar, R, Chamari, K, and Shephard, RJ. Match analysis of elite adolescent team handball players. J Strength Cond Res 25(9): 2410–2417, 2011—The purposes of this study were to examine the activity profile of elite adolescent players during regular team handball games and to compare the physical and motor performance of players between the first and second halves of a match. Activity patterns (video analysis) and heartrate (HR) responses (telemetry) were monitored in top nationaldivision adolescent players (18 men, aged 15.1 6 0.6 years) throughout 6 regulation games (25-minute halves with a 10minute interval). The total distance covered averaged 1,777 6 264 m per game (7.4% less in the second than in the first half, p . 0.05). Players ran 170 6 24 m at high intensity and 86 6 12 m at maximal speed, with 32 6 6 bouts of running (duration 2.3 6 0.3 seconds) at speeds . 18 km
h21; they stood still for 16% of the playing time. The mean HR during play was 172 6 2 b
min21 (82 6 3% of maximal HR). Blood lactate concentrations at the end of the first and second halves were 9.7 6 1.1 and 8.3 6 0.9 mmol
L21, respectively (difference p , 0.05). We conclude that adolescent handball players cover less distance and engage in fewer technical actions in the second half of a match. This indicates that team handball is physiologically very demanding. The practical implication is that coaches should seek to sustain performance in the second period of a game by modifying playing tactics and maximizing both aerobic and anaerobic fitness during training sessions.

C

KEY WORDS time-and-motion analysis, team sports, locomotor activity, heart rate, blood lactate, fatigue

Address correspondence to Dr. Mohamed S. Chelly, [email protected]. 25(9)/2410–2417 Journal of Strength and Conditioning Research Ó 2011 National Strength and Conditioning Association

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ompetitive team handball is an intermittent highintensity body-contact team sport that requires a combination of aerobic and anaerobic fitness to perform a sequence of well-coordinated activities (9,10,15,29,35). Performance in a variety of intermittent team sports has been linked to the participant’s speed, power, strength, agility, and a sustained ability to repeat short highintensity bursts of activity throughout a match, rather than the capacity to sustain a steady submaximal work rate (5). Team handball places a heavy emphasis on sprinting, running, jumping, and throwing (17). A detailed knowledge of the activity profile and how this changes over a typical match would be helpful to coaches not only in perfecting collaboration between players during technical–tactical combinations but also in optimizing techniques and training to sustain performance through the final minutes of play (15,18,19). Several previous studies examined the physiological characteristics of both elite and nonelite adult team handball players (16,17,29,34), but these articles offered no information about the demands placed on team members during competition. The 1 earlier study (35) that collected data on heart rates (HRs), blood lactate concentrations, and other physiological parameters during typical games (35) was based on adults aged .20 years. To our knowledge, no previous studies have examined time-and-motion demands and exercise intensities over the course of adolescent handball games. The aims of this study were thus to examine the activity patterns of elite adolescent players during regular team handball games and in particular to compare the physical and motor performance of players between the first and second halves of a match. We hypothesized that locomotor activity, handball-specific activities, and physiological measures would all show some deterioration in the second period. Information on these issues would provide coaches with a clearer picture of the physical demands imposed on adolescents by team handball and would help in developing training programs and tactics of play to conserve performance during the final minutes of play.

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Journal of Strength and Conditioning Research METHODS Experimental Approach to the Problem

A descriptive approach was adopted to examine as dependent variables the activity profile, technical performance, and physiological loading of elite adolescent players during the first and second halves of regulation 7-a-side team handball games. Eighteen players were each videotaped throughout 6 matches. Match-related performance was summarized in terms of the following parameters: type of locomotor activity (sprinting, high-speed running, jogging, walking), gamespecific actions (passing, shooting, engagement, dissuasion, fixing, dribbling, jumping) and physiological parameters (mean HR, maximal heart rate [HRmax], percentage of HRmax, and blood lactate concentration at the end of each period). A repeated-measures design permitted statistical analysis of differences in performance between the first and second halves of matches. Subjects

Our sample of 18 male team handball players (age: 15.1 6 0.6 years; height: 1.79 6 0.05 m; body mass: 70.1 6 6.7 kg; body fat: 11.0 6 1.2%; training experience: 7.0 6 0.6 years) was chosen from a pool of top national-division adolescent players. All were in good health and had passed a medical examination undertaken by the team physician. The participants and their parents were fully informed about the protocol before participating in the study. Informed consent was obtained from both participants and their parents in accordance with the recommendations of the local ethical committee and current ethical standards in sports and exercise research. Participants were free to withdraw from the study at any time without penalty. Procedures

All testing was completed during the competitive season, 2 months after the beginning of the national championship. Players normally engaged in 4 training sessions per week (;90 minutes per session) and a competitive game at the weekend. Their formal training emphasized technical– tactical skill development (80% of total time); the remaining 20% of time was allocated to strength and conditioning routines. Aerobic development was sought mainly through small-sided drills, as adopted for other team sports such as soccer (28). Explosive power was developed by 5- to 20-m sprints and plyometric jumps and bounds (26). Data were collected between 5.00 and 7.00 PM, and subjects were unaware of the specific objectives of the measurements. After exclusion of the goal keepers, active participants were divided into 3 groups of 6 players according to skill and playing position (stratified randomization) (37), thus forming 3 teams of similar competitive ability (G1, G2, and G3). On 6 occasions over a 2-week period, each of these 3 teams played against each other, thus giving 6 3 6 3 3 = 96 data sets for analysis.

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Yo-Yo Intermittent Recovery Test

The individual’s maximal running velocity and HRmax were determined by a Yo-Yo intermittent recovery test. All players were familiar with this test, which was included in their normal fitness assessment. Twenty-meter shuttle runs are performed at increasing velocities, with 10-second periods of active recovery between runs, until the subject is exhausted. The test can begin at 1 of 2 speeds (4); we followed Krustrup et al. (21) and Castagna et al. (13) in using the level 1 version, which we judged as more appropriate for adolescents (Table 1). Testing was performed on the handball court. A calibrated portable CD player (Philips, Az1030 CD player, Eindhoven, The Netherlands) provided appropriate audio cues (www.teknosport.com, Ancona, Italy). The test ended when the participant either failed twice to reach the finish line in the required time (objective evaluation), or felt unable to complete another shuttle at the required speed (subjective evaluation). The total distance covered (including the last incomplete shuttle) was considered as the Yo-Yo test performance and the velocity associated with this final stage was considered as the individual’s vmax (13). The reliability of the test in this age group was demonstrated by an intraclass correlation of 0.96 (p , 0.001) and an intraindividual coefficient of variation (CV) of 3.8%, values comparable with the previous findings of Krustrup et al. (21) for habitually active individuals. Match Video Analyses

Activities during the games were recorded by 2 digital video cameras (Sony, DCL TRV 130E, Tokyo, Japan) with fixed

TABLE 1. Level 1 Yo-Yo intermittent recovery test protocol.* Shuttle Stage Speed bouts distance Cumulative Stage (km
h21) (2 3 20 m) (m) distance (m) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

10 12 13 13.5 14 14.5 15 15.5 16 16.5 17 17.5 18 18.5 19

1 1 2 3 4 8 8 8 8 8 8 8 8 8 8

40 40 80 120 160 320 320 320 320 320 320 320 320 320 320

40 80 160 280 440 760 1,080 1,400 1,720 2,040 2,360 2,680 3,000 3,320 3,640

*After each 2 3 20-m shuttle-run bout, players engaged in 10 seconds of active recovery, jogging around cones set 5 m from the starting line.

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Handball Match Analysis and Heart Rate fields of vision. The cameras were set up approximately 5 m from 1 court sideline and 10 m above the field of play; their combined view covered the entire court, which was calibrated in 5-m bands. All players except the goal keepers were monitored throughout 6 regular games, yielding 96 data sets. The videotapes were later replayed, with a computerized coding of activity patterns (27) (SAGIT System, Ljubjana, Slovenia). Players were next digitized in real time, using software to follow movements and to determine distances and speeds during each game. To increase precision, a single operator who was thoroughly trained in the necessary skills undertook all digitizing; he had previously analyzed .8 hours of team handball activities. Locomotor activities were assigned to 5 arbitrary categories: standing, walking, jogging, high-intensity running, and maximal sprinting (4), using the methodology of Bangsbo et al. (5) (Table 2). Each player’s locomotor style was studied before analysis, and several validation tests were performed for each locomotor category. To determine the reliability of assessments, analyses were repeated for 5 minutes of actual play at differing speeds (walking, jogging, and running); the spatial and temporal dimensions were well known, because a reference square was used. Intraclass correlation coefficients ranged from 0.89 to 0.96 (39).

TABLE 2. Categories of locomotor activity during a handball game (n = 18). Category Standing Walking Jogging High-intensity running Sprinting

Speed (m
s21)

Speed (km
h21)

0–0.1 0.2–1 1.1–3 5.1–7

0–0.36 0.37–3.6 3.7–10.8 18.1–25

.7.1

.25.1

Velocities attained during the selected categories of activity were determined by detailed videotape analysis of player movements over the marked court distances. The frequency and average duration of each locomotor activity were recorded at 5-minute intervals throughout each game. The distance covered by each category of activity was calculated as the product of total time and mean speed for a given activity. A previous study has indicated a CV of 1–2% for this type of analysis (35).

TABLE 3. Inter and intrasubject coefficients of variation (%) for variables measured during handball match (based on 6match average for each of 18 subjects). Intersubject (n = 18)

Locomotors activities Sprinting distance High running speed distance Jogging distance Walking distance Work–rest pattern Duration of play Duration of rest Specific actions Passes Shooting Engagements Dissuasion Fixing Dribbling Jumping Physiological parameters Mean heart rate Maximal heart rate % Maximal heart rate Blood lactate

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Intrasubject (n = 6)

First half

Second half

All scores

Mean

Range

11.5 13.7 17.0 16.1

18.2 18.4 35.4 9.5

10.9 13.6 22.8 11.2

10.8 12.2 19.7 11.6

8.5–12.3 6.3–22.8 11.2–33.3 9.3–14.6

4.6 3.1

3.8 3.2

3.6 2.5

3.5 2.1

2.1–4.5 1.9–2.2

41.5 29.2 23.2 12.4 12.9 27.7 16.8

16.0 22.3 30.6 10.3 29.0 26.1 17.8

24.5 19.8 17.5 8.7 14.6 23.1 13.7

27.2 20.3 13.3 8.4 13.2 21.9 13.3

26.2–28.2 14.0–24.5 6.4–18.1 3.4–12.9 9.8–15.6 8.5–29.2 7.3–18.4

3.1 4.1 2.2 13.3

3.7 2.6 4.5 46.0

1.6 2.2 2.4 24.0

1.4 1.4 2.2 20.7

1.3–1.5 1.2–1.7 1.3–3.7 13.9–32.7

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TABLE 4. Average duration of a bout of running and subsequent recovery time during the first and second halves of a handball game.* Time of play (s) Time of rest (s) First half 11.9 6 0.5† Second half 11.3 6 0.4 Average for match 14.4 6 1.1

15.8 6 0.5‡ 15.4 6 0.5 19.5 6 0.9

*Mean 6 SD of data averaged over 6 games for each of the 18 subjects. **: One-way analysis of variance with repeated measures shows a difference between first half and second halves of the game (significant at p # 0.01). ***: One-way analysis of variance with repeated measures shows a difference between first half and second halves of the game (significant at p # 0.001).

Technical Activities and Heart-Rate Data

Each game was defined in terms of ÔÔplaying timeÕÕ (the time participants spent on the court, excluding half-time and timeouts). The same video system monitored the specific technical activities of each participant over the same 6 games. Seven specific activities (passing, shooting, dribbling, dissuasion, fixing, engagement, and jumping) were identified and assessed by the same examiner. Short-range telemetry HR monitors (Polar S 810, Polar Electro Oy, Kempele, Finland) were fitted to each player 20 minutes before kick-off, and HRs were recorded successfully from all participants every 5 seconds over the 6 matches. The peak HR observed during the Yo-Yo test was assumed to be the individual’s HRmax (21). Heart-rate

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readings were classified into 3 intensity zones as suggested by Woolford and Angove (40) and the American College of Sport Medicine: very vigorous activity (.85% HRmax), aerobic activity (.65–85% HRmax), and light activity (.65% HRmax). Blood lactate concentrations were determined on samples of capillary blood drawn from the heated ear lobe within 3 minutes of completing each half of a match. Detector strips were read by a hand-held photometer (Lactate Pro; Arkray, Kyoto, Japan). The analyzer (CV 3%) was calibrated against appropriate standards immediately before each test. Statistical Analyses

Each of the 3 groups of players engaged in 6 matches; data from 6 matches were thus available for each participant (96 data sets). Normality of all variables was tested using the Kolmogorov–Smirnov test procedure. Two variables (proportion of time spent jogging and blood lactate levels) showed significant skewing; these values are presented as the median with upper and lower quartiles. Descriptive data for the remaining variables are shown as mean and SDs. Coefficients of variation were calculated to demonstrate the inter and intrasubject reproducibility of all measured and calculated parameters (Table 3). Mean values for match activities and HR were compared for the first and second halves of play, using 1-way analyses of variance with repeated-measures statistical significance being set at p # 0.05. It was judged that a 10% deterioration in the performance of players during the second half of a match would have practical significance; given a sample size of 18 players, to have an 80% chance of demonstrating a 1-sided change with a p # 0.05, variables would require a CV , 12%.

RESULTS

Figure 1. Percentages of total running distance covered, absolute distances covered and standard deviations for each of the five categories of movement adopted in this study. HIR = high intensity running (Mean 6 SD, based on six observations on each of 18 subjects).

The average number of goals scored by G1, G2, G3 (6 matches per group) were 17.7 6 2.2, 19.2 6 6.0, and 21.7 6 3.1, respectively, showing that the 3 teams were quite well matched in terms of ability. Players made an average of 501 6 47 changes of activity during a game (a change every ;5.9 seconds of play). They performed 38 6 6 high-speed runs, with an average duration of 2.0 6 0.6 seconds. The average durations of running bouts and subsequent recovery periods are summarized in Table 4; running bouts were significantly shorter during the second half of the game. The

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Handball Match Analysis and Heart Rate

TABLE 5. Distances (m) covered at selected speeds of movement during the first and second halves of a handball game.* First half

TABLE 6. Number of specific technical actions in the first and second halves of a handball game.* First half

Second half

51.7 6 21.5 5.4 6 1.6 11.3 6 2.6 10.5 6 1.3 10.3 6 1.3 5.6 6 1.5 45.9 6 7.7

49.2 6 7.8 4.7 6 1.0 9.2 6 2.8† 8.8 6 0.9‡ 7.1 6 2.1‡ 5.7 6 1.5 42.8 6 7.6

Second half

Sprint 63.6 6 7.3 34.6 6 6.3† High-intensity 94.3 6 12.9 69.0 6 12.7† running Jogging 604 (499–689) 532 (488–567)‡ Walking 180.9 6 29.1 181.5 6 17.3 *Data are expressed as mean 6 SD over 6 games for each of 18 participants (except data for jogging, expressed as the median (lower–upper quartiles). *: One-way analysis of variance with repeated measures shows a difference between first half and second halves of the game (significant at p # 0.05). ***: One-way analysis of variance with repeated measures shows a difference between first half and second halves of the game (significant at p # 0.001).

Passes Shooting Engagement Dissuasion Fixing Dribbling Jumping

*Mean 6 SD of data averaged over 6 games for each of 18 participants. *: One-way analysis of variance with repeated measures shows a difference between first half and second halves of the game (significant at p # 0.05). ***: One-way analysis of variance with repeated measures shows a difference between first half and second halves of the game (significant at p # 0.001).

percentages of the total running distance and absolute distances covered by the 5 categories of movement are summarized in Figure 1. Significantly larger distances were covered by sprinting, high-intensity running and jogging and lesser distances were covered by walking in the first than in the second half of the game (p , 0.05) (Table 5); the variance of the jogging component was also much increased in the second period (Table 3). A mean of 133 6 15 specific technical activities was identified during a game; these activities occupied some 22%

of playing time. The number of passes, shots, dissuasions, fixing, engagements, and jumps decreased significantly from the first to the second half of the game, but the frequency of dribbling and jumping remained unchanged (Table 6); there was also more interindividual variance in engagements during the second period (Table 3). The mean HR averaged over the 6 games was 172 6 2.1 b
min21 (82 6 3 % of HRmax). The HR exceeded 170 b
min21 (i.e., vigorous activity) for 72% of total playing time, 77.4% during the first half, but dropping to 66.6% in the second half (p , 0.05). Based on the recorded HR (Figure 2), 10% of the playing time was occupied by very vigorous activity, 64% by moderate activity, and 28% by light activity. The mean HR during the second half of the game was significantly lower than during the first half (83 vs. 87% of HRmax) (p , 0.05). In the second half of the game, players also spent more time at intensities between 81 and 85% of HRmax but less time at intensities . 85% of HRmax (p , 0.05) (Figure 3). The mean blood lactate was higher immediately after the first than immediately after Figure 2. Mean heart rate (HR) and corresponding percentage of the individual’s maximal heart rate (% HRmax) the second half of the game observed during the first and second halves of a game (Mean 6 SD, based on six observations on each of 18 (9.7 6 1.1 vs. 8.33 6 0.93 mmol
subjects). **: One-way analysis of variance with repeated measures shows a difference significant at p # 0.01. L21, respectively; p , 0.05);

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as to how far these differences reflect technical factors such as differences in match-analysis systems and game duration (27,34,35). The activity patterns reported here differ from those observed by Souhail et al. (35) in terms of the variety of specific activities undertaken, and the volume and intensity of large-scale rhythmic movements. This could reflect the somewhat greater age of the present participants (15.1 6 0.6 vs. 14.3 6 0.5 years) and differences in the level of play and the number of years of practice. Figure 3. Percentages of time spent in light (, 65%HRmax), moderate (65–85 %HRmax) and very vigorous The present findings suggest physical activity (. 85% HRmax); data presented for the entire game and for the first and second halves of the game (Mean 6 SD, based on six observations on each of 18 subjects). that although elite adolescent handball games elicit similar levels of physiological stress to adult professional competition, the total distance covered by there was also a much greater variance in lactate concenthe younger players is substantially shorter. Movement trations after the second period (Table 3). patterns are affected by many factors, including playing position, tactical disposition, and characteristics of the match. DISCUSSION Nevertheless, the total distance covered by the adolescent handball players is similar to that covered by basketball The present data show that elite adolescent handball players players of similar age (14). In contrast, young male soccer covered about one-eighth of the total match distance of just players (12) cover a distance of 6,204 6 731 m in 2 30over 1,500 m by high-intensity running. During the second minutes halves, with 985 6 362 m (16%) run at high half of the game, many measures indicated fatigue relative to intensities (speed .13 km
h21). Adult soccer players cover performance in the first half of the game; players ran a shorter an even greater distance, 8,000–12,000 m for elite men (5,33) distance, covered less ground at high speed, conducted fewer and 9,000–11,000 m in high-level female players (25). technical actions and had lower values for both mean HR and In this study, the team handball players covered almost average percentage of maximum HR. 7.5% less distance during the second half of the game. The average distance covered per game was 1,777 6 264 m Castagna et al. (12) also observed a 3.8% decrement in the (range 1,500–2,611 m). The distance covered by older distance covered by young soccer players during the second handball players is typically more than twice as great, for half of a match, a finding reiterated in other studies of soccer example, 4,464–5,088 m in adult professionals (27), 4,700– (5,22,38) and elite basketball matches (7). This is explained in 5,600 m for national players (34), and (in an experimental part by an 11.2% decrease of total movement time during match using the same SAGIt software as ours) an average of the second half, probably reflecting growing muscular 4,790 m for 2 Slovenian first-league teams (34). However, it fatigue (12). must be emphasized that the total playing time is shorter for Comparisons between handball and other team sports are young players. Sibila et al. (34) noted that left back players limited by differences in rules, field of play, and duration of the covered an average of 3,464 m and left wing players 3,557 m, game, but some useful comparisons can be made with other underlining that the wings covered a greater distance than team sports that demand intermittent spurts of activity (30). other players. The percentage of the total distance covered at In team handball, the percentage of the total distance covered high and maximum intensity running was also less in our at high and maximum intensity running is greater than in study than that seen in the Slovenian team (34). Sibila et al. basketball (24) but less than in soccer (3,31). However, all 3 (34) included a video study of 8 Kuwaiti national team types of competition impose high physiological demands. players, noting 5 types of locomotor activity (walking, slow Indeed, defining ‘‘rest’’ as standing, walking or jogging, and running, sprinting, backward running, and sideways movework as the distance covered by high intensity or sprinting, ment), and movements with and without the ball. The total the work-to-rest ratio for our handball players was 1:2. Our distance covered in the Kuwaiti study was 2,478 6 224 m, data showed a slight decrease in the relative distance covered much more comparable with our findings. It remains unclear VOLUME 25 | NUMBER 9 | SEPTEMBER 2011 |

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Handball Match Analysis and Heart Rate by high-intensity running during the second half of a match, but the same time was spent in walking. There has been no previous study of technical activities in adolescent handball players. Nevertheless, 1 analysis in nonelite adults (36) found that backs averaged more passes and shots than players in other positions. Similar observations were noted concerning jumps and engagement (36). Reported dissimilarities probably reflect differences in the nature of the games, team handball requiring mainly spot shuffling (14,27). The mean HR and percentages of HRmax that we observed were similar to those previously recorded for young team handball players, professional team handball players, and for football, basketball and futsal players (1,3,6,20,23,24,32,35). The team handball player’s HR remains above 85% of maximum for an average 83% of playing time and the player is engaged in very vigorous physical activity for .80% of a game. Furthermore, and in contrast with other sports such as basketball, soccer, and rugby, the HR rarely falls below 150 b
min21. This substantiates our claim that team handball is physically very demanding, with an anaerobic demand greater than that in many team sports. We observed a reduction in mean HR during the second half of the game, as also seen in soccer (164 vs. 154 b
min21) (3). Also, the player’s HR less frequently exceeded 170 b
min21 in the second half of the match, again mirroring findings for other field sports (3,6). The high blood lactate concentrations confirm a substantial use of anaerobic energy (24). Lactate concentrations were similar to those previously reported in young male team handball players (35). Blood lactate concentrations as low as 4–5 mmol
L21 have been observed in young soccer players, but during adult soccer competition values have reached 14 mmol
L21 (11). Our findings suggest that handball players need lactic acid–tolerance training to improve their intramuscular buffering capacity. Bishop et al. (8) underlined the importance of H+ neutralizing capacity to maintain performance during repeated short sprints. However, aerobic training is also necessary to improve the elimination of lactate during recovery intervals; if oxygen availability is impaired, lactate accumulates, limiting the player’s ability to sustain a high power output (2). We conclude that adolescent team handball players develop a high level of aerobic energy expenditure throughout a game, with superimposed episodes when there is considerable anaerobic energy turnover. Further, fatigue leads to deterioration in both physical and motor performance in the second half of a match.

PRACTICAL APPLICATIONS This study provides the first detailed analysis of movement patterns and the resulting physiological demands placed upon elite adolescent handball players. A combination of high aerobic and anaerobic demand reduced their ability to maintain high-intensity running in the second halves of matches. This finding is important both for coaches who are

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developing team specific training programs, and sports scientists who should be encouraged to study factors that contribute to the progressive deterioration in performance over a game. Plainly, a team’s competitive ability may be enhanced if performance can be sustained into the final minutes of play through some combination of altered tactics and the development of aerobic and anaerobic fitness. The optimal approach will likely prove professional conditioning by intermittent high-intensity endurance exercise, plus the avoidance of unnecessary rapid movements early in the game.

ACKNOWLEDGMENTS The authors would like to thank Dr. Helmi Ben Saad (M.D., Ph.D., Laboratory of Physiology, Faculty of Medicine of Sousse, Tunisia) for valuable statistical help. We also thank the ‘‘Ministe`re de l’enseignement supe´rieur et de la Recherche Scientifique, Tunisia’’ for financial support.

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