Exercise and Sport Sciences

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Open Access
Analysis of tries scored during the 2018 and 2019 super rugby tournaments
(University of the Free State, 2021-11) Greef, Gabriel Pieter; Coetzee, F. F.; Kraak, W. J.
Introduction: The last few years, the professional rugby union defensive system improved and lead to teams scoring fewer tries. The growth of professionalism in sport has aided this with many teams now having a performance analysis staff to support the coaching process. Part of their job is to analyse performances of their teams and conduct analysis on opposition teams to then share this information with the management and support team. Analysing and understanding the performance indicators pertaining to tries can assist coaching staff with information to develop and rethink attacking strategies. Aim of the study: The primary aim of the study is to analyse the try scoring profile of the 2018 and 2019 Super Rugby competition. Methods: The current study included all the Super Rugby matches that was played during the 2018 and 2019 seasons. Video footage of all Super Rugby matches were supplied by the South African Rugby Union technical department. All videos was then analysed according to set performance indicators using Nacsport Scout+ video analysis software. All data was captured using data Microsoft Excel software. Results: The current study revealed that tries were responsible for most of the modes of scoring and points for both the 2018 and 2019 rugby seasons. The results indicated that during 2018 the percentage points contribution of tries was 65% (4,570 out of 7,069) and during 2019 it was 46% (811 out of 1,779). When looking at zonal locations where the tries orginated from the results revealed that 75% of the tries for the 2018 and 2019 seasons originated from the attacking half of the field (Zone A & B) and 64% Channel 1. Lineouts were the set piece origin for 37% and 39% of the tries for 2018 and 2019. Turnovers won were the general play origin for 22% of the tries for both the 2018 and 2019 seasons. Conclusions: In summary, tries were scored originating from all over the field, but more tries were scored in Zone A and B. Tries originated from several different possession platforms, where set pieces: lineouts and general play: turnovers won were the main ones platforms in both 2018 and 2019 seasons. Fundamentally, coaches and specialist attacking coaches will be able to use these try scoring profiles to improve technical and tactical skills and develop a framework to plan and execute effective plays and tactics in training to score more tries and concede less tries in matches. The results found in this study can be used to guide further research around this topip. Future studies should compare the findings with that of other professional rugby tournaments for the example the United Rugby Championships, Top14 and the newly formed Super Rugby tournament. Lastly, research should focus on the try scoring profile in women’s rugby to see if similar trends are evident.
Open Access
Attitudes and insights of Free State Swimming coaches towards scientific coaching principles
(University of the Free State, 2013-02) Jones, Colleen Jo-Ann; Bloemhoff, H. J.; Coetzee, F. F.
English: Objectives: The aim of this study is to determine the attitudes and insights of swimming coaches in the Free State Aquatics region towards scientific coaching principles. A comparison between performance coaches and participant coaches’ scientific coaching principles to improve performance or participation levels in swimming were recorded. Methods: This study was done by sampling data via quantitative research (i.e. a questionnaire). All swimming coaches who were at least 18 years old, regardless of their level of qualification, affiliated or not with Free State Aquatics, were invited to participate in the study. A questionnaire was compiled using data from various research sources. All coaches were categorised into a participant or performance coach. The researcher captured data from the data forms to Microsoft Excel. A statistician conducted further analysis using SAS Version 9.1.3. Frequencies and percentages were calculated for categorical data. For numerical data, where data were evenly distributed, means and standard deviations were calculated. Medians and percentiles were calculated where data were not normally distributed. The Student’s T-test was used to compare mean values between the two groups, whereas the Kruskal-Wallis test was used to compare median values. The appropriate p-values and/or confidence intervals were reported. For the dependent data, the mean or median differences were calculated within the groups. The Student’s T-test, or Wilcoxon signed rank test, was used to test for significant median differences. A Fischer Exact test was used to test for significant frequency differences. A significance level of p ≤ 0.05 was used throughout the research study. Results: Seventy one percent of the participant coaches and 29% of the performance coaches participated in the research study. Out of a total of 42 participants (coaches), 21% were male and 79% were female. An alarming result was that 36% of coaches had no qualifications in swimming coaching whatsoever, but are currently involved in coaching. Almost half (46.7%) of the participants have no swimming coaching qualification, while 41.7% of the performance coaches only have a ‘Learn to Swim’ qualification. Only 23.8% of all coaches (participant and performance coaches) are registered with SSA, which is compulsory. Therefore, 76.2% of all coaches are not compliant with SSA rules and regulations pertaining to a coach. As expected, performance coaches rated professional knowledge (50%) and interpersonal knowledge (58.4%) as very important. This differs from participant coaches who indicated that professional knowledge (50%) was important to them. Performance coaches preferred learning methods through internal learning (75%) and unmediated learning (58.4%). Participant coaches reported that internal learning (56.7%) and mediated learning (40%) were their preferred learning methods. Differences between performance and participant coaches’ characteristics are passion and enthusiasm and love for the sport, as demonstrated by performance coaches. This is contradictory to the main goal of participant coaches who would like to instil an element of fun in swimming, in order for the swimmers to gain passion and enthusiasm and ideally love for the sport so that they continue with swimming. In comparison, a participant coach’s role as a friend differed significantly from performance coaches (p = 0.0437). This coincides with their strategy of integrating professional and personal life while coaching. There was no significant difference between participant and performance coaches with regard to the multi-disciplinary involvement in performance improvement. Conclusions: It is alarming that almost half of the current swimming coaches have no qualifications at all. SSA and FSA must enforce stricter rules and regulations regarding coaching, so that all coaches have the minimum qualification in relation to their level of coaching. Various learning methods must be employed to develop numerous knowledge components to achieve optimal scientific coaching.
Open Access
Biomechanical analysis of foot contact in junior sprinters
(University of the Free State, 2011) Hugo, Elmie; Coetzee, F. F.; Opperman, M. C.
English: The purpose of this study was to determine the effects of different foot types (normal, flat and high arch) with regards to speed, roll-over and impact forces, thus attempting to indicate if a specific foot type is dominant amongst sprinters. The different foot types of ten junior sprint athletes and ten nonsprinters were determined by walking over a pressure platform (RSscan International’s Footscan® 7.x plate system). The effects of foot roll-over and peak pressures during sprinting were determined for left and right feet respectively. The subjects ran barefoot at their top speed (sprinted) over 20 meters, crossing a pressure platform (RSscan International’s Footscan® 7.x plate system) comprising the last two meters of the 20 meter distance. The initial contact, final contact, time to peak pressure and the duration of contact of the different sub-areas of the foot were measured. The results of the sprinters’ trials were averaged and compared to the non-sprinters’ averaged trials by performing a statistical T-test. The control group (non-sprinters) dominantly has a high arch foot type for both feet. In the sprinter group, the different foot types are all represented almost equally with regards to right feet, whereas the left feet are dominantly normal type, followed by high arch and then flat foot types. There was a significant difference (p < 0.05) during the Foot flat phase (FFP) between the sprinter group (mean left: 4.04ms, mean right: 4.34ms) and control group (mean left: 26.40ms, mean right: 24.46ms), left: p=0.007; right: p=0.022. This indicates that the FFP time is significantly faster for the sprinter group than for the control group. The control group spent a higher percentage of time on the rear foot than the sprinters did (left: p=0.0057, right: p=0.0268). The control group’s peak plantar pressures were predominantly on the sub-areas of the heel (mean:HL=Left: 327.69, right: 351.44; mean HM= Left: 434.08, right: 423.19) and M1, M2, M3, whereas the sprinters’ peak plantar pressures are predominantly on the subareas of the M1, M2, M3, mid-foot and T1, meaning that sprinters predominantly have peak pressures on forefoot contact whereas the nonsprinters predominantly have peak pressures on heel contact. The results of this study therefore indicate that in general, sprinters dominantly have a normal foot type whereas the non-sprinters have a high arch foot type, and sprinters predominantly have peak pressures on forefoot contact whereas the non-sprinters predominantly have peak pressures on heel contact during sprints.
Open Access
A conceptual framework to improve the reporting quality of strength training exercise descriptors in anterior cruciate ligament reconstruction rehabilitation programs
(University of the Free State, 2023) Vlok, Arnold; Coetzee, F. F.
𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 Muscle weakness after anterior cruciate ligament reconstruction (ACLR) is persistent and associated with abnormal biomechanics, poor knee function, new knee injury and development of osteoarthritis. The proposed drivers of persistent muscle weakness after ACLR are changes in muscle morphology, atrophy-inducing cytokines in the knee joint, and neurological alterations on a cortical and spinal level. The most accessible approach to target muscle weakness is various types of strength training exercises. However, another explanation for persistent weakness after ACLR rehabilitation could be that programs are not following the best practice for strength training. Failure to improve muscle strength after ACLR could be caused by faulty programming of exercise descriptors (e.g., exercise type, frequency, load). 𝐀𝐢𝐦 The main aim of this study was to develop a conceptual framework to improve the reporting quality of strength training exercise descriptors in ACLR rehabilitation programs. 𝗠𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝘆 The study was conducted in three stages, including a Scoping Review, focussing on which strength training exercise descriptors are reported in ACLR research after ACLR surgery, and comparing the current standards of reporting ACLR strength training exercise descriptors to international best practice strength training guidelines. The modified e-Delphi survey was utilised to formulate a conceptual rehabilitation framework for ACLR. The last stage included validating the preliminary ACLR conceptual framework that included a core outcome set (COS) of strength training exercise descriptors for reporting after ACLR. 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 𝗮𝗻𝗱 𝗱𝗶𝘀𝗰𝘂𝘀𝘀𝗶𝗼𝗻 We extracted data on 117 exercises from 41 studies. A median of seven of the 19 possible exercise descriptors were reported (range 3-16). Reporting of specific exercise descriptors varied across studies from 93% (name of the strength training exercise) to 5% (exercise aim). On average, 46%, 35%, and 43% of the exercise descriptors included in the ACSM, CERT, and Toigo and Boutellier guidelines were reported, respectively. The e-Delphi results from 27 ACLR experts regarding the 21-exercise descriptor definition was 100% consensus agreement (>80% agreement), also 100% consensus agreement on a COS of strength training exercise descriptors (). However, very low consensus agreement on exercise dosages prescribed in ACLR strengthening programs. The validation meeting consisted of four panellists that validated the preliminary ACLR conceptual framework and proposed to re-organise the 13 COS of exercise descriptors into levels of importance regarding the frequency of reporting. 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻 The proposed ACLR conceptual framework for researchers and clinicians provided a platform for the reporting of strength training rehabilitation after ACLR. Improving the reporting quality of strength training exercise descriptors, definitions, and exercise dosages for ACLR rehabilitation programs can aid in the transfer of ACLR rehabilitation research towards private practice. Therefore, enabling clinicians to implement evidence-based strength training exercise configurations.
Open Access
Developmental coordination disorder in children: assessment, identification and intervention
(University of the Free State, 2020-11) Du Plessis, Aletta Margaretha (Alretha); De Milander, M.; Coetzee, F. F.
𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻: Developmental coordination disorder (DCD) is a motor skill disorder that affects children worldwide, with various prevalence rates reported in the literature. Approximately 60% of children in South Africa (SA) come from low socio-economic (SE) environments. It is, therefore, essential to determine the prevalence of possible DCD in these environments. Although various screening tools are available for identifying possible DCD, teachers' ability to use the Movement Assessment Battery for Children-2 (MABC-2) Checklist has not been established. Furthermore, children with DCD and possible DCD will continue to experience motor difficulties if motor intervention is not provided. A motor intervention guideline for children with DCD in SA in the field of Kinderkinetics has not been established. 𝗢𝗯𝗷𝗲𝗰𝘁𝗶𝘃𝗲𝘀: The first objective was to determine the prevalence of possible DCD in Grade 1 (Gr. 1) learners in a low SE environment in Mangaung, SA, using the MABC-2 Performance Test. Secondly, the study aimed to establish teachers' ability to identify Gr. 1 learners with possible DCD in low SE environments using the MABC-2 Checklist. Finally, an e-Delphi survey was used to develop a motor intervention framework as a guideline for Kinderkineticists to help children with DCD or possible DCD within the South African context. 𝗠𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝘆: Two hundred and forty-two (N=242; 51.2% boys, 48.8% girls) Gr. 1 learners, 6–8-year-old from a low SE environment (quintile 1–3 schools) in Mangaung Metro, Motheo District, Free State (FS) Province, participated in study objective one. Possible DCD prevalence was determined using the MABC-2 Performance Test. For the second objective, the study was conducted in the same environment. Gr. 1 learners 6–8-year-old (N=200; 49.5% boys, 50.5% girls) and 29 female class teachers of the Gr.1 learners participated in the study. The convergent validity of the MABC-2 Performance Test and Checklist completed by teachers was determined. Lastly, for objective three, 29 Kinderkineticists in SA with expert experience participated in a three-round online e-Delphi survey by answering questions related to motor intervention for children with possible DCD. 𝗥𝗲𝘀𝘂𝗹𝘁𝘀: The results of objective one showed that the prevalence of possible DCD found in the Gr. 1 learners was 9.9%. The gender results indicated a possible DCD prevalence of 10.5% for boys and 9.3% for girls. No statistically significant difference between the boys and girls was found (p=0.94). The results concerning objective two indicated that the movement specialists identified more learners (90%) in the non-DCD group (> 15th percentile) than the teachers (54%). The teachers wrongfully identified 46% of the learners with possible DCD, who were not identified with possible DCD according to the movement specialists. The movement specialists identified 10% of the learners with possible DCD. Only a slight agreement ((k=0.17) was found between the MABC-2 Performance Test and Checklist when the ≤ 15th percentile was used as a cut-off score. The sensitivity was 85% and the specificity 58%. In the e-Delphi survey, consensus (80%) was reached on 51/89 questions in round one, 89/144 for round two, and 12/30 in round three. A motor intervention framework was developed using the feedback of each round from the participants where consensus was reached. 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻: The prevalence of possible DCD in low SE environments in Mangaung of Gr. 1 learners was higher than the worldwide estimated prevalence of DCD (5–6%). It is recommended that when teachers use the MABC-2 Checklist, the Performance Test should be performed in conjunction with the Checklist to obtain the most reliable results. A motor intervention framework was developed as a first draft to use as a guideline by Kinderkineticists, focusing on intervention planning, goal-setting, intervention approaches, intervention apparatus, intervention delivery mode, additional role players, settings, dosage, and evaluation.
Open Access
Effect of short-term macronutrient manipulation on endurance capacity of long-distance runners
(University of the Free State, 2020-11) Deacon, Lizl; Coetzee, F. F.; Coetzee, B.; Du Toit, W. C.
Introduction: The influence of specific nutrition programmes on optimal endurance performance enjoys wide interest. However, limited knowledge in this regard accentuates the need for further research on optimal nutrition for individual endurance performance optimisation. Objectives: (i) To investigate differences in the effects of a short-term (48-hour) highcarbohydrate (high-CHO) versus a high-FAT diet on indirect respiratory indices of long-distance runners, namely maximal oxygen consumption (V̇ O₂max), oxygen consumption (V̇ O₂), carbon dioxide output (V̇ CO₂), respiratory exchange ratio (RER), minute ventilation (V̇ E), and substrate utilisation (CHO oxidation and fat oxidation), as well as on physiological and perceptual measurements such as time to exhaustion, absolute (W) and relative power output (W/kg) and work output (kJ), during a treadmill graded exercise test (GXT) to exhaustion. (ii) To determine certain threshold points that occurred during the GXT, including ventilatory threshold 1 (VT1), ventilatory threshold 2 (VT2), lactate lhreshold (LT), peak oxygen uptake (V̇ O₂peak) and maximal oxygen consumption (V̇ O₂max) after the high-CHO and high-FAT trials, respectively. (iii) To explore individual preferential fuel source use over a short-term period to enhance performance. Methods: This was a randomised controlled cross-over trial assessing the effects of a 48-hour high-CHO (67%CHO, 17%fat, 16%Prot) or 48-hour high-FAT (65%fat, 21%CHO, 14%prot) diet amongst 24 well-trained male endurance runners. After each 48-hour diet period and an overnight fast, the participants completed a GXT consisting of 3-minute stages with 1 km/h increments until exhaustion. The two dietary treatment periods were parted by a two-week washout period. The study treatments were compared with respect to the various measurements using ANOVA with diet, participant and period as fixed effects. From these ANOVAs, the mean values for each study treatment (high-FAT and high-CHO diets) were calculated, including a point estimate and 95% confidence interval (CI) for the mean difference "high-FAT – highCHO", the p-value associated with a test of the null-hypothesis of no difference between treatment means, and the effect size calculated as the ratio of the point estimate of the mean difference divided by the residual standard deviation from the ANOVA. Results: No statistically significant differences were observed between the diets with regard to any of the indirect indices measured [V̇ O₂max, V̇ O₂, V̇ CO₂, RER and V̇ E and carbohydrate oxidation (CHOox) and fat oxidation (FATox] as well as LT. Furthermore, no statistically significant differences were observed with regard to the physiological and perceptual responses (RPE, HR, time to exhaustion, work and absolute and relative power output). Moderate effect sizes were observed for V̇ O₂ at VT1 (d = 0.58) and at VT2 (d = 0.41), and for V̇ O₂max at VT1 (d = 0.61) and VT2 (d = 0.47). Otherwise, moderate effect sizes were observed for speed at VT1 (d = 0.48) and HR at V̇ O₂max (d = 0.41). For fat contribution, moderate effect sizes were observed at both VT1 (d = 0.40) and VT2 (d = 0.43), and a medium effect size at V̇ O₂max (d = 0.56). Conclusion: No statistically significant differences were seen between the effects of the short-term high-CHO and high-FAT diets on any of the respiratory and other indices measured in endurance runners during a GTX to exhaustion. However, some moderate effects sizes observed for some of the indices either favouring high-CHO or high-FAT depending on the individual, suggest that further research is justified, possibly involving longer-term diets.
Open Access
Factors associated with injuries sustained by players during a Currie Cup rugby competition
(University of the Free State, 2004-10) Le Roux, Douglas Leonard; Holtzhausen, L. J.; Coetzee, F. F.
English: The aim of this study was to review the available literature on the epidemiology of injuries in professional rugby, and then to collect data on previous injuries and the influence of external factors on rugby injuries. Secondly, the incidence, nature and circumstances surrounding injuries in a cohort of professional South African provincial rugby players were documented. The data collected was compared with available data in order to determine trends of injuries that, if taken into consideration, could possibly lead to the prevention of injuries to future rugby players. No study has been done on injury rate and frequency in the Currie Cup competition. Being the cornerstone of providing players for competitions like the Super 12 and Tri-nations, it is certainly appropriate to record the incidence and nature of injuries in the Currie Cup competition. This study attempted to identify factors associated with injury, to direct further analytical research and suggest measures to reduce injury rate. It also drew a comparison between results obtained through this study, and results obtained by other relevant studies in other competitions. The epidemiological data used in this study were collected from two professional rugby teams that competed in the 2002 Currie Cup Rugby Competition. This competition is held annually in South Africa and includes provincial teams from 14 regions in South Africa.
Open Access
Morphological and skill-related fitness components as possible predictors of injuries in elite female field hockey players
(University of the Free State, 2014) Naicker, Marlene; Coetzee, F. F.
Introduction: The incidence of injury in female field hockey players is high, but there is little data on the physical demands of the game or the injury risk factors. Objective: To establish an athletic profile of elite female field hockey players and to determine if morphological or skill-related factors measured in the pre-season can predict injury in the in-season. Methods: Thirty female field hockey players comprising the South African national field hockey team underwent pre-season testing. These tests included anthropometry, balance, flexibility (sit and reach test), explosive power (vertical jump test), upper and lower body strength (bench and leg press), core strength, speed (10 m, 40 m and repeated sprint test with and without a hockey stick), agility (Illinois test) and isokinetic testing of the ankle. Also included was a questionnaire to collect information on demographic data, elite-level experience, playing surface, footwear and injury history. Injuries in training and matches were recorded prospectively in the subsequent season using an injury profile sheet. Players reporting an injury were contacted to collect data regarding injury circumstances. Univariate and multivariate regression analyses were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for ±1 standard deviation of change. Results: A total of 87 injuries were recorded with ligament and muscle injury the most frequent. The highest incidence of injury was the ankle joint followed by the hamstring muscles and lower back respectively. Univariate analyses showed that ankle dorsiflexion strength was a very strong predictor of ankle injuries (p=0.0002), and that ankle dorsiflexion deficit (p=0.0267) and eversion deficit (p=0.0035) were significantly good predictors of ankle injury. All balance indices, i.e. anterior/posterior (p=0.0465), medial/lateral (p<0.0001) and overall (p<0.0001), constituted the other pre-season performance measures showing significant potential to predict ankle injury. For lower leg injuries, univariate associations were found with ankle inversion deficit (p=0.0253), eversion deficit (p=0.0379) and anterior/posterior balance index (p=0.0441). Conclusion: Dorsiflexion strength and all balance indices were strong predictors of ankle injury while ankle inversion deficit, eversion deficit and anterior/posterior balance were associated with lower leg injuries in elite female field hockey players.
Open Access
The motor proficiency of obese 8-11 year old children
(University of the Free State, 2005) Potgieter, Carolina Frederika; Botes, S. L.; Coetzee, F. F.
English: A rapid increase in the prevalence of obesity in children has been seen around the world. There was a 60% increase in the prevalence of being overweight and a 70% increase in the prevalence of obesity between 1989 and 1998 (Ogden et al., 1997:1, Reilly et al., 1999:1039, Martorell et al., 2000:959). What’s more, motor abilities can be influenced by excess weight from a very early age. Groups of normal weight and obese babies were compared, and a delayed gross motor development was found in the obese. A significant correlation was found between excessive weight and gross motor delay. Over the following year, both weight and motor development reverted to normal in the majority of infants (Jaffe & Kosakov, 1982:619). Parizkova (1996) found that the potential deteriorating effect of excess fat on dynamic performance increases with age and the longer the duration of obesity. This researcher discovered that in preschool children, the effect of increased weight and body mass index is only apparent in some areas, such as broad jump and the 20 meter dash, and much less so in other measured variables. The significant effect of increased weight and fat is most marked during puberty. From the above mentioned statistics and research, the question is raised on whether obesity has an influence on the motor proficiency of 8-11 year old children. The first goal of the study was to identify 30 children with obesity (age 8-11) and 30 non-obese children (age 8-11) to form the control group. Body mass index was used as criterium to determine obesity. Boys with a body mass index of 18- 21kg/m2 and girls with a body mass index of 18-22 kg/m2 were identified as obese, while the control group all had a body mass index of less than 18kg/m2. Fat percentage was determined using the Heath and Carter method (skinfolds of the triceps, sub-scapula, para-umbilicus, supra-iliac, medial thigh and medial calf) (Heath and Carter, 1969:57). Furthermore, somatotyping has been used for the estimation of body composition. Somatotyping of an individual is expressed by a three digit evaluation comprising three consecutive numbers (rated from lowest to highest, 1-7) and always listed in the same order. Each number represents the evaluation of a basic component, endomorphy (relating to relative adipose), mesomorphy (relating to skeletal muscle development), and ectomorphy (relating to the relative linearity of the body). There after, the obese (n=30) and non-obese (n=30) children, age 8-11, were evaluated with the Bruininks-Oseretsky test (Bruininks, 1978) to determine their motor proficiency. The Bruiniks-Oseretsky Test of Motor Proficiency is an individually administered test that assesses the motor functioning of children from 4½ to 14½ years of age. The complete battery – eight subtests (Running Speed and Agility, Balance, Bilateral Coordination, Strength, Upper Limb Speed, Response Speed, Visual Motor Control and Upper Limb Coordination and Dexterity) comprised of 46 separate items – provides a comprehensive index of motor proficiency as well as separate measures of both gross and fine motor skills. The Short Form – 14 items from the Complete Battery – provides a brief survey of general motor proficiency (Bruininks, 1978:11). The data was analyzed by means of the t-test. This test was used because it is the most commonly used method to evaluate the differences in means between two groups. The study revealed that there was no significant difference in any age group (8, 9, 10 or 11) between the motor proficiency of obese versus non-obese children. This is in contrast with the hypothesis that states that there will be a significant difference between the motor proficiency of obese versus non-obese children. Although the study can conclude that there was no major difference between the two groups, obesity remains a concern. The prevalence of this epidemic is rising year after year and it is therefore recommended that obesity should be prevented as far as possible and that those who suffer from obesity should be treated as soon as they are diagnosed with obesity. Treatment of obesity is most successful if realistic goals are set; a balanced diet is emphasized; a safe rate of weight loss of about 0.5 kg a week is achieved through moderate reduction of energy intake (about 20-25% decrease); increased physical activity is emphasized as much as diet; parental support is strong and behavior therapy is provided to help both child and parents achieve the diet, exercise and behavior goals (Frühbeck, 2000:328). Another concern is that the motor proficiency of children between 8 and 11 years is not what it is suppose to be. Both the obese and non-obese group had a low score of motor proficiency, which means that they were probably never exposed to appropriate motor development in their early childhood years. It is therefore recommended that more attention be given to early motor development to help children improve their motor proficiency which is essential for the performance of specialized movements in later childhood and adolescence. Motor development programs may be implemented in pre-school and primary schools as part of the curriculum.
Open Access
A perceptual-motor intervention programme for grade 1-learners with developmental coordination disorder
(University of the Free State, 2015-02) De Milander, Monique; Coetzee, F. F.; Venter, A.
English: Background Developmental coordination disorder (DCD) is recognised as one of the most common developmental dysfunctions during childhood. Developmental coordination disorder is diagnosed in children who experience significant difficulties in motor learning and in the performance of functional motor tasks that are critical for success in their daily lives. However, one of the major concerns regarding children with DCD is that they are often not formally diagnosed, but rather described by their parents and teachers as lazy or awkward. In an attempt to identify children with DCD, several research tools, such as questionnaires for screening purposes and norm-referenced tests to measure the degree of movement difficulties, can be used. Even though children will not outgrow this disorder as previously believed, children can be helped by means of various interventions. Aims The first aim of this study was to determine the prevalence of DCD among Grade 1 children in Bloemfontein. The second aim was to establish the ability of parents to identify Grade 1 children with DCD at home; in addition the third aim was to establish the ability of teachers in identifying Grade 1 children with DCD in the classroom. The fourth aim was to explore the influence of DCD on learning related skills. Aim five and six was to determine if the application of a perceptual-motor intervention as well as a sport stacking intervention will significantly improve the motor proficiency status of Grade 1 children identified with DCD independently. Method Participants For the purpose of aim 1, 559 participants’ between the ages of 5 and 8 years took part in this study. There were n=321 girls and n=238 boys. Aim 2 include 410 participants and consisted of n=226 girls and n=184 boys, whilst aim 3 had 506 participants and there were n=289 girls and n=217 boys. Furthermore, aim 4 had 347 participants including n=190 girls and n=157 boys. Aim 5 and 6, which relates to the two interventions used in this study was as follows. Seventy six (76) participants took part in the perceptual-motor intervention. The group consisted of girls (n=34) and boys (n=42) classified with DCD. The intervention had a pre-test/post-test experimental design (n=36) with a control group (n=40). With reference to the sport stacking intervention, 18 children between the ages of 6 and 7 years took part in this study. The group consisted of girls (n=6) and boys (n=12) classified with DCD. This intervention also had a pre-test/post-test experimental design (n=10) with a control group (n=8). Measuring instruments The instrument used to assess the participants motor proficiency levels and to identify symptoms of DCD was the Movement Assessment Battery for Children-2 (MABC-2 Test). This test includes manual dexterity, balance as well as aiming and catching, in addition the three sub-tests constitute a total test score. In order to determine if parents possess the ability to identify symptoms of DCD at home the Developmental Coordination Disorder Questionnaire ’07 (DCDQ’07) was used. With the purpose of determining if teachers possess the ability to identify DCD in the classroom the Movement Assessment Battery for Children-2 Checklist (MABC-C) was used. It is designed to identify primary school children likely to have movement difficulties. The Aptitude Test for School Beginners (ASB) was administered by qualified teachers to all participating children in the first two months of the school year. A requirement of the ASB is that it must be presented and completed in a child’s mother tongue. The ASB is a norm-based instrument and consists of eight sub-items, which include perception, spatial skills, reasoning, numerical skills, gestalt, coordination, memory and verbal comprehension. Each sub-item is evaluated by means of a standard score out of five. An evaluation score of 1 is regarded as below average and an evaluation score of 5 as above average. The aim of the ASB is to obtain a differentiated picture of certain aptitudes of grade 1 children. Data analysis Analysis of the data was done by a biostatistician using Statistical Analysis Software Version 9.1.3. Descriptive statistics, namely frequencies and percentages, were calculated for categorical data. Medians and percentiles were calculated for numerical data. Median differences were tested by calculating p-values using the signed-rank test. The Chi-square statistics were used to test for proportion differences. This was used to determine the prevalence of DCD (article 1), as well as for learning related skills and DCD (article 4) and for the sport stacking intervention (article 6). Furthermore, data analysis was performed using the Statistical Package for the Social Sciences (SPSS) for Windows (SPSS version 16.0), in order to determine if parents and teachers possess the ability to identify children with DCD. The convergent validity of the classification of motor problems (no motor difficulties or motor difficulties) using the MABC-2 Test and the classification of motor difficulties (no motor difficulties or motor difficulties) by the parents of the participants using the DCDQ’07 and the teachers using the MABC-C, the kappa (k-) coefficient was used. Finally, the Mann-Whitney-U test was used to compare differences between the experimental- and control group with reference to the perceptual-motor intervention for children with DCD (article 5). Probability level of 0.05 or less was taken to indicate statistical significance. Results The results of aim 1 revealed the prevalence of DCD amongst Grade 1 learners in Bloemfontein is estimated to be 15%. The results also indicate that boys have a significantly higher (p=0.050) prevalence of DCD although marginally when compared to their female counterparts. Aim 2 indicated a 15% convergent validity between the MABC-2 Test and the DCDQ’07, similar results were obtained for aim 3, indicating a 11% convergent validity between the MABC-2 Test and the MABC-C. Therefore, it can be argued that parents using the DCDQ’07 and teachers using the MABC-2 could not identify children with DCD at home or in the classroom. The results in aim 4 indicated the prevalence of DCD to be 12%. Additionally, DCD had a significant effect (p=0.050) on five of the eight learning-related subtypes, namely reasoning, numerical skills, gestalt, coordination and memory. Furthermore, the results of aim 5 indicated that a perceptual-motor intervention only improved balance as a sub-test of the MABC-2 Test. Interesting to note is that children taking part in Physical Education classes presented by the teachers also prove to be beneficial. In contrast, aim 6 (sport stacking intervention for DCD) showed that the intervention had a significant effect (p=0.050) on two of the three sub-tests, namely manual dexterity, balance, as well as the total test score. This suggests that sport stacking can be used as an effective intervention programme for children with DCD. Conclusions The results revealed that the school age children in the current study had a higher incidence of DCD (15%) compared to the findings reported in the literature (5-6%). This information is important, and indicates that appropriate screening tools should be used to identify children earlier. Unfortunately the reliability of the MABC-C and the DCDQ’07 completed by parents and teachers to identify children with DCD was found to be low. Therefore it is recommended that specific norms should be developed for South African children. Furthermore, the results revealed that children with DCD do struggle with learning related skills. This knowledge enables teachers to address the specific needs of children with DCD. It can be concluded that perceptual-motor interventions have more often than not positive effects on children with DCD; however it is recommended that a combination of the bottom-up approach and top-down approach should be used for optimal results.
Open Access
Performance indicators in (ATP) tournaments
(University of the Free State, 2021-11) Carlisle, Jason; Coetzee, F. F.
Introduction: Key performance indicators (KPI’s) are vitally important in the context of sport. Being able to analyse and adapt accordingly to the KPI’s, would be of great benefit to the athletes as well as the coaches. Aim: To differentiate between the KPI’s of winning and losing players of matches played and the surface types and their influence on the outcome of matches. (Player height and age, number of aces hit, 1st and 2nd serve accuracy, points won off the 1st and 2nd serves, number of breakpoints faced, and number of breakpoints saved.) Methods: The current study was conducted in a retrospective manner as a quantitative design. The data was collected from a public domain, GitHub, and consisted of the 2018 ATP Tour. The data collected varied across three surfaces played on, namely Clay, Grass, and Hard Courts. The outcome of the current study was to determine the effects of the KPI’s on the final result of the tennis matches. Results: The current study found significant differences between the winning and losing players with regards to Aces, Service Points, 1st Serves Won, 2nd Serves Won, Breakpoints Faced, as well as Breakpoints Saved, however, no significant difference was found between the 1st Serves In (p=1.368). The current study also find a significant difference with regards to Aces struck (p=0.0006) between Hard and Clay Courts. No other significant differences (p<0.05) were reported across the KPI’s. Conclusion: It is important for coaches and players to note that age and height do not discriminate between winner and losers in men’s tennis as well as 1st Serves. However, all the other KPI’s show significant differences between winner and losers. This information may assist players and coaches in preparing themselves or their athletes to achieve success.
Open Access
Physical activity and lifestyle aspects of female students at a tertiary institution
(University of the Free State, 2013-07) Losper, T'Neil Sarelle; Opperman, M. M.; Coetzee, F. F.; Bloemhoff, H. J.
English: BACKGROUND AND RATIONALE: It is generally believed that a sharp rise in chronic diseases and unhealthy living has occurred. Researchers believe that the modern lifestyle and a lack in physical activity (PA) are the main reasons for this problem (McGinnis, 1992:S196). Chronic diseases and obesity are factors that can be prevented or reduced with physical activity and a healthy way of living. The way in which physical activity can have an indirect influence on conserving health can be explained in two ways: Firstly physical activity can be used as trigger mechanism to change other destructive lifestyle habits (Weinstein, 1987:8; Eddy & Beltz, 1989: 168). Secondly, participation in PA can have an indirect effect on the reduction of coronary diseases because of its reducing effect on depression, anxiety and tension, to name a few (Willis & Campbell, 1992:47). According to Bray and Born, (2004:181) there is an increasing need for physical activity among young adults. Young adults attending universities gain increased control over their lifestyles. However, they may not necessarily develop positive behaviors like regular PA. The lifestyle that students live is questionable. Whether their activity levels are adequate and whether they generally lead to healthy lifestyles is unknown as little research is available on this matter, especially in South Africa. Keating, Guan, Pinero and Bridges (2005:116) stated that it is well known that students' PA as a research topic has been seriously neglected. Young adulthood is considered to be an important phase of life, as many lifelong health behaviour patterns are established during this phase (Timperio, Salmon & Ball, 2004:20). OBJECTIVES: The purpose of the study is twofold: 1. To identify PA levels of undergraduate female students indifferent ethnic groups on a South African university campus, and 2. To establish the lifestyle profile and body composition of female students in different ethnic groups in a South African university campus. RESEARCH METHODS: The sample constituted of female students at the University of the Free State in their 1st, 2nd and 3rd year+ of study residing on the campus. The sample consisted of 244 students (78 1st years, 98 2nd years, 68 3rd years-: 139 black, 21 coloured and 84 white students). The following three research instruments were used: • International Physical Activity Questionnaire (IPAQ) (2012) • Belloc and Breslow's 7 lifestyle habits questionnaire • The Heath and Carter anthropometrical assessment. RESULTS AND DISCUSSION: By comparing the 1st, 2nd and 3rd year groups it is evident that 40.16% of the group as a whole (all ethnic groups) did take part in some form of physical activity. Fifty five point one percent (55.13%) of 1st year female students, 42.86% of the 2nd year and 44.12% of the 3rd year female students participated in PA. The White female students had the highest physical activity participation rate (67.86%), followed by the coloured students (38.10%). The black students' physical activity participation (35.97%) was the lowest. An average of 4 out of the 7 lifestyle habits being followed by the majority of the participants. The majority of participants eat breakfast daily (51.64%) but they do not eat 3 meals per day. Eighty seven present (87.70%) of the sample are nonsmokers, with 77.05% of the respondents consuming little to no alcohol, and at least 66.80% of the group maintains a healthy body weight. Unfortunately their eating, sleeping and exercise habits are not optimal. It is evident that the lifestyle habits of the students decrease from the 1st to the s= year, but that by the time they progress to the 3rd year-, they start trying to change their lifestyles habits to a certain extent. The ethnic groups do not show a significant difference among their lifestyle habits but white female students do have a more positive profile.
Open Access
Positional match statistics in Currie Cup and Super Rugby competitions between winning and losing teams
(University of the Free State, 2016-11) Schoeman, Riaan; Coetzee, F. F.
English: Background Rugby union (here after referred to as rugby), as most other team sports, is becoming more aware of statistics as a reliable method to evaluate players and match variables during match play. This non-invasive evaluation method provides coaches and conditioning coaching with much needed information regarding player attendance to match situations and the successful execution of these match situations. Winning and losing teams from all levels of competitions use statistics to not only evaluate the team’s performance, but to determine which variables might be responsible for the outcome of the game. It is accepted that teams from a winning side might perform better in certain areas of play than losing teams, and players from higher levels of participation can execute certain skills more effectively. Previous research has been conducted on various teams from different participation levels on the physiological differences, mental toughness and match variables. The increased professionalism of rugby players may also indicate an increased ability of players from one season to the next. The ability of players will also vary from one position to the next and may be approximately exposed to certain match variables. Aims The first aim of this study was to determine the tackle and collision count for Super Rugby players during the 2013 competition. The second was to analyse the passing and kicking statistics that discriminate between winning and losing teams during the 2014 Super Rugby season. Thirdly, the study attempted to differentiate between the Super Rugby competition and the Currie Cup competition according to the occurrence of match activities and lastly to evaluate the evolution of the Super Rugby competition from 2011 to 2015 by the use of regression statistics. Method Sample The first aim consisted of conducting an analysis of 1,900 players from 30 games played during the 2013 Super Rugby competition. Two games from each of the participating franchises were used and selected in regards to number of matches available and balance of the sample. The second aim included an analysis of 1298 players from the 2013 Super Rugby season, whilst the third aim involved 1800 players with n=900 players from Super Rugby and n=900 players from the Currie Cup competition. Furthermore, aim 4 consisted of 4500 players and included n=900 from each of the Super Rugby seasons from 2011 to 2015. Measuring instruments Data was supplied by the Cheetahs Super Rugby Franchise, Bloemfontein, South Africa, using the Verusco TryMaker Pro. Verusco has provided Super Rugby teams with TryMaker Pro since the year 2000. TryMaker Pro is the most advanced analysis system custom-made for rugby, and it is the preferred system for the professional teams using Verusco. The Verusco coding centre codes all the games for registered teams and delivers high-detail, high-speed analysis within hours of the game having been played. Data analysis All data were captured in Microsoft Excel 2007 and subsequently converted into an SAS data set. For aim 1 the following analysis was done: The GLIMMIX procedure of the SAS Version 9.22 statistical software package was used for further statistical analysis (SAS, 2009). Means and standard deviations were used for numerical data. Individual tackle counts for each position, team and game were analysed using a generalised linear mixed model (GLIMM) with position and team as fixed effects, the natural logarithm of individual time played in minutes as offset, and position-by-team and game-by-team interaction terms as random effects. Regarding the fitted random effects, it seemed reasonable to allow for correlation between tackle counts for a specific individual across several games (modelled by the position-by-team random effect), and for correlation between tackle counts across players in a given team and game (modelled by the team-by-game random effect). Furthermore, the GLIMM was specified with Poisson error distribution and the natural logarithm as link function. Individual collision counts for each position, team and game were analysed in the same manner. In both cases – tackle counts and collision counts – the model fitted the data well and there was no evidence of residual over-dispersion. Based on the GLIMM, the mean rate of tackles and mean rate of collisions per 80 minutes (that is, normalised to a full-length rugby game) were estimated for each playing position, with 95% confidence intervals (CIs) of the mean rates. Similarly, in order to compare the mean rates of tackles and collisions between different playing positions, rate ratios (that is, the ratio of tackle and collision rates between playing positions) were estimated, with 95% CIs for the rate ratios. Aim 2 included the following statistical analysis: Means and standard deviations were used for numerical data. Individual tackle counts for each position, team and game were analysed using a generalised linear mixed model (GLIMM) with position and team as fixed effects, the natural logarithm of individual time played in minutes as offset, and position-by-team and game-by-team interaction terms as random effects. Regarding the fitted random effects, it seemed reasonable to allow for correlation between tackle counts for a specific individual across several games (modelled by the position-by-team random effect), and for correlation between tackle counts across players in a specific team and game (modelled by the team-by-game random effect). Furthermore, the GLIMM was specified with Poisson error distribution and the natural logarithm as link function. Team rates for passing and kicking were analysed in the same manner. In both cases, passing and kicking rates, the model fitted the data well and there was no evidence of residual over-dispersion. Based the GLIMM, the mean rate of passing and mean rate of kicking per 80 min were estimated for each team, with 95% confidence intervals (CIs) of the mean rates. Aim 3 consisted of each count variable (number of lineouts, scrums, rucks, mauls etc.) to be analysed using a generalised linear mixed model (GLIMM) with season (2011 versus 2015) as fixed effect, and both winning team and losing team as random effect. (The fitting of the variables winning team and losing team as random effects allowed for correlation between the counts in question for a given team across several games.) Furthermore, the GLIMM was specified with Poisson error distribution and the natural logarithm as link function; residual over-dispersion was allowed for in the model. Based on the GLIMM, the mean rates of lineouts, scrums, rucks, mauls etc. per game were estimated for the 2011 and 2015 seasons. Similarly, in order to compare the mean rates between the 2011 and 2015 seasons, ratios of lineout rates etc. between the 2015 and 2011 seasons were estimated, together with 95% CIs for the rate ratios. The above analyses were carried out separately for the data of the winning teams, for the data of the losing teams, and for the data of two teams involved in each game combined (that is, for the game). The analysis was carried out using SAS procedure GLIMMIX (SAS, 2013). Aim 4 used descriptive statistics for the count and percentage data calculated for the 2011 to 2015 seasons. Descriptive statistics were calculated per season for the winning teams, for the losing teams, and for the two teams involved in each game combined (that is, for the total count per game). Each count variable (number of lineouts, scrums, rucks, mauls etc.) was analysed using a generalised linear mixed model (GLIMM) with Season (2011 versus 2015) as fixed effect, and both winning team and losing team as random effect. (The fitting of the variables winning team and losing team as random effects allowed for correlation between the counts in question for a given team across several games.) Furthermore, the GLIMM was specified with Poisson error distribution and the natural logarithm as link function; residual over-dispersion was allowed for in the model. Based on the GLIMM, the mean rates of lineouts, scrums, rucks, mauls etc. per game were estimated for the 2011 and 2015 seasons. Similarly, in order to compare the mean rates between the 2011 and 2015 seasons, rate ratios, that is, ratios of lineout rates etc. between the 2015 and 2011 seasons were estimated, together with 95% CIs for the rate ratios. The above analyses were carried out separately for the data of the winning teams, for the data of the losing teams, and for the data of two teams involved in each game combined (that is, for the game). Percentage territory and percentage possession of the winning team in each game were analysed using a linear mixed model with Season as fixed effect, and both Winning Team and Losing Team as random effects. Based on the linear mixed model, the mean percentage territory (and possession) was estimated for each season, together with a 95% CI for the mean percentage. Similarly, in order to compare the mean percentage between the 2011 and 2015 seasons, mean differences, that is, differences of mean percentage territory and possession between the 2015 and 2011 seasons were estimated, together with 95% CIs for the mean differences. The analysis was carried out using SAS procedure MIXED (see SAS, 2013). Results The results from aim one underlined the importance of specific demands on the various playing positions regarding the tackles and collisions sustained by Super Rugby players. Clearly, loose forwards (6: = 16.65 tackles/80 min; 7: = 17.30 tackles/80 min; 8: = 14.68 tackles/80 min) had the highest tackling rates, followed by the locks (4: = 13.74 tackles/80 min; 5: = 14.07 tackles/80 min). Amongst the backs, the inside centre (12: = 12.89 tackles/80 min) was the player with the highest tackling rates, followed by the outside centre (13: = 9.96 tackles/80 min). The results showed that the open-side flanker (7) had the highest tackle rate of all playing positions (17.30 tackles/80 min). The open-side flank (7) was involved in the most collisions (50.91), followed by the blind-side flank (6), loosehead lock (4) and eighthman (8), with collision rates of 46.08, 44.81 and 43.03 respectively, per 80 minutes collision count per game. The results showed significant differences between positional groups for tackles, except for the front row players and the second row (1, 2, 3 vs 4, 5; p=0.0715 to p=0.6324). Within a positional group, namely the backline players, the tackling rate of the inside centre differed significantly from the tackling rate of the other backline players (9 vs 12, p=0.0029; 10 vs 12, p=0.0045; and 12 vs 13, p=0.0100). Aim two indicated that losing teams tend to pass the ball more (157.41) than winning teams (127.02). The results illustrated a significant difference between winning teams and losing teams regarding total passes, bad passes, and good passes (p=<0.05). Winning teams tend to kick the ball more (25.77) than losing teams (20.23). Results indicated a significant difference between winning teams and losing teams regarding total kicks, long kicks, short kicks, and kicking metres (p=<0.05). Winning teams kicked more long kicks (18.55) than losing teams (14.19). Winning teams also used the short kick (7.22) more effectively and more often than losing teams (6.04). Losing teams gain a mean total of 660.01m per game in comparison to winning teams who gain 901.4m per game. In the third aim it was discovered that, when the two competitions are compared, it is evident that only two variables can be distinguished. The mauls and tackles missed are the only two variables that show remarkable difference, with 3.23 mauls and 8.9 tackles missed per game more in Currie Cup competition than the Super Rugby. The results of this study underline the importance of measuring and analysing specific performance indicators on a regular basis as these performance indicators can increase or decrease as the level of competition change. The greatest increase occurred with rucking, as this variable increased from 139.63 in Currie Cup to 143.13 in Super Rugby. Super Rugby teams lose fewer lineouts, and have less missed tackles, while Currie Cup teams utilise mauls more as an offensive weapon. Aim 4 identified playing time, lineouts lost, scrums, scrums lost, tackles and penalties decreased from 2011 to 2015, while lineouts, mauls and the number of missed tackles increased. The results of this study underline the importance of measuring and analysing specific performance indicators on a regular basis as these performance indicators can increase or decrease in a short time frame. From 2011 to 2015 winning teams consistently lost fewer lineouts than losing teams, even with an overall increase in the number of lineouts per game. The study indicates a slight decrease in the number of tackles, but still supports the fact that winning teams have higher tackle rates than losing teams. Conclusions The results of the study show that there are significant differences between individual playing positions within the same positional group with regard to tackling and collision rates sustained during match play. The study confirms that losing teams pass more than winning teams and that winning teams kick more than losing teams during match play. The study also discovered a greater distance gained through kicks by winning teams. The higher or lower numbers of performance indicators performed by teams over competitions emphasise the different physiological demands for teams. The study concluded that playing time, lineouts lost, scrums, scrums lost, tackles and penalties decreased from 2011 to 2015, while lineouts, mauls and the number of missed tackles increased. The findings may be important for future research as they indicate a constant shift in statistics and outcomes of teams over seasons within a particular competition.
Open Access
Randomised observer-blind controlled clinical trial of the effect of static stretching versus static stretching with self-myofascial release on hamstring flexibility
(University of the Free State, 2021-11) Vos, Madeline; Coetzee, F. F.; Schall, R.; Sinclair, C.
Introduction: Flexibility is an important component in everyday life, especially for athletes. Flexibility is related to improved quality of life, better performance and reduced risk of injuries, and better functionality are associated with improved ROM. Static stretching (SS) is one of the most frequently used mechanisms with self-myofascial release (SMR) being a newly implemented mechanism. Both these interventions are seen as an effective way of flexibility improvements, each with their own set of downfalls. Objectives: The purpose of this study was to compare the effects of SS alone versus SMR + SS on hamstring flexibility. To assess the difference, SS alone and SMR + SS were evaluated over a 4-week period.Methods: This was a randomized control study. Fifty-six (56) male high-performance athletes from the University of the Free State were recruited and were randomly assigned into the two intervention groups, 28 participants in group one who represented SS and 28 participants in group two who represented SMR + SS. Data collection took place over a period of one month, with three data collections taking place. Outcome measures for this study were hamstring flexibility, which was assessed with an active knee extension (AKE) test and a straight-leg raise test (SLR). The two groups received three sets of one-minute stretching and/or foam rolling with 30-second rests for at least 3 days out of a 7-day week. Results: Both groups showed improvement in both AKE and SLR when comparing Week 0 to Week 4. However, the improvement seen when comparing SS alone versus SMR + SS was the same; the only exception was the pace at which improvement was seen at Week 2 and Week 4. Improvement at Week 2 was at a faster pace for both interventions than that of Week 4. When comparing the sport codes with one another, all showed improvements with both interventions; one intervention was not superior to another. Conclusion: The results of this study show that the addition of SMR before SS does not show a significant improvement in hamstring flexibility than that of SS alone. Actually, SMR + SS improved hamstring flexibility quicker than SS only when analysing Week 2 versus Week 4.
Open Access
The relationship between core stability and athletic performance among female university athletes
(University of the Free State, 2020-07) De Bruin, Marizanne; Coetzee, F. F.; Opperman, M.
Introduction: Literature on the effect of core stability on athletic performance in different sport codes is limited. Questions remain as to whether core stability should be considered as a component in itself or as different components, as well as the assessment thereof, and if a relationship exists with athletic performance in different sport codes. Objective: The primary objectives of this research study were to establish an anthropometric profile of female university hockey, netball, running, soccer and tennis athletes and to determine if a relationship exists between core stability and athletic performance. Population: Data were collected from 83 female athletes from the University of the Free State participating in hockey, netball, middle- and long-distance running (400 m, 800 m, 1 500 m and 3 000 m), soccer and tennis in the 2018/2019 sport season. Methods: This was a quantitative, cross-sectional study. Core stability was assessed using the isometric back extension (IBE) test, lateral flexion (LF) test and the abdominal flexion (AF) test to assess core strength (in Newton) and core endurance (in seconds), respectively, and the core stability grading system using a pressure biofeedback unit to assess core motor control. Athletic performance was assessed using the forty-metre sprint, T-test, vertical jump and the medicine ball chest throw. All athletes executed three trials of each test in a randomised order and the best value of each test was used for analysis. Correlations between each of the seven core stability tests and the four athletic performance tests were determined, overall, and separately by sport. Furthermore, the effect of core stability on athletic performance assessments was assessed using ANCOVA, fitting the factor of sport, and the covariates age, height, weight, body fat percentage and BMI of the athletes, as well as various interaction terms. Results: This study depicted the anthropometric profiles of female university athletes and found that runners have the greatest height and netball the greatest body weight, body fat percentage and BMI compared to the other sport codes. Overall, there is a statistically significant difference with respect to age, body weight, body fat percentage and BMI, but height difference is not statistically significant between sports. The highest mean value for core strength was observed in hockey, whilst tennis showed the lowest, as measured by the IBE, LF and AF characteristics. The highest mean value of core endurance was observed in runners, and the lowest in tennis, as measured by the same characteristics as core strength, only for time. The highest value of core motor control was noted in runners (grade 5) and the lowest in netball (grade 1). The highest average percentage of female university athletes obtained a grade 3. Overall, there is a statistically significant difference in sports with respect to all three characteristics of core strength and core endurance as well as the core motor control component. When considering the correlations between core stability and athletic performance for all sport codes, all correlations of core strength, core endurance and core motor control with athletic performance were weak (r<0.2) and moderately weak (r=0.2-0.5). However, when the different core tests were considered separately, the correlations for the LF characteristic of core strength was moderately strong (r=0.5-0.8) for the medicine ball chest throw and strong (r=0.8-1.0) for the vertical jump. When considered for the different sport codes separately, moderately strong correlations (r=0.2-0.5) were found in all sport codes only- for core strength with certain athletic performance tests. Overall, there is a statistically significant difference between sports with respect to all four athletic performance characteristics. Conclusion: Correlations were found between core stability and athletic performance, even though some correlations were weak and moderately weak. It can also be concluded that different sport codes require different components of core stability, and have different sets of skills based on the position played and event. Therefore, core stability can be considered as an important modality to improve athletic performance, however, it should not be the main focus in exercise training programmes.
Open Access
Stretching tecniques on hamstring flexibility in female adolescents
(University of the Free State, 2010) Janse van Rensburg, Lizl; Coetzee, F. F.
This study compared the eflicacy of 4 ditlerent hamstring-stretching techniques. Flexibility can be achieved by a variety of stretching techniques, yet little research has been performed on the most effective method. The four most basic stretches includes: Static stretching where the limb is held stationary at and endpoint for a certain time period; Dynamic stretching, an active stretch where the limb is slowly moved from the neutral position to the endpoint; PNF hold-relax- and PNF contract-relax stretching which is also referred to as active stretches because of the concentric and isometric contractions throughout the stretch (Prentice) 2010: Ill). This study’s aim was to determine which type of stretching technique IS most effective in improving hamstring length. One hundred female subjects between the ages of 13 and 17 years were enrolled in the study. The 90°/90° hamstring length measure was used for all measurements to measure knee extension angle. Alii 00 subjects were included in a randomized controlled trial of 5 different groups comparing different hamstring-stretching techniques. Outcorne measure (hamstring length) was recorded on all subjects initially, at 3 weeks and at 6 weeks. After 3 weeks of stretching, there was a statistically significant improvement in hamstring length (p<0.0001) using all stretches when compared to the control group. From weeks 3 through 6, hamstring length for all groups again showed statistically significant improvement when compared to the control group. No significant difference was found comparing the intervention groups after 3 weeks or after 6 weeks of stretching. After both 3 weeks and 6 weeks of stretching the straight-leg-raise (static stretching) group had the greatest improvement in hamstring length, although the difference was not statistically significant.
Open Access
Time motion analysis of elite under 19 female netball players using GPS technology
(University of the Free State, 2018-01) Shaw, Michael-Louis; Coetzee, F. F.; Kraak, W. J.
Introduction: Netball is a high intensity team sport characterized by short bursts of movements coupled with less intense recovery periods. Understanding the physiological demands of the sport is essential for constructing sport-specific conditioning programmes. Objectives: The purpose of this study was to profile the physical characteristics and physiological demands on elite u/19 female netball players during netball matches, in an attempt to assess the differences in those characteristics and demands for the various playing positions in netball. Methods: Global Positioning System (GPS) data on a total of forty-four (44) elite junior netball players (u/19A) were collected and a total of sixteen netball matches were analysed for the study. Therefore, a total of hundred and forty (140) GPS data sets (player games) were analysed (equivalent to 560 (140 x 4) player quarters out of a total of 731 player quarters that were recorded). Minimax X4 Catapult GPS units as well as a Polar HR monitors and chest straps were used to determine the physiological demands of netball players. The following variables were recorded: Distances covered, player load, the maximal velocity during the match; and heart rate (HR) response. The various HR and GPS data variables were analysed using a linear mixed model with Playing Position as fixed effect, and the random effects Game, Team, Game x, Team interaction term, and Player. Fitting these random effects allowed for correlation between the observations in question due to multiple observations from the same game, team, and player. Based on this linear mixed model, the mean values of the variable for each playing position were estimated, together with their standard errors. Furthermore, the pairwise mean differences between playing positions were estimated, together with 95% confidence intervals (CIs) for the mean differences and P-values associated with the null-hypothesis of zero mean difference between the pair of playing positions in question. Results: The body weight, body fat percentage and height of u/19 female netball players vary according to playing position. The Goal Shooter (GS) (186 b/min) recorded significantly (p<0.05) lower mean maximum HR than all the other positions. The mean HR of the GS (162 b/min) and the Goal Defence (GD) (170 b/min) was significantly lower than the Centre (C),Goal Attack (GA) (180 b/min) and WA (178 b/min). The C presented with the highest mean maximum velocity (5.23m.s-1) whereas the GS recorded the lowest mean maximal velocity of 4.05m.s-1. The C also covered significantly (p<0.05) more distance and presented with significantly (p<0.05) higher Player load (PL) than all the other positions, whereas the GS and the Goal Keeper (GK) presented with significantly (p<0.05) lower distance covered and PL. However, the GS and GK had a significantly higher PL per meter. The C covered 44% of its total distance between 0.2 – 3.6 m.s-1 whereas the GK and GS covered 77% of their total distance between 0.2 – 3.6 m.s-1. The GS and GK covered significantly (p<0.005) more distance in velocity band 1 than the C, GA, GD and Wing Attack (WA) and the Wing Defence (WD) travelled significantly (p=0.007) further than the C in velocity band 1. However, the GK and GS covered significantly (p<0.05) less distance than all the other positions in velocity band 2. The C travelled significantly (p<0.05) further than all the other positions in velocity band 3 and 4 and the GK travelled significantly (p<0.05) less in velocity band 4 than the other positions. Conclusions: The study revealed the differences in physical profile and physical demands of u/19 female netball players between the seven playing positions. These findings emphasize the difference in physical demand between the different positions as well as the different type of load placed on the different positions. Coaches and conditioning coaches must implement the findings of the study to develop sport-specific, and more importantly, position-specific conditioning programs.
Open Access
Time motion analysis of international rugby
(University of the Free State, 2010-11) Schoeman, Riaan; Coetzee, F. F.
English: This study examined the relationship between the Distance covered, High Intensity Distance covered, and the Percentage Work Rate at High Intensity and how it correlates to the score and result of each match. This paper attempted to address deficiencies in the game of rugby and provide a meaningful body of data to determine winning and losing components that jeopardize matches at senior international level. Eighteen matches (Test and Super 14) were used to gather data through the Pro zone time motion analysis program. Calculating the frequency, mean duration and total time spent in activities is fundamental in time motion analysis (McLean, 1992:285-96). The extent of these changes has, however, never been quantified. What is even more important is that their impact on playing the game has not been evaluated. Teams losing the away games, even though they won all components, can be due to home team support, playing conditions, the magnitude of the game, law variations, competition structure and the team structure played. Time motion analysis is an effective method of quantifying the demands of rugby and provides a conceptual framework for the specific physical preparation of players. The results of this study showed no significant difference (p < 0.05) between the variables (distance covered, high intensity distance covered and percentage work rate at high intensity) in the winning and losing team. The correlation between all the variables (distance covered, r = 0.67 , high intensity distance covered, r = 0.62 and percentage work rate at high intensity, r = 0.54) and winning have practical implications. The information obtained from these analyses allows coaches to structure training programmes specific to the requirements of the game, and facilitates more effective training and improved performance.

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