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M. Tech. Clinical Technology. / Soccer is the most popular sport in the world. Elite level soccer players cover about 10 km during a 90-minute game. Although running is the predominant activity in soccer, explosive movements such as sprinting, jumping and kicking are important for successful performance. The aims of this study were to determine the technical skill ability, aerobic and anaerobic fitness of the players; determine whether a relationship exists between the technical skill ability and aerobic and anaerobic fitness; and determine whether a relationship exists between team ranking order and these variables.

Objectives: The objectives of this research were to gain a detailed understanding of approaches, facilitators and constraints to creating an optimal motivational climate within elite youth soccer programs in North America by examining the insights of expert coaches in this field. Design and Method: By using a case study design, six coaches were interviewed using a semi-structured interview format which explored perceptions about and key aspects of the optimal motivational climate and identified specific strategies while reporting challenges to the process of creating the desired climate. Inductive thematic analysis was used to identify major recurring themes that occurred amongst the participant responses and then discussed from the perspective of existing motivational frameworks. Results: Five dimensions of the desired motivational climate emerged from the theming: developing the autonomous player, connectedness, the opportunity for player advancement, failure as part of the process, and context may have an influence on the climate. Five specific strategies used in creating the desired motivational climate were identified: communication within the group, player advancement, modeling, selection/de-selection, and communication with parents. Five challenges to creating the desired climate surfaced: contact time with the athletes, parents/parental involvement, consistency within club staff, player movement within the club, and mentality of the player coming into the club. Conclusion: The findings of this study show that coaches tried to create a motivational climate that was autonomy supportive and task involving. Some aspects of the motivational climate were consistent however with facets of an ego-involving climate. It was also found that parents were believed to have an impact on the motivational environment surrounding the players. The research highlights the complexity of motivational climate in elite youth soccer programs and demonstrates the need for further exploration into education for coaches as well as observation and intervention-based research. / Graduate

Title: The comparison of the sport training in soccer in selected soccer teams in the U8 category. Objectives: To the creation of the concept of sport training in the category U8 in the team Dukla Prague compare this sport training with other Prague teams and held various important differences or comfornity. Methods: In creating the concept of sports training soccer U8 used the methos od purposeful collecting qualitative data. Futhermore, also use their own and expert experience dealing with this issue. Results: The result of this thesis is to identify individual differences in sports training of young soccer players between teams of Prague. Key words: Football, sports training children, preschool age, the trainig procces, the gaming principle

The purpose of this study was to develop a physiological profile of elite Australian Youth soccer players. Over three years, 150 players from the U'17, U'20 and U'23 national squads were tested for six measurements - height, weight, sum of eight skinfolds, vertical jump, maximum oxygen consumption and speed over twenty metres. Comparisons were made between those selected in the final team (classified as Successful) and those who failed to be selected (classified as Unsuccessful) to determine any significant differences between the two groups A physical and physiological profile was obtained for each player - expressed as a single value in both numerical and graphical formats. Players were ranked based on this score to determine significant differences between successful and unsuccessful players. Several significant differences (p<0.05) were found between Successful and Unsuccessful groups for a number of the variables primarily in the performance area rather than in the anthropometry parameters. For all squads, significant differences (P<0.05) were found between those who made the squad and those who did not when ranked based on their physical and physiological score. This study highlights the importance of the application of scientific testing to soccer Furthermore, it provides a system by which players' results can be analysed and ranked, and expressed in a format that provides the coach with immediate feedback as to an individual's specific strengths and weaknesses as a basis for training and team selection.

Background: Football (Soccer) is arguably the most popular sport in the international sporting arena. A survey conducted by FIFA (Fédération International de Football Association) (FCPA, 2000) indicated that there are 240 million people who regularly play soccer around the world. Internationally, there are 300 000 clubs with approximately 1.5 million teams. In South Africa, there were 1.8 million registered soccer players in 2002/2003 (Alegi, 2004). Although youth players are predominantly amateurs and have no financial value for their clubs or schools, their continued health and safety are still of vital importance. There are some clubs which contract development players at 19 years of age in preparation for playing in their senior sides and these young players should be well looked after, to ensure a long career playing soccer. Being able to predict injuries and prevent them would be of great value to the soccer playing community. Aims: The main aim of this research was to create a statistical predictive equation combining biomechanics, balance and proprioception, plyometric strength ratios of ND/Bil (Non dominant leg plyometrics/ Bilateral plyometrics), D/Bil (Dominant leg plyometrics/ Bilateral plyometrics) and ND+D/Bil (Non dominant leg + dominant leg plyometrics/ Bilateral plyometrics) and previous injuries to determine a youth soccer player's risk of the occurrence of lower extremity injuries. In the process of reaching this aim it was necessary to record an epidemiological profile of youth soccer injuries over a two season period. It was also necessary to record a physical profile of, and draw comparisons between, school and club youth soccer players. Following the creation of the prediction model a preventative training programme was created for youth soccer players, addressing physical shortcomings identified with the model. Design: A prospective cohort study Subjects: Schoolboy players from two schools in the North West Province, as well as club players from three age groups were used for this study. Players from the U/16 and U/18 teams in the two schools were tested prior to the 2007 season. Players from the U/17, U/18 and U/19 club development teams were tested prior to the 2008 season. The combined total number of players in the teams amounted to 110 players. Method: The test battery consisted of a biomechanical evaluation, proprioceptive and plyometric testing and an injury history questionnaire. The Biomechanical evaluation was done according to the protocol compiled by Hattingh (2003). This evaluation was divided into five regions with a dysfunction score being given for each region. A single limb stance test was used to test proprioception. A Sergeant jump test was utilised using the wall mark method to test plyometric jumping height. A previous injury questionnaire was also completed on all players prior to testing. Test subjects from the schools were tested with the test battery prior to commencement of the 2007 season. The testing on the club teams was undertaken prior to the 2008 season. Injuries were recorded on the prescribed injury recording form by qualified Physiotherapists at weekly sports injury clinics at each of the involved schools and clubs. The coaching staff monitored exposure to training activities and match play on the prescribed recording forms. These training and match exposure hours were used, along with the recorded injuries for creating an epidemiological profile. Injuries were expressed as the amount of injuries per 1000 play hours. Logistical regression was done by using the test battery variables as independent variables and the variable injured/not injured as dependent variable (Statsoft, 2003). This analysis created prediction functions, determining which variables predict group membership of injured and non injured players. Results: There were 110 youth players involved in the research study from seven teams and four different age groups. There were two groups of U/16 players, an U/17 group, three U/18 groups and an U/19 group. The players were involved in a total of 7974 hours of exposure to training and match play during the seasons they were monitored. The average age of the players was 16.6 years. The majority of players were right limb dominant (83.6%) and 65.7% of players failed a single limb stance test. The mean jump height for both legs combined was 33.77cm, with mean heights of 22.60cm for dominant leg jump and 22.66cm for the non dominant leg. In the biomechanical evaluation of the lower leg and foot area, the average youth player presented with adaptation of toes, normal or flat medial foot arches, a normal or pronated rear foot in standing and lying and a normal or hypomobile mid-foot joint. Between 42.7% and 51.8% of players also presenting with decreased Achilles tendon suppleness and callusing of the transverse foot arch. The youth profile for the knee area indicated that the players presented with excessive tightness of the quadriceps muscles, normal patella tilt and squint, normal knee height, a normal Q-angle, a normal VMO: VL ratio and no previous injuries. This profile indicated very little dysfunction amongst youth players for the knee area. For the hip area, the youth profile was described as follows: There was shortening of hip external rotators, decreased Gluteal muscles length, normal hip internal rotation and no previous history of injury. Between 38.2% and 62.7% of players also exhibit shortened muscle length of the adductor and Iliopsoas muscles and decreased length of the ITB (Iliotibial Band). In the Lumbo-pelvic area there was an excessive anterior tilt of the pelvis with normal lumbar extension, side flexion, rotation and lumbar saggital view without presence of scoliosis. Between 58.18% and 65.45% of players presented with an abnormal coronal view and decreased lumbar flexion. Between 41.81% and 44.54% of players also presented with leg length, ASIS, PSIS, Cleft, Rami and sacral rhythm asymmetry. The similarity of the results for these tests in all players contributed to a new variable called 'SIJ dysfunction'. This was compiled from the average of the scores for Leg length, ASIS, PSIS, Cleft, Rami and Sacral rhythm, which was also considered for inclusion in the prediction model. The neurodynamic results of youth players indicated that approximately between 44.54% and 50.91% of players presented with decreased Straight leg raise and prone knee bend tests. The total combined dysfunction scores for the left and right sides were 17.091 and 17.909 respectively, indicating that there were higher levels of dysfunction on the right side than the left. This increased unilateral dysfunction could probably be attributed to limb dominance and increased use of the one leg for kicking and passing during the game. In the epidemiological study on youth players, there were a total of 49 training injuries and 52 match injuries. The total injury rate for youth players was 12.27 injuries/1000 hours, with a total match injury rate of 37.12 injuries/1000 match hours. The combined training injury rate was 7.17 injuries/1000 training hours. 87.13% of injuries were of the lower limb area and the individual areas with the highest percentage of injuries were the Ankle (25.74%), Knee (19.80%), Thigh (15.84%) and Lower leg (14.85%).The totals for youth players indicated that sprains (30.69% of total), strains (27.72% of total) and contusions (27.72% of total) were the most common causative mechanism of injuries. The severity of injuries show 'zero day' (no time off play) injuries to be the most common type (35.64%), followed by 'slight' (1 to 3 days off play) (33.66%) and 'minor' (4 to 7 days off play) (14.85%). School players had higher injury rates than club players but the severity of injuries to club players was higher, with longer absences from play. Non-contact injuries accounted for 52.47% of the total with 46.53% being contact injuries. School players had lower levels of non-contact injuries than club players, which correlated well with lower dysfunction scores recorded for school players during the biomechanical evaluations. This demonstrated that there was a definite relationship between levels of biomechanical dysfunction and the percentage of non-contact injuries in youth players, which formed the premise of the creation of a prediction model for non-contact youth soccer injuries. The next step in the creation of a prediction model was to identify the variables that discriminated maximally between injured and non-injured players. This was done using stepwise logistic regression analysis. After the analysis, ten variables with the largest odds ratios were selected for inclusion in the prediction model to predict non-contact injuries in youth soccer players. The prediction model created from the stepwise analysis presented as follows: P (injury)= exp(-8.2483 -1.2993a + 1.8418b + 0.2485c + 4.2850d + 1.3845e + 1.3004f-1.1566g + 1.8273h-0.9460i-0.5193j) l + exp(-8.2483-1.2993a + 1.8418b+ 0.2485c + 4.2850d + 1.3845e + 1.3004f-1.1566g + 1.8273h-0.94601-0.5193J) a = Toe dysfunction b = Previous ankle injury c = Ankle dysfunction d = SIJ dysfunction e = Lumbar Extension f = Straight Leg Raise g = Psoas length h = Patella squint i = Gluteal muscle length j = Lumbar dysfunction P = probability of non contact injury exp(x) = e x , with e the constant 2.7183 In the ankle area, the toe positional test, previous ankle injury history and combined ankle dysfunction score were included in the prediction model. In the knee area, the patella squint test was included in the model. In the hip area, the Psoas component of the Thomas test was included, along with the Gluteal muscle length test. In the Lumbo-pelvic area, the SIJ dysfunction (average of Leg length, ASIS, PSIS, Rami, Cleft and Sacral rhythm tests), lumbar extension test and lumbar dysfunction scores were included in the prediction model. In the neurodynamic area, the Straight leg raise test was included in the prediction model. The prediction model therefore contained tests from all five the bio mechanical areas of the body. Overall, this model correctly predicted 86.91% of players as either injured or not-injured. The I value (effect size index for improvement over chance) of the prediction model (1=0.67), along with the sensitivity (65.52%), specificity (94.87%), overall correct percentage of prediction (86.91%) and Hosmer and Lemeshow interferential goodness-to-fit value (X 2(8) = 0.7204), all demonstrated this prediction model to be a valid and accurate prediction tool for non-contact youth soccer injuries A second prediction model, for the prediction of hip and groin injuries amongst youth players, was also created. The prediction model created from the stepwise analysis for groin injuries presents as follows: P (Groin injury)^ exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) l + exp(-116.2 + 33.5383d+14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) d = SIJ dysfunction k = Previous knee injury m = Previous hip injury e = Lumbar extension f = Straight leg raise n = Limb dominance p = ND/Bil plyometric ratio P = probability of groin injury exp(x) = ex, with e the constant 2.7183 The prediction model for hip and groin injuries included the variables of SIJ dysfunction, previous knee injury, previous hip injury, lumbar extension, straight leg raise, limb dominance and the ratio of non-dominant leg to bilateral legs plyometric height. When all the validifying tests were examined, the I-value (0.64868), sensitivity (66.67%), specificity (98.01%), false negatives (1.98%), false positives (33.33%), Hosmer and Lemeshow goodness-to-fit value (X2(8) = 0.77) and the overall percentage of correct prediction (96.26%) all reflected that this model was an accurate prediction tool for hip and groin injuries amongst youth soccer players. Conclusion: This study showed that it was possible to create a prediction model for non-contact youth soccer injuries based on a pre-season biomechanical, plyometric and proprioceptive evaluation along with a previous injury history questionnaire. This model appears as follows: P (injury)= exp(-8.2483 -1.2993a + 1.8418b + 0.2485c + 4.2850d + 1.3845e + 1.3004f - 1.1566g + 1.8273h - 0.9460i - 0.5193J) l + exp(-8.2483-1.2993a+ 1.8418b + 0.2485c + 4.2850d + 1.3845e + 1.3004f-1.1566g+1.8273h-0.94601-0.5193J) a = Toe dysfunction b=Previous ankle injury c = Ankle dysfunction d= SIJ dysfunction e=Lumbar Extension f = Straight Leg Raise g = Psoas length h = Patella squint i = Gluteal muscle length j = Lumbar dysfunction P = probability of non contact injury exp(x) = ex, with e the constant 2.7183 It was also possible to create a prediction model for non contact hip and groin injuries, which appears as follows: P (Groin injury)= exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) l + exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) d = SIJ dysfunction k = Previous knee injury m = Previous hip injury e = Lumbar extension f = Straight leg raise n = Limb dominance p = ND/Bil plyo metric ratio P = probability of groin injury exp(x) = ex, with e the constant 2.7183 It was also possible to create a prediction model for non contact hip and groin injuries, which appears as follows: P (Groin injury)= exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) l + exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) d = SIJ dysfunction k = Previous knee injury m = Previous hip injury e = Lumbar extension f = Straight leg raise n = Limb dominance p = ND/Bil plyo metric ratio P = probability of groin injury exp(x) = ex, with e the constant 2.7183 Using the hip and groin prediction model, combined with the injury prediction model, injuries in youth soccer players can be predicted. The data for each player should first be substituted into the injury prediction model, to determine the chance of getting injured during the season. The data should then be substituted into the hip and groin injury prediction model, determining the chance of hip and groin injuries during the season. The results from the groin injury prediction model could then be used to exclude groin injuries amongst players. A negative result for the hip and groin injury, which showed a false negative percentage of 1.98%, could be used to determine that an injury that was predicted using the overall injury prediction model, would not be a hip and groin injury. A positive result in the groin injury test could, however, not exclude injuries to other body areas that were predicted by the overall injury prediction model, so the groin injury prediction model could only be used to exclude hip and groin injuries. / Thesis (Ph.D. (Education)--North-West University, Potchefstroom Campus, 2009.

Background: Football (Soccer) is arguably the most popular sport in the international sporting arena. A survey conducted by FIFA (Fédération International de Football Association) (FCPA, 2000) indicated that there are 240 million people who regularly play soccer around the world. Internationally, there are 300 000 clubs with approximately 1.5 million teams. In South Africa, there were 1.8 million registered soccer players in 2002/2003 (Alegi, 2004). Although youth players are predominantly amateurs and have no financial value for their clubs or schools, their continued health and safety are still of vital importance. There are some clubs which contract development players at 19 years of age in preparation for playing in their senior sides and these young players should be well looked after, to ensure a long career playing soccer. Being able to predict injuries and prevent them would be of great value to the soccer playing community. Aims: The main aim of this research was to create a statistical predictive equation combining biomechanics, balance and proprioception, plyometric strength ratios of ND/Bil (Non dominant leg plyometrics/ Bilateral plyometrics), D/Bil (Dominant leg plyometrics/ Bilateral plyometrics) and ND+D/Bil (Non dominant leg + dominant leg plyometrics/ Bilateral plyometrics) and previous injuries to determine a youth soccer player's risk of the occurrence of lower extremity injuries. In the process of reaching this aim it was necessary to record an epidemiological profile of youth soccer injuries over a two season period. It was also necessary to record a physical profile of, and draw comparisons between, school and club youth soccer players. Following the creation of the prediction model a preventative training programme was created for youth soccer players, addressing physical shortcomings identified with the model. Design: A prospective cohort study Subjects: Schoolboy players from two schools in the North West Province, as well as club players from three age groups were used for this study. Players from the U/16 and U/18 teams in the two schools were tested prior to the 2007 season. Players from the U/17, U/18 and U/19 club development teams were tested prior to the 2008 season. The combined total number of players in the teams amounted to 110 players. Method: The test battery consisted of a biomechanical evaluation, proprioceptive and plyometric testing and an injury history questionnaire. The Biomechanical evaluation was done according to the protocol compiled by Hattingh (2003). This evaluation was divided into five regions with a dysfunction score being given for each region. A single limb stance test was used to test proprioception. A Sergeant jump test was utilised using the wall mark method to test plyometric jumping height. A previous injury questionnaire was also completed on all players prior to testing. Test subjects from the schools were tested with the test battery prior to commencement of the 2007 season. The testing on the club teams was undertaken prior to the 2008 season. Injuries were recorded on the prescribed injury recording form by qualified Physiotherapists at weekly sports injury clinics at each of the involved schools and clubs. The coaching staff monitored exposure to training activities and match play on the prescribed recording forms. These training and match exposure hours were used, along with the recorded injuries for creating an epidemiological profile. Injuries were expressed as the amount of injuries per 1000 play hours. Logistical regression was done by using the test battery variables as independent variables and the variable injured/not injured as dependent variable (Statsoft, 2003). This analysis created prediction functions, determining which variables predict group membership of injured and non injured players. Results: There were 110 youth players involved in the research study from seven teams and four different age groups. There were two groups of U/16 players, an U/17 group, three U/18 groups and an U/19 group. The players were involved in a total of 7974 hours of exposure to training and match play during the seasons they were monitored. The average age of the players was 16.6 years. The majority of players were right limb dominant (83.6%) and 65.7% of players failed a single limb stance test. The mean jump height for both legs combined was 33.77cm, with mean heights of 22.60cm for dominant leg jump and 22.66cm for the non dominant leg. In the biomechanical evaluation of the lower leg and foot area, the average youth player presented with adaptation of toes, normal or flat medial foot arches, a normal or pronated rear foot in standing and lying and a normal or hypomobile mid-foot joint. Between 42.7% and 51.8% of players also presenting with decreased Achilles tendon suppleness and callusing of the transverse foot arch. The youth profile for the knee area indicated that the players presented with excessive tightness of the quadriceps muscles, normal patella tilt and squint, normal knee height, a normal Q-angle, a normal VMO: VL ratio and no previous injuries. This profile indicated very little dysfunction amongst youth players for the knee area. For the hip area, the youth profile was described as follows: There was shortening of hip external rotators, decreased Gluteal muscles length, normal hip internal rotation and no previous history of injury. Between 38.2% and 62.7% of players also exhibit shortened muscle length of the adductor and Iliopsoas muscles and decreased length of the ITB (Iliotibial Band). In the Lumbo-pelvic area there was an excessive anterior tilt of the pelvis with normal lumbar extension, side flexion, rotation and lumbar saggital view without presence of scoliosis. Between 58.18% and 65.45% of players presented with an abnormal coronal view and decreased lumbar flexion. Between 41.81% and 44.54% of players also presented with leg length, ASIS, PSIS, Cleft, Rami and sacral rhythm asymmetry. The similarity of the results for these tests in all players contributed to a new variable called 'SIJ dysfunction'. This was compiled from the average of the scores for Leg length, ASIS, PSIS, Cleft, Rami and Sacral rhythm, which was also considered for inclusion in the prediction model. The neurodynamic results of youth players indicated that approximately between 44.54% and 50.91% of players presented with decreased Straight leg raise and prone knee bend tests. The total combined dysfunction scores for the left and right sides were 17.091 and 17.909 respectively, indicating that there were higher levels of dysfunction on the right side than the left. This increased unilateral dysfunction could probably be attributed to limb dominance and increased use of the one leg for kicking and passing during the game. In the epidemiological study on youth players, there were a total of 49 training injuries and 52 match injuries. The total injury rate for youth players was 12.27 injuries/1000 hours, with a total match injury rate of 37.12 injuries/1000 match hours. The combined training injury rate was 7.17 injuries/1000 training hours. 87.13% of injuries were of the lower limb area and the individual areas with the highest percentage of injuries were the Ankle (25.74%), Knee (19.80%), Thigh (15.84%) and Lower leg (14.85%).The totals for youth players indicated that sprains (30.69% of total), strains (27.72% of total) and contusions (27.72% of total) were the most common causative mechanism of injuries. The severity of injuries show 'zero day' (no time off play) injuries to be the most common type (35.64%), followed by 'slight' (1 to 3 days off play) (33.66%) and 'minor' (4 to 7 days off play) (14.85%). School players had higher injury rates than club players but the severity of injuries to club players was higher, with longer absences from play. Non-contact injuries accounted for 52.47% of the total with 46.53% being contact injuries. School players had lower levels of non-contact injuries than club players, which correlated well with lower dysfunction scores recorded for school players during the biomechanical evaluations. This demonstrated that there was a definite relationship between levels of biomechanical dysfunction and the percentage of non-contact injuries in youth players, which formed the premise of the creation of a prediction model for non-contact youth soccer injuries. The next step in the creation of a prediction model was to identify the variables that discriminated maximally between injured and non-injured players. This was done using stepwise logistic regression analysis. After the analysis, ten variables with the largest odds ratios were selected for inclusion in the prediction model to predict non-contact injuries in youth soccer players. The prediction model created from the stepwise analysis presented as follows: P (injury)= exp(-8.2483 -1.2993a + 1.8418b + 0.2485c + 4.2850d + 1.3845e + 1.3004f-1.1566g + 1.8273h-0.9460i-0.5193j) l + exp(-8.2483-1.2993a + 1.8418b+ 0.2485c + 4.2850d + 1.3845e + 1.3004f-1.1566g + 1.8273h-0.94601-0.5193J) a = Toe dysfunction b = Previous ankle injury c = Ankle dysfunction d = SIJ dysfunction e = Lumbar Extension f = Straight Leg Raise g = Psoas length h = Patella squint i = Gluteal muscle length j = Lumbar dysfunction P = probability of non contact injury exp(x) = e x , with e the constant 2.7183 In the ankle area, the toe positional test, previous ankle injury history and combined ankle dysfunction score were included in the prediction model. In the knee area, the patella squint test was included in the model. In the hip area, the Psoas component of the Thomas test was included, along with the Gluteal muscle length test. In the Lumbo-pelvic area, the SIJ dysfunction (average of Leg length, ASIS, PSIS, Rami, Cleft and Sacral rhythm tests), lumbar extension test and lumbar dysfunction scores were included in the prediction model. In the neurodynamic area, the Straight leg raise test was included in the prediction model. The prediction model therefore contained tests from all five the bio mechanical areas of the body. Overall, this model correctly predicted 86.91% of players as either injured or not-injured. The I value (effect size index for improvement over chance) of the prediction model (1=0.67), along with the sensitivity (65.52%), specificity (94.87%), overall correct percentage of prediction (86.91%) and Hosmer and Lemeshow interferential goodness-to-fit value (X 2(8) = 0.7204), all demonstrated this prediction model to be a valid and accurate prediction tool for non-contact youth soccer injuries A second prediction model, for the prediction of hip and groin injuries amongst youth players, was also created. The prediction model created from the stepwise analysis for groin injuries presents as follows: P (Groin injury)^ exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) l + exp(-116.2 + 33.5383d+14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) d = SIJ dysfunction k = Previous knee injury m = Previous hip injury e = Lumbar extension f = Straight leg raise n = Limb dominance p = ND/Bil plyometric ratio P = probability of groin injury exp(x) = ex, with e the constant 2.7183 The prediction model for hip and groin injuries included the variables of SIJ dysfunction, previous knee injury, previous hip injury, lumbar extension, straight leg raise, limb dominance and the ratio of non-dominant leg to bilateral legs plyometric height. When all the validifying tests were examined, the I-value (0.64868), sensitivity (66.67%), specificity (98.01%), false negatives (1.98%), false positives (33.33%), Hosmer and Lemeshow goodness-to-fit value (X2(8) = 0.77) and the overall percentage of correct prediction (96.26%) all reflected that this model was an accurate prediction tool for hip and groin injuries amongst youth soccer players. Conclusion: This study showed that it was possible to create a prediction model for non-contact youth soccer injuries based on a pre-season biomechanical, plyometric and proprioceptive evaluation along with a previous injury history questionnaire. This model appears as follows: P (injury)= exp(-8.2483 -1.2993a + 1.8418b + 0.2485c + 4.2850d + 1.3845e + 1.3004f - 1.1566g + 1.8273h - 0.9460i - 0.5193J) l + exp(-8.2483-1.2993a+ 1.8418b + 0.2485c + 4.2850d + 1.3845e + 1.3004f-1.1566g+1.8273h-0.94601-0.5193J) a = Toe dysfunction b=Previous ankle injury c = Ankle dysfunction d= SIJ dysfunction e=Lumbar Extension f = Straight Leg Raise g = Psoas length h = Patella squint i = Gluteal muscle length j = Lumbar dysfunction P = probability of non contact injury exp(x) = ex, with e the constant 2.7183 It was also possible to create a prediction model for non contact hip and groin injuries, which appears as follows: P (Groin injury)= exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) l + exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) d = SIJ dysfunction k = Previous knee injury m = Previous hip injury e = Lumbar extension f = Straight leg raise n = Limb dominance p = ND/Bil plyo metric ratio P = probability of groin injury exp(x) = ex, with e the constant 2.7183 It was also possible to create a prediction model for non contact hip and groin injuries, which appears as follows: P (Groin injury)= exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) l + exp(-116.2 + 33.5383d + 14.5108k + 4.1972m + 1.9330e + 10.7006f-14.4028n + 48.8751p) d = SIJ dysfunction k = Previous knee injury m = Previous hip injury e = Lumbar extension f = Straight leg raise n = Limb dominance p = ND/Bil plyo metric ratio P = probability of groin injury exp(x) = ex, with e the constant 2.7183 Using the hip and groin prediction model, combined with the injury prediction model, injuries in youth soccer players can be predicted. The data for each player should first be substituted into the injury prediction model, to determine the chance of getting injured during the season. The data should then be substituted into the hip and groin injury prediction model, determining the chance of hip and groin injuries during the season. The results from the groin injury prediction model could then be used to exclude groin injuries amongst players. A negative result for the hip and groin injury, which showed a false negative percentage of 1.98%, could be used to determine that an injury that was predicted using the overall injury prediction model, would not be a hip and groin injury. A positive result in the groin injury test could, however, not exclude injuries to other body areas that were predicted by the overall injury prediction model, so the groin injury prediction model could only be used to exclude hip and groin injuries. / Thesis (Ph.D. (Education)--North-West University, Potchefstroom Campus, 2009.

Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / A proposta deste estudo foi construir uma cartografia dos modos de fazer psicologia em centros de treinamento (CTs) de categorias de base, bem como das relações da psicologia do esporte com outros saberes/poderes e de seus possíveis efeitos na formação do jogador de futebol, tendo por campo empírico o cotidiano de alguns clubes de Belo Horizonte e do Rio de Janeiro. Em aliança com os pensamentos de Félix Guattari e Gilles Deleuze, apropriamo-nos dos escritos destes e de outros pesquisadores da Análise Institucional como interlocutores nesta cartografia; igualmente, das contribuições de Michel Foucault sobre sociedade disciplinar e biopoder. Estudos antropológicos e sócio-históricos também nos ajudaram a compreender como se constrói a noção/prática de formação no futebol brasileiro contemporâneo. Colaboraram ainda nessa composição os debates metodológico-epistemológicos sobre História Oral, procedimento que funcionou como um dispositivo ético-político durante todo o processo de investigação. Neste sentido, mediante entrevistas de história oral temática, buscou-se conhecer o trabalho de quatro psicólogos do esporte atuantes em categorias de base na atualidade. Complementarmente, observações em centros de treinamento foram realizadas. Nesse percurso, apreendemos nuances da instrumentalização do corpo-atleta que remetem ao processo histórico de construção dos atuais modos de formação do jogador de futebol no Brasil. Pistas sobre os primeiros trabalhos de Psicologia do Esporte de que se tem notícia integram tal processo, e apontam a uma psicologia que também se instrumentalizava, tendo os testes psicométricos como principal recurso. Em uma trajetória na qual forças mais, e menos flexíveis produzem efeitos políticos, vê-se o aspirante a jogador de futebol transformar-se em um atleta que funciona como jogador-peça, jogador-produto, ou mesmo jogador-empresa, a fim de realizar o almejado e muitas vezes inquestionável sonho de ser mundialmente conhecido e aclamado. No espaço dos CTs, disciplina e biopoder se articulam em dispositivos em prol da manutenção de uma produção em moldes capitalísticos. Das modulações das práticas neoliberais surge ainda a figura do empresário para gerenciar a vida dos jogadores e garantir que sejam produtos valorizados no mercado global de boleiros. Embora ainda hoje os testes e os perfis psicológicos sejam instrumentos hegemônicos na psicologia esportiva, as práticas desta última são tão diversas quanto os modos de subjetivação existentes e implicam efeitos às vezes mais, às vezes menos adaptados à promoção do rendimento esportivo e à constituição do atleta empreendedor-de-si mesmo. / The purpose of this study was to construct a cartography about the ways of doing psychology in youth soccer training centers (TCs), and also about relationships between sport psychology and other knowledges/powers and their possible effects on the formation of soccer players, having as an empirical field the daily life of some clubs of Belo Horizonte and Rio de Janeiro. In accordance with the thought of Gilles Deleuze and Felix Guattari, we take the writings of these and other researchers of Institutional Analysis as interlocutors in this cartography; we did the same with the contribution of Michel Foucault about disciplinary society and biopower. Anthropological and social-historic studies also helped us in understanding how the idea / practical of formation is being built in contemporary Brazilian soccer. Oral History methodological and epistemological debates also cooperated in that composition, and this was a procedure that worked as an ethical-political device throughout the research process. In this sense, with thematic oral history interviews, the aim was to get to know the work of four sport psychologists who are active in youth soccer. In addition, observatins were conducted in training centers. Along the way, nuances about the instrumentalization of the body-athlete which refer to the historical process of the construction of current modes of training soccer players in Brazil have been apprehend. Clues about the first works in Sport Psychology which are known to us integrate this process and point to a psychology that had been also instrumentalized, having the psychometric tests as its main resource. In a trajectory in which forces - sometimes more, sometimes less flexible produce political effects, the aspiring soccer player becomes an athlete who works as a piece- player, a product-player, or even an enterprise-player in order to realize the desired, and often unquestioned, dream of being a world-renowned and acclaimed soccer player. At TCs spaces, discipline and biopower are articulated as devices for the maintenance of production in the capitalistic framework. From the modulations of neoliberal practices the entrepreneur also appears, to manage players? lives and ensure that they become high-valued products in the global marketplace of footballers. Although the tests and psychological profiling tools are still hegemonic in the practice of sport psychology, those practices are as diverse as the existing modes of subjectivation and imply effects - sometimes more, sometimes less adapted to the promotion of sport performance and to the establishment of the athlete entrepreneur-of-itself.

Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / A proposta deste estudo foi construir uma cartografia dos modos de fazer psicologia em centros de treinamento (CTs) de categorias de base, bem como das relações da psicologia do esporte com outros saberes/poderes e de seus possíveis efeitos na formação do jogador de futebol, tendo por campo empírico o cotidiano de alguns clubes de Belo Horizonte e do Rio de Janeiro. Em aliança com os pensamentos de Félix Guattari e Gilles Deleuze, apropriamo-nos dos escritos destes e de outros pesquisadores da Análise Institucional como interlocutores nesta cartografia; igualmente, das contribuições de Michel Foucault sobre sociedade disciplinar e biopoder. Estudos antropológicos e sócio-históricos também nos ajudaram a compreender como se constrói a noção/prática de formação no futebol brasileiro contemporâneo. Colaboraram ainda nessa composição os debates metodológico-epistemológicos sobre História Oral, procedimento que funcionou como um dispositivo ético-político durante todo o processo de investigação. Neste sentido, mediante entrevistas de história oral temática, buscou-se conhecer o trabalho de quatro psicólogos do esporte atuantes em categorias de base na atualidade. Complementarmente, observações em centros de treinamento foram realizadas. Nesse percurso, apreendemos nuances da instrumentalização do corpo-atleta que remetem ao processo histórico de construção dos atuais modos de formação do jogador de futebol no Brasil. Pistas sobre os primeiros trabalhos de Psicologia do Esporte de que se tem notícia integram tal processo, e apontam a uma psicologia que também se instrumentalizava, tendo os testes psicométricos como principal recurso. Em uma trajetória na qual forças mais, e menos flexíveis produzem efeitos políticos, vê-se o aspirante a jogador de futebol transformar-se em um atleta que funciona como jogador-peça, jogador-produto, ou mesmo jogador-empresa, a fim de realizar o almejado e muitas vezes inquestionável sonho de ser mundialmente conhecido e aclamado. No espaço dos CTs, disciplina e biopoder se articulam em dispositivos em prol da manutenção de uma produção em moldes capitalísticos. Das modulações das práticas neoliberais surge ainda a figura do empresário para gerenciar a vida dos jogadores e garantir que sejam produtos valorizados no mercado global de boleiros. Embora ainda hoje os testes e os perfis psicológicos sejam instrumentos hegemônicos na psicologia esportiva, as práticas desta última são tão diversas quanto os modos de subjetivação existentes e implicam efeitos às vezes mais, às vezes menos adaptados à promoção do rendimento esportivo e à constituição do atleta empreendedor-de-si mesmo. / The purpose of this study was to construct a cartography about the ways of doing psychology in youth soccer training centers (TCs), and also about relationships between sport psychology and other knowledges/powers and their possible effects on the formation of soccer players, having as an empirical field the daily life of some clubs of Belo Horizonte and Rio de Janeiro. In accordance with the thought of Gilles Deleuze and Felix Guattari, we take the writings of these and other researchers of Institutional Analysis as interlocutors in this cartography; we did the same with the contribution of Michel Foucault about disciplinary society and biopower. Anthropological and social-historic studies also helped us in understanding how the idea / practical of formation is being built in contemporary Brazilian soccer. Oral History methodological and epistemological debates also cooperated in that composition, and this was a procedure that worked as an ethical-political device throughout the research process. In this sense, with thematic oral history interviews, the aim was to get to know the work of four sport psychologists who are active in youth soccer. In addition, observatins were conducted in training centers. Along the way, nuances about the instrumentalization of the body-athlete which refer to the historical process of the construction of current modes of training soccer players in Brazil have been apprehend. Clues about the first works in Sport Psychology which are known to us integrate this process and point to a psychology that had been also instrumentalized, having the psychometric tests as its main resource. In a trajectory in which forces - sometimes more, sometimes less flexible produce political effects, the aspiring soccer player becomes an athlete who works as a piece- player, a product-player, or even an enterprise-player in order to realize the desired, and often unquestioned, dream of being a world-renowned and acclaimed soccer player. At TCs spaces, discipline and biopower are articulated as devices for the maintenance of production in the capitalistic framework. From the modulations of neoliberal practices the entrepreneur also appears, to manage players? lives and ensure that they become high-valued products in the global marketplace of footballers. Although the tests and psychological profiling tools are still hegemonic in the practice of sport psychology, those practices are as diverse as the existing modes of subjectivation and imply effects - sometimes more, sometimes less adapted to the promotion of sport performance and to the establishment of the athlete entrepreneur-of-itself.

Name: Assessment of individual game performance in football players U10 Objectives: The aim of the thesis is to analyse the success rate of the chosen playing skills in competitive matches in the U10 category in football. Methods: The researched group was made of fifteen individuals, including two goalkeepers, with the average age 10 years, ± 0,5 year. The individuals were observed and evaluated in five matches. The method of analysis was used to gather the data. The data were taken down by the scale system and written into the recording sheet. Three football skills were chosen for the research - pass, dribbling past the opponent, and ball reception. Nonparametric coefficient r was used for the determination of material significance of the differences. Results: Much higher success rate of the pass was discovered on the defensive half in comparison to the attacking half (85,84 % vs. 72,37 %; r = 0,83). Dribbling past the opponent was more frequent on the attacking half in comparison to the defensive half (28,37 vs. 21,67; coefficient r = 0,78), however, there was not any significant difference in the success on the attacking half in comparison to the defensive half (57,39 % vs. 53,39 %; coefficient r = 0,27). Player's passes were more successful compared to their dribbling-past-the-opponent skill...