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The Variability in Kinematics and Carry in a Longitudinal Intra-individual Study of Elite Golfers

Parker, James, 1980- (author)
Högskolan i Halmstad,Rydberglaboratoriet för tillämpad naturvetenskap (RLAS),Scandinavian College of Sport, Gothenburg, Sweden
Hellström, John, 1968- (author)
Högskolan i Halmstad,Akademin för ekonomi, teknik och naturvetenskap,Swedish Golf Federation, Stockholm, Sweden
Ivarsson, Andreas, 1984- (author)
Högskolan i Halmstad,Centrum för forskning om välfärd, hälsa och idrott (CVHI)
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Johnson, Urban, 1961- (author)
Högskolan i Halmstad,Centrum för forskning om välfärd, hälsa och idrott (CVHI)
Olsson, Charlotte, 1967- (author)
Högskolan i Halmstad,Rydberglaboratoriet för tillämpad naturvetenskap (RLAS)
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 (creator_code:org_t)
2016
2016
English.
In: Abstracts. ; , s. 47-48
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Purpose: To hit further and with high accuracy is important for success in the long game in golf. Even for very accomplished golfers a certain degree of between shot variance is evident even when trying to consistently repeat a successful shot. The consistency is determined by the biomechanics of the golfer, which influences club head speed (CHS) and position, and initial ball launch conditions, which in combination with environmental factors determine shot outcome. Previous research has identified several biomechanical variables associated with variance in CHS, including thorax rotation speed  and lead arm speed (LAS). Pilot data from our laboratory have indicated moderate non-significant relationship between CHS and carry in elite male golfers when studied over time. Thus, the aim of this study was to explore the relationship between peak speed of the pelvis, thorax, and lead upper arm and carry over time, investigating both within and between session variability in elite male golfers.Methods: Six elite male golfers (handicap range -3 to +0.5) (age range 21-23 years) were included in this study. The golfers were studied on four separate occasions over a year.  Each test occasion included a golf specific warm-up of the golfers’ choice, then subjects were instructed to hit five balls with their driver and use the swing that was as ‘normal ‘as possible. Data on swing kinematics was collected using a four sensor electromagnetic motion capture system at 120Hz (Polhemus Inc. USA). Nine landmarks were digitized to define segment lengths, orientations and joint axes. CHS and carry were collected using a launch monitor (Trackman3e, v.3.2, Trackman, Denmark). The swing events were determined from sensors on the club; top of backswing was determined when the club changes direction from backswing to downswing. Impact was determined when the clubhead reaches the horizontal position equivalent to where it was at address. Angular velocities and displacements of the pelvis, thorax, and lead arm were calculated using standard biomechanics principles in conjunction with advanced motion measurement software (AMM 3D, USA). No data smoothing techniques were used before data analysis. IBM SPSS v.22 was used to analyse the data through hierarchical multilevel modelling (MLM). First a baseline model without predictors was run, then MLM was repeated with predictors where the first level of the data contained carry and kinematic data from each shot (within session level). At the second level, the carry scores were nested within sessions and analysed between sessions. Lastly, at the third level, the sessions were nested within players (between players). Carry was used as outcome variable and kinematics as predictor variables with a probability level of 0.05.Results: Initially MLM baseline model for carry only, was tested) without predictors. The results showed a statistical significant intercept (Estimate = 226.24, p<.001). Intraclass correlations (ICC) suggested that 32.5% of the variance in carry were present within sessions (level 1), whilst 38.0% were attributed to differences in carry between sessions (level 2). Results from the second MLM generated an improved model fit (-2 LL & BIC) where peak speeds of the pelvis, thorax, and lead upper arm were included as fixed effect covariates on level 1. The result showed that peak LAS was a statistically significant predictor of carry (β=.17, p=.001) whereas peek speed of neither thorax (β=-.04, p=.364) nor pelvis (β=.02, p=.673) had any statistically significant relationship with carry.Discussion: The present study found that 32.5% of variation in shot consistency can be explained at the within session level (influenced by for example variance in centeredness of impact), and 38% of variation in shot consistency can be explained at the between session level (influenced by for example environmental factors). Furthermore, LAS was the only significant predictor of within session variance in carry. Our results indicated peak LAS speed as a predictor of within session variance in carry and this is partly supported by previous research who found golfers with higher arm speed had higher ball velocity than golfers with lower arm speed(Healy et al., 2011). However, results from our pilot study differ from previous research which reports a relationship between peak thorax speed and driver performance. The difference could be due to our results being based on longitudinal data at intra-individual level, whereas previous studies have used a cross-sectional study design, different analysis methods and reported at an inter-individual level. In conclusion, our preliminary data show that within session LAS is a predictor of carry distance when the objective is shot consistency. Practitioners may consider training strategies to optimize arm speed when improve driving consistency among elite golfers. ReferencesHealy, A., Moran, K. A., Dickson, J., Hurley, C., Smeaton, A. F., O'Connor, N. E., . . . Chockalingam, N. (2011). Analysis of the 5 iron golf swing when hitting for maximum distance. Journal of sports sciences, 29(10), 1079-1088. 

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap -- Idrottsvetenskap (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Health Sciences -- Sport and Fitness Sciences (hsv//eng)

Keyword

Golf biomechanics
driving performance
consistency
longitudinal
multi-level modelling

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ref (subject category)
kon (subject category)

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