Investigating the perceived effectiveness of digital technology for elite athlete support in golf

Digital technologies have enabled vast and varied amounts of data to be captured on elite athletes. The data is intended for use by athletes, coaches and support team e.g. physiotherapists, sports scientists for many purposes including performance development or injury prevention. However, the usefulness of such digital technologies and the information gathered is only beneficial if deemed effective by all those involved. The purpose of this study was to investigate the effectiveness of digital technology for elite athletes’ development and support from athlete, coach and support team perspective in golf. Interviews were conducted with athletes, coaches and support team for a sport where digital technologies were used to facilitate training. The results of the study uncovered four categories that helped to understand how effectiveness was perceived which were “The Influence on Psychological Well-being and Proprioception”, “Measurement Uncertainty”, “Environment” and “Type, Ease and Frequency of Use”. Exploring these categories provided insight into the best practices for digital technology integration into elite athlete support and ultimately can help shape future developments of digital technologies.</div

Matching golfers’ movement patterns during a golf swing

The golf swing is a multidimensional movement requiring alternative data analysis methods to interpret non-linear relationships in biomechanics data related to golf shot outcomes. The purpose of this study was to use a combined principal component analysis (PCA), fuzzy coding, and multiple correspondence analysis (MCA) data analysis approach to visualise associations within key biomechanics movement patterns and impact parameters in a group of low handicap golfers. Biomechanics data was captured and analysed for 22 golfers when hitting shots with their own driver. Relationships between biomechanics variables were firstly achieved by quantifying principal components, followed by fuzzy coding and finally MCA. Clubhead velocity and ball velocity were included as supplementary data in MCA. A total of 35.9% of inertia was explained by the first factor plane of MCA. Dimension one and two, and subsequent visualisation of MCA results, showed a separation of golfers’ biomechanics (i.e., swing techniques). The MCA plot can be used to simply and quickly identify movement patterns of a group of similar handicap golfers if supported with appropriate descriptive interpretation of the data. This technique also has the potential to highlight mismatched golfer biomechanics variables which could be contributing to weaker impact parameters

Comparison of centre of gravity and centre of pressure patterns in the golf swing

Analysing the centre of pressure (COP) and centre of gravity (COG) could reveal stabilising strategies used by golfers throughout the golf swing. This study identified and compared golfers’ COP and COG patterns throughout the golf swing in medial–lateral (ML) and anterior–posterior (AP) directions using principal component analysis (PCA) and examined their relationship to clubhead velocity. Three-dimensional marker trajectories were collected using Vicon motion analysis and force plate data from two Kistler force plates for 22 low-handicap golfers during drives. Golfers’ COG and COP were expressed as a percentage distance between their feet. PCA was performed on COG and COP in ML and AP directions. Relationships between principal component (PC) scores were examined using Pearson correlation and regression analysis used to examine the relationship with clubhead velocity. ML COP movements varied in magnitude (PC1), rate of change and timing (PC2 and PC3). The COP and COG PC1 scores were strongly correlated in both directions (ML: r = 0.90, P < .05; AP: r = 0.81, P < .05). Clubhead velocity, explained by three PCs (74%), related to timing and rate of change in COPML near downswing (PC2 and PC3) and timing of COGML late backswing (PC2). The relationship between COPML and COGML PC1 scores identified extremes of COP and COG patterns in golfers and could indicate a golfer’s dynamic balance. Golfers with earlier movement of COP to the front foot (PC2) and rate of change (PC3) patterns in ML COP, prior to the downswing, may be more likely to generate higher clubhead velocity

How valid and accurate are measurements of golf impact parameters obtained using commercially available radar and stereoscopic optical launch monitors?

© 2017 The application of measurement technology in golf is increasing. In particular, measures of golf performance are valuable to coaches, golfers, club-fitters and equipment manufacturers. Commercially available launch monitors, such as the TrackMan Pro IIIe and Foresight GC2 + HMT, offer bespoke instantaneous methods to measure such parameters. Uncertainty in the outputs, however, is not well established nor independently verified. This study aimed to determine the degree of agreement between parameters from two launch monitors with measurements taken using a benchmark system. A total of 240 shots were collected with a driver, 7-iron and utility wedge. Shots were simultaneously tracked by each system and outputs compared using Limits of Agreement analysis. In addition, two reference grades were defined based on different levels of agreement; research and coaching grade. Agreement between the launch monitors and the benchmark system was noticeably stronger for ball parameters with greater variability in clubhead parameters. Furthermore, for both launch monitors, the strength of agreement for several parameters varied between clubs. The majority of ball parameters from both launch monitors fell within the research reference grade, but caution is needed for the use of clubhead parameters within a research environment. For coaches and clubfitters, the results suggest the launch monitor parameters are largely of sufficient quality

Elite players’ perceptions of football playing surfaces: a mixed effects ordinal logistic regression model of players’ perceptions

The aim of this study was to determine potential explanatory factors that may be associated with different attitudes amongst the global population of elite footballers to the use of different surfaces for football. A questionnaire was used to capture elite football players’ perceptions of playing surfaces and a mixed effects ordinal logistic regression model was used to explore potential explanatory factors of players’ perceptions. In total, responses from 1129 players from 44 different countries were analysed. The majority of players expressed a strong preference for the use of Natural Turf pitches over alternatives such as Artificial Turf. The regression model, with a players’ country as a random effect, indicated that players were less favourable towards either Natural Turf or Artificial Turf where there was perceived to be greater variability in surface qualities or the surface was perceived to have less desirable properties. Player’s surface experience was also linked to their overall attitudes, with a suggestion that the quality of the Natural Turf surface players experienced dictated players’ support for Artificial Turf

Comparison of two- and three-dimensional methods for analysis of trunk kinematic variables in the golf swing

Two-dimensional methods have been used to compute trunk kinematic variables (flexion/extension, lateral bend, axial rotation) and X-factor (difference in axial rotation between trunk and pelvis) during the golf swing. Recent X-factor studies advocated three-dimensional (3D) analysis due to the errors associated with two-dimensional (2D) methods, but this has not been investigated for all trunk kinematic variables. The purpose of this study was to compare trunk kinematic variables and X-factor calculated by 2D and 3D methods to examine how different approaches influenced their profiles during the swing. Trunk kinematic variables and X-factor were calculated for golfers from vectors projected onto the global laboratory planes and from 3D segment angles. Trunk kinematic variable profiles were similar in shape; however, there were statistically significant differences in trunk flexion (-6.5 ± 3.6°) at top of backswing and trunk right-side lateral bend (8.7 ± 2.9°) at impact. Differences between 2D and 3D X-factor (approximately 16°) could largely be explained by projection errors introduced to the 2D analysis through flexion and lateral bend of the trunk and pelvis segments. The results support the need to use a 3D method for kinematic data calculation to accurately analyze the golf swing

Golf coaches' perceptions of key technical swing parameters compared to biomechanical literature

Assessing a coach's technical knowledge of a sporting technique can reveal measureable biomechanical parameters associated with a successful performance. Therefore, the purpose of this study was to identify the key technical parameters that golf coaches associate with a successful golf swing. Sixteen high-level golf coaches were observed coaching a highly skilled golfer after which they participated in a semi-structured interview regarding their technical analysis of the golf swing. The data were inductively analysed and five intrinsically linked key technical parameters were identified: ‘Posture’, Body Rotation’, ‘Arm and Wrist Action’, ‘Sequential Movement and Body Segments' and ‘Club Motion’. The parameters Posture and Body Rotation were further sub-categorised and compared to the existing biomechanical literature whereby gaps in knowledge were identified. The results of this study can be used to guide future golf biomechanics research and coaching technologies

The preferred movement path paradigm: influence of running shoes on joint movement

PURPOSE: (a) to quantify differences in lower extremity joint kinematics for groups of runners subjected to different running footwear conditions, and (b) to quantify differences in lower extremity joint kinematics on an individual basis for runners subjected to different running footwear conditions. METHODS: Three-dimensional ankle and knee joint kinematics were collected for 35 heel-toe runners when wearing three different running shoes and when running barefoot. Absolute mean differences in ankle and knee joint kinematics were computed between running shoe conditions. The percentage of individual runners who displayed differences below a 2°, 3° and 5° threshold were also calculated. RESULTS: The results indicate that the mean kinematics of the ankle and knee joints were similar between running shoe conditions. Aside from ankle dorsi-flexion and knee flexion, the percentage of runners maintaining their movement path between running shoes (i.e. less than 3°) was in the order of magnitude of about 80 to 100%. Many runners showed ankle and knee joint kinematics that differed between a conventional running shoe and barefoot by more than 3°, especially for ankle dorsiflexion and knee flexion CONCLUSION: Many runners stay in the same movement path (the preferred movement path) when running in various different footwear conditions. The percentage of runners maintaining their preferred movement path depends on the magnitude of the change introduced by the footwear condition

Investigating the effectiveness of digital technology for elite athlete development and support from athlete, coach and support team perspectives: Final report for the IOC Olympic Studies Centre Advanced Olympic Research Grant Programme 2018/2019 Award

Digital technologies have enabled vast and varied amounts of data to be captured on elite athletes. The data is intended for use by athletes, coaches and practitioners e.g. physiotherapists, sports scientists for a plethora of purposes including performance development or injury prevention. The purpose of this project was to investigate the effectiveness of digital technology for elite athletes’ development and support from athlete, coach and support team perspective. Semi-structured interviews were conducted with athletes, coaches and support team for two sports: trampoline gymnastics and golf, where digital technologies were used to facilitate elite athlete training. The results of the study provided insight into the long-term effectiveness and best practices for digital technology for elite athlete support and ultimately could help shape future developments for digital technologies

Just noticeable differences in the length of golf irons

Current custom fitting guidelines for golf clubs suggest the smallest change in club length from a standard length iron should be 6 mm (1/4”). However, no previous research suggests why this length change is used. This study aims to identify the minimum noticeable difference in the length of 7-iron clubs using just noticeable difference analysis techniques. Fifty golfers of varying ability were asked to compare a standard length 7-iron to test 7-irons of varying lengths, regarding changes in the perception of club length and body position at address. Irrespective of golfing ability, golfers could perceive a just noticeable difference of 13 mm (1/2”) from the standard length club. However, when asked if changes in body position were present, category 1 golfers noticed differences with a 6 mm change in club length and category 2 golfers noticed differences with a 13 mm change. No changes in body position were perceived by highly handicapped golfers