Putting the "I" Back in Team

Statistical Tests for Sports Science Practitioners: Identifying Performance Gains in Individual Athletes

ABSTRACT

Harry, JR, Hurwitz, J, Agnew, C, and Bishop, C. Statistical tests for sports science practitioners: identifying performance gains in individual athletes. J Strength Cond Res 38(5): e264-e272, 2024-There is an ongoing surge of sports science professionals within sports organizations. However, when seeking to determine training-related adaptations, sports scientists have demonstrated continued reliance on group-style statistical analyses that are held to critical assumptions not achievable in smaller-sample team settings. There is justification that these team settings are better suited for replicated single-subject analyses, but there is a dearth of literature to guide sports science professionals seeking methods appropriate for their teams. In this report, we summarize 4 methods' ability to detect performance adaptations at the replicated single-subject level and provide our assessment for the ideal methods. These methods included the model statistic, smallest worthwhile change, coefficient of variation (CV), and standard error of measurement (SEM), which were discussed alongside step-by-step guides for how to conduct each test. To contextualize the methods' use in practice, real countermovement vertical jump (CMJ) test data were used from 4 (2 females and 2 males) athletes who complete 5 biweekly CMJ test sessions. Each athlete was competing in basketball at the NCAA Division 1 level. We concluded that the combined application of the model statistic and CV methods should be preferred when seeking to objectively detect meaningful training adaptations in individual athletes. This combined approach ensures that the differences between the tests are (a) not random and (b) reflect a worthwhile change. Ultimately, the use of simple and effective methods that are not restricted by group-based statistical assumptions can aid practitioners when conducting performance tests to determine athlete adaptations.

A survey into the current fitness testing practices of elite male soccer practitioners: from assessment to communicating results

This study provides insight into the current fitness testing practices in elite male soccer. One hundred and two practitioners from professional soccer leagues across 24 countries completed an online survey comprising 29 questions, with five sections: a) background information, b) testing selection, c) testing implementation, d) data analysis, and e) data reporting. Frequency analysis was used to evaluate the responses to fixed response questions and thematic analysis was used for open-ended questions to generate clear and distinct themes. Strength (85%) and aerobic capacity (82%) represent the most frequently assessed physical qualities. Scientific literature (80%) is the most influential factor in testing selection and practitioners conduct fitness testing less frequently than their perceived ideal frequency per season (3.6 ± 2 vs. 4.5 ± 2). Time and competitive schedule were the greatest barriers to fitness testing administration. Practitioners mostly used a 'hybrid' approach (45%) to fitness testing, blending 'traditional' (i.e., a day dedicated to testing) and 'integrated' (i.e., testing within regular training sessions) methods. Microsoft Excel is the most used software for data analysis (95%) and visualization (79%). An equal use of the combination of best and mean scores of multiple trials (44%) and the best score (42%) was reported. Comparing a player's test performance with previous scores (89%) was the most common method for interpreting test results. However, only 38% considered measurement error. Digital displays and verbal feedback are the most common data reporting methods, with different data reporting processes for coaches and players. Practitioners can use data and findings from this study to inform their current testing practices and researchers to further identify areas for investigation, with the overarching aim of developing the field of fitness testing in elite male soccer.

Relationships between surrogate measures of mechanical and psychophysiological load, patellar tendon adaptations, and neuromuscular performance in NCAA division I men's volleyball athletes

Introduction

Patellar tendon adaptations occur in response to mechanical load. Appropriate loading is necessary to elicit positive adaptations with increased risk of injury and decreased performance likely if loading exceeds the capacity of the tendon. The aim of the current study was to examine intra-individual associations between workloads and patellar tendon properties and neuromuscular performance in collegiate volleyball athletes.

Methods

National Collegiate Athletics Association Division I men's volleyball athletes (n = 16, age: 20.33 ± 1.15 years, height: 193.50 ± 6.50 cm, body mass: 84.32 ± 7.99 kg, bodyfat%: 13.18 ± 4.72%) competing across 9 weeks of in-season competition participated. Daily measurements of external workloads (i.e., jump count) and internal workloads [i.e., session rating of perceived exertion (sRPE)] were recorded. Weekly measurements included neuromuscular performance assessments (i.e., countermovement jump, drop jump), and ultrasound images of the patellar tendon to evaluate structural adaptations. Repeated measures correlations (r-rm) assessed intra-individual associations among performance and patellar tendon metrics.

Results

Workload measures exhibited significant negative small to moderate (r-rm =-0.26-0.31) associations with neuromuscular performance, negative (r-rm = -0.21-0.30), and positive (r-rm = 0.20-0.32) small to moderate associations with patellar tendon properties.

Discussion

Monitoring change in tendon composition and performance adaptations alongside workloads may inform evidence-based frameworks toward managing and reducing the risk of the development of patellar tendinopathy in collegiate men's volleyball athletes.

The reliability, validity and sensitivity of an individualised sub-maximal fitness test in elite rugby league athletes

We aimed to examine the reliability, validity and sensitivity of an individualised sub-maximal fitness test (SMFTIFT60). Nineteen elite rugby league players performed a one-week test-retest of SMFTIFT60. Typical Errors and ICCs were: small (<3.5%) and extremely high (>0.90) for accelerometer-derived variables; moderate (<2.5% points) and moderate to very high (0.71-0.89) for exercise and recovery heart rate (HRex and HRR, respectively). Convergent validity correlations with the 10-week pre-season change in 30-15 Intermittent Fitness Test performance were large for changes in SMFTIFT60 HRex (r = -0.57) and HRR (0.60), and very large for changes in accelerometer measures (range: -0.71 to -0.79). For sensitivity, within-player dose-response relationships between SMFTIFT60 HRex and prior 3-day training loads were negative and ranged from moderate (session ratings of perceived exertion [sRPE-TL], r = -0.34), to large (high-speed running distance, -0.51; acceleration load, -0.73) and very large (heart rate Training Impulse [TRIMP], -0.83). All other relationships were unclear or trivial to small. Physiological and accelerometer-derived measures from the SMFTIFT60 are reliable and valid for the assessment of fitness in rugby league players. Only HRex appears sensitive to acute changes in training load. The SMFTIFT60 could be a useful monitoring tool in team sports.

Load Monitoring Practice in Elite Women Association Football

The description of current load monitoring practices may serve to highlight developmental needs for both the training ground, academia and related industries. While previous studies described these practices in elite men's football, no study has provided an overview of load monitoring practices in elite women's football. Given the clear organizational differences (i.e., professionalization and infrastructure) between men's and women's clubs, making inferences based on men's data is not appropriate. Therefore, this study aims to provide a first overview of the current load monitoring practices in elite women's football. Twenty-two elite European women's football clubs participated in a closed online survey (40% response rate). The survey consisted of 33 questions using multiple choice or Likert scales. The questions covered three topics; type of data collected and collection purpose, analysis methods, and staff member involvement. All 22 clubs collected data related to different load monitoring purposes, with 18 (82%), 21 (95%), and 22 (100%) clubs collecting external load, internal load, and training outcome data, respectively. Most respondents indicated that their club use training models and take into account multiple indicators to analyse and interpret the data. While sports-science staff members were most involved in the monitoring process, coaching, and sports-medicine staff members also contributed to the discussion of the data. Overall, the results of this study show that most elite women's clubs apply load monitoring practices extensively. Despite the organizational challenges compared to men's football, these observations indicate that women's clubs have a vested interest in load monitoring. We hope these findings encourage future developments within women's football.

The Relative Age Effect on Competition Performance of Spanish International Handball Players: A Longitudinal Study

Background: Competitive success is the ultimate objective of elite professional sport organisations. Relative age effects (RAE) impact athlete selection processes in the short and long-term performance. The aims of this study were: (i) examine the presence of RAE by gender, competitive level, and playing position, as well as evaluate the impact of RAE on individual (goals, percentage of effectiveness in shots, saves; percentage of effectiveness in saves, assists, turnovers, steals, blocked shots, penalties, minutes played, and minutes played per match) and collective competition performance (final team position); and (ii) analyse the impact of RAE on the evolutionary trends of individual performance in international competitions throughout 16 seasons in Spanish handball (2005–2020).

Methods: The sample included 631 Spanish handball players (male: n = 359; female: n = 272). A Chi-square goodness-of-fit test was used to assess whether a skewed birthdate distribution occurred. A one-way analysis of variance (ANOVA) of independent measures was used to examine the individual and collective statistical parameters by birth quartiles. A linear regression in a Hopkins sheet were performed to compare individual performance trends.

Results: The results revealed RAE in the male formative categories (p < 0.001), as well as the male and female senior categories (p < 0.05). By position, RAE especially affected the “centre-back” in the male formative (p < 0.01) and senior categories (p < 0.05). No significant relationship between RAE and individual performance was found in male formative categories, while an impact of RAE on the “minutes played” was detected in the female senior category (p < 0.05). With regard to collective performance, a higher number of relatively older handball players was observed in the best ranked teams in the male formative categories and in the quarter-final teams in the female formative categories (p < 0.05). Among the male players, relatively older players spent more minutes on the court than relatively younger players, although this advantage dissipated over time and did not lead to better performance. Among the female players, relatively younger players were found to perform better as the level of competitive handball increased.

Discussion: These findings are important for talent identification and development policies in sport federations and other elite sport institutions by demonstrating the many unintended consequences of selections to international competitions at the youth level.

Training Load Monitoring Considerations for Female Gaelic Team Sports: From Theory to Practice

Athlete monitoring enables sports science practitioners to collect information to determine how athletes respond to training loads (TL) and the demands of competition. To date, recommendations for females are often adapted from their male counterparts. There is currently limited information available on TL monitoring in female Gaelic team sports in Ireland. The collection and analysis of female athlete monitoring data can provide valuable information to support the development of female team sports. Athletic monitoring can also support practitioners to help minimize risk of excessive TL and optimize potential athletic performance. The aims of this narrative review are to provide: (i) an overview of TL athlete monitoring in female team sports, (ii) a discussion of the potential metrics and tools used to monitor external TL and internal TL, (iii) the advantages and disadvantages of TL modalities for use in Gaelic team sports, and (iv) practical considerations on how to monitor TL to aid in the determination of meaningful change with female Gaelic team sports athletes.

Load Monitoring Practice in European Elite Football and the Impact of Club Culture and Financial Resources

Load monitoring is considered important to manage the physical training process in team sports such as Association Football. Previous studies have described the load monitoring practices of elite English football clubs and clubs with an established sports-science department. An examination of a broader international sample is currently not available. In addition, previous research has suggested factors that may improve the implementation of load monitoring practices, such as a strong club belief on the benefit of evidence-based practice (EBP) and high club financial resources. However, no study has examined yet the actual impact of these factors on the monitoring practices. Therefore, this study aims (1) to provide an overview of load monitoring practices in European elite football and (2) to provide insight into the differences in implementation between clubs by examining the impact of the club beliefs on the benefit of EBP and the club financial resources. An online survey, consisting of multiple choice and Likert scale questions, was distributed among sports-science and sports-medicine staff (n = 99, 50% response rate). Information was asked about the types of data collected, collection purposes, analysis methods, and staff involvement. The results indicated that external load data (e.g., global navigation satellite system, accelerometer…) was collected the most whilst respondents also indicated to collect internal load (e.g., heart rate, rating of perceived exertion…) and training outcome data (e.g., aerobic fitness, neuromuscular fatigue…) for multiple purposes. Considerable diversity in data analysis was observed suggesting that analysis is often limited to reporting the gathered data. Sports-science staff were responsible for data collection and analysis. Other staff were involved in data discussion to share decision-making. These practices were positively impacted by a stronger club belief on the benefit of EBP and greater financial resources. Creating an organizational culture, characterized by a strong belief on the benefit of EBP, is important to increase the impact of load monitoring. However, the actual potential may still be largely determined by financial resources. High-level clubs could therefore play a leading role in generating and sharing knowledge to improve training practices and player health.

The Implementation of Velocity-Based Training Paradigm for Team Sports: Framework, Technologies, Practical Recommendations and Challenges

While velocity-based training is currently a very popular paradigm to designing and monitoring resistance training programs, its implementation remains a challenge in team sports, where there are still some confusion and misinterpretations of its applications. In addition, in contexts with large squads, it is paramount to understand how to best use movement velocity in different exercises in a useful and time-efficient way. This manuscript aims to provide clarifications on the velocity-based training paradigm, movement velocity tracking technologies, assessment procedures and practical recommendations for its application during resistance training sessions, with the purpose of increasing performance, managing fatigue and preventing injuries. Guidelines to combine velocity metrics with subjective scales to prescribe training loads are presented, as well as methods to estimate 1-Repetition Maximum (1RM) on a daily basis using individual load–velocity profiles. Additionally, monitoring strategies to detect and evaluate changes in performance over time are discussed. Finally, limitations regarding the use of velocity of execution tracking devices and metrics such as “muscle power” are commented upon.

Does Mathematical Coupling Matter to the Acute to Chronic Workload Ratio? A Case Study From Elite Sport

Purpose: Criticisms of the acute to chronic workload ratio (ACWR) have been that the mathematical coupling inherent in the traditional calculation of the ACWR results in a spurious correlation. The purposes of this commentary are (1) to examine how mathematical coupling causes spurious correlations and (2) to use a case study from actual monitoring data to determine how mathematical coupling affects the ACWR. Methods: Training and competition workload (TL) data were obtained from international-level open-skill (basketball) and closed-skill (weightlifting) athletes before their respective qualifying tournaments for the 2016 Olympic Games. Correlations between acute TL, chronic TL, and the ACWR as coupled/uncoupled variations were examined. These variables were also compared using both rolling averages and exponentially weighted moving averages to account for any potential benefits of one calculation method over another. Results: Although there were some significant differences between coupled and uncoupled chronic TL and ACWR data, the effect sizes of these differences were almost all trivial (g = 0.04–0.21). Correlations ranged from r = .55 to .76, .17 to .53, and .88 to .99 for acute to chronic TL, acute to uncoupled chronic TL, and ACWR to uncoupled ACWR, respectively. Conclusions: There may be low risk of mathematical coupling causing spurious correlations in the TL–injury-risk relationship. Varying levels of correlation seem to exist naturally between acute and chronic TL variables regardless of coupling. The trivial to small effect sizes and large to nearly perfect correlations between coupled and uncoupled AWCRs also imply that mathematical coupling may have little effect on either calculation method, if practitioners choose to apply the ACWR for TL monitoring purposes.

Visualizing the Complexity of the Athlete-Monitoring Cycle Through Principal-Component Analysis

PURPOSE

To discuss the use of principal-component analysis (PCA) as a dimension-reduction and visualization tool to assist in decision making and communication when analyzing complex multivariate data sets associated with the training of athletes.

CONCLUSIONS

Using PCA, it is possible to transform a data matrix into a set of orthogonal composite variables called principal components (PCs), with each PC being a linear weighted combination of the observed variables and with all PCs uncorrelated to each other. The benefit of transforming the data using PCA is that the first few PCs generally capture the majority of the information (ie, variance) contained in the observed data, with the first PC accounting for the highest amount of variance and each subsequent PC capturing less of the total information. Consequently, through PCA, it is possible to visualize complex data sets containing multiple variables on simple 2D scatterplots without any great loss of information, thereby making it much easier to convey complex information to coaches. In the future, athlete-monitoring companies should integrate PCA into their client packages to better support practitioners trying to overcome the challenges associated with multivariate data analysis and interpretation. In the interim, the authors present here an overview of PCA and associated R code to assist practitioners working in the field to integrate PCA into their athlete-monitoring process.

Getting the most out of intensive longitudinal data: a methodological review of workload-injury studies

OBJECTIVES

To systematically identify and qualitatively review the statistical approaches used in prospective cohort studies of team sports that reported intensive longitudinal data (ILD) (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Since longitudinal research can be improved by aligning the (1) theoretical model, (2) temporal design and (3) statistical approach, we reviewed the statistical approaches used in these studies to evaluate how closely they aligned these three components.

DESIGN

Methodological review.

METHODS

After finding 6 systematic reviews and 1 consensus statement in our systematic search, we extracted 34 original prospective cohort studies of team sports that reported ILD (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Using Professor Linda Collins' three-part framework of aligning the theoretical model, temporal design and statistical approach, we qualitatively assessed how well the statistical approaches aligned with the intensive longitudinal nature of the data, and with the underlying theoretical model. Finally, we discussed the implications of each statistical approach and provide recommendations for future research.

RESULTS

Statistical methods such as correlations, t-tests and simple linear/logistic regression were commonly used. However, these methods did not adequately address the (1) themes of theoretical models underlying workloads and injury, nor the (2) temporal design challenges (ILD). Although time-to-event analyses (eg, Cox proportional hazards and frailty models) and multilevel modelling are better-suited for ILD, these were used in fewer than a 10% of the studies (n=3).

CONCLUSIONS

Rapidly accelerating availability of ILD is the norm in many fields of healthcare delivery and thus health research. These data present an opportunity to better address research questions, especially when appropriate statistical analyses are chosen.