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Missing data are often unavoidable. The reason values go missing, along with decisions made of how missing data are handled (deleted or imputed), can have a profound effect on the validity and accuracy of study results. In this article, we aimed to: estimate the proportion of studies in football research that included a missing data statement, highlight several practices to avoid in relation to missing data, and provide recommendations for exploring, visualising and reporting missingness. Football related articles, published in 2019 were studied. A survey of 136 articles, sampled at random, was conducted to determine whether a missing data statement was included. As expected, the proportion of studies in football research that included a missing data statement was low, at only 11.0% (95% CI: 6.3% to 17.5%); suggesting that missingness is seldom considered by researchers. We recommend that researchers describe the number and percentage of missing values, including when there are no missing values. Exploratory analysis should be conducted to explore missing values, and visualisations describing missingness overall should be provided in the paper, or at least supplementary materials. Missing values should almost always be imputed, and imputation methods should be explored to ensure they are appropriately representative. Researchers should consider these recommendations, and pay greater attention to missing data and its influence on research results.

Performance indicators that contributed to success at the group stage and play-off stages of the 2019 Rugby World Cup were analysed using publicly available data obtained from the official tournament website using both a non-parametric statistical technique, Wilcoxon's signed rank test, and a decision rules technique from machine learning called RIPPER. Our statistical results found that ball carry effectiveness (percentage of ball carries that penetrated the opposition gain-line) and total metres gained (kick metres plus carry metres) were found to contribute to success at both stages of the tournament and that indicators that contributed to success during the group stages (dominating possession, making more ball carries, making more passes, winning more rucks, and making less tackles) did not contribute to success at the play-off stage. Our results using RIPPER found that low ball carries and a low lineout success percentage jointly contributed to losing at the group stage, while winning a low number of rucks and carrying over the gain-line a sufficient number of times contributed to winning at the play-off stage of the tournament. The results emphasise the need for teams to adapt their playing strategies from the group stage to the play-off stage at tournament in order to be successful.

The concept of competitive balance is considered to be an essential aspect in the field of sport economics. This work describes a novel approach for measuring and evaluating competitive balance through concentration of championships. The concentration of championships was assessed using a sliding window approach with the length of five consecutive competitions (years) and a single competition (year) increment over the whole evaluated period. Because the sliding window was relatively short, the newly developed index, termed ‘We Are the Champions’ (WAC5), is sensitive to rapid changes in competitive balance. The WAC5 index, average WAC5, expected WAC5, and ΔWAC5 were applied to data from 68 competitions of several individual and team sports collected for the 1960 – 2020 period. The significance of indices was tested by resampling (bootstrapping and permutation). The results of the study show a growth in competitive balance of several ice hockey competitions (national and international), but decreasing competitive balance in Formula 1 racing and in several European soccer competitions. In soccer competitions, there was a substantially lower competitive balance in a league than in a domestic cup competition within each country/federation. The difference between the overall competitive balance in the most popular, North American, professional leagues and the top European soccer leagues is growing. A significant grouping of champions was determined for all sports involving individual athletes, but also for several team competitions.

International audience; This study compared changes in the energy-time profiles in pole vaulting using several body models. Two-dimensional kinematics were collected from 20 successful vaults (5.20-6.01 m) performed by 10 athletes during a national meet. The linear and angular kinetic, potential, and total mechanical energy-time profiles were obtained from three pole vaulter models composed of 12, 5, and 3 segments (M12, M5, and M3, respectively), as well as calculated and approximated centre of mass models. One-dimensional statistical parametric mapping was used to compare these energy-time profiles from the models, while agreements of discrete energy parameters were assessed. For all the studied energy-time profiles, there was a main effect (0.05 < p < 0.001) of the models, but pairwise comparisons showed that M5 presented the lowest differences with M12 in comparison with the other models (M3 and approximated centre of mass models). In addition, M5 showed better agreement (lower bias and small effect size) with M12 for the studied energy parameters compared to the other models. Therefore, M5 may be a reliable option to simplify the body model and speed up the computation of the energy-time profiles of the pole vaulter.

The COVID-19 pandemic has caused mandatory lockdowns leading to disruptions in sports training programs. This study aimed to determine the effects of a 16-week COVID-19 lockdown on body composition as well as kinetic and kinematic parameters of the countermovement jump (CMJ) for professional martial artists. Thirteen (n=13) professional martial artists participated in this retrospective cohort study. Subjects were tested on the CMJ at four timepoints: 1) pre-lockdown (pre), 2) immediately post-lockdown (post), 3) two weeks post-lockdown (post+2), and 4) four weeks post-lockdown (post+4). Body composition was measured via bioelectrical impedance and jump data were collected using a force platform sampling at 1,000 Hz. Individual repeated-measures ANOVAs were conducted with pairwise post-hoc analyzes. Differences were observed in vertical jump height (VJH) of 10.33%, peak velocity (PV) of 3.10%, reactive strength index modified (RSImod) of 13.8%, and peak propulsive power (PPP) of 6.00% (p

The recent and rapid developments in track spike innovation have been followed by a wave of record-breaking times and top performances. This has led many to question what role "super spikes" play in improving running performance. To date, the specific contributions of new innovations in footwear, including lightweight, resilient, and compliant midsole foam, altered geometry, and increased longitudinal bending stiffness, to track running performance are unknown. Based on current literature, we speculate about what advantages these features provide. Importantly, the effects of super spikes will vary based on several factors including the event (e.g., 100 m vs. 10,000 m) and the characteristics of the athlete wearing them. Further confounding our understanding of super spikes is the difficulty of testing them. Unlike marathon shoes, testing track spikes comes with a unique challenge of quantifying the metabolic energy demands of middle-distance running events, which are partly anaerobic. Quantifying the exact benefits from super spikes is difficult and we may need to rely on comparison of track performances pre- and post- the introduction of super spikes.

Objectives: The COVID-19 crisis also affected elite sport severely, as elite athletes either stopped or drastically reduced their training regimen due to the lack of competitions and the mandatory lockdown. The aim of this study was to test whether heart rate variability was a reliable index of training load, which was dramatically altered due to the mandatory lockdown that occurred as a consequence of the COVID-19. Equipment and methods: Training (volume and intensity) and heart rate variability of sixteen professional male (n=8; body mass index = 22.2±2.0) and female cyclists (n=8; body mass index = 20.3±1.1) before (4 weeks), during (7 weeks), and after (4 weeks) the mandatory lockdown in Spain were monitored. Results: Individual analyses showed that the mandatory lockdown caused reliable reductions in training volume in 13 subjects (-96 to -7 % reductions in minutes), that were followed by an increase after the lockdown in all subjects (5 to 270%). In contrast, changes in training load were not homogenous across individuals. Moreover, such changes were not matched by comparable variations in heart rate variability. A mixed model of the heart rate variability as a function of training volume and intensity revealed no significant modulation by these two variables, and subject specific effects on the slope. In this study, we did not find evidence of association between heart rate variability and training load and/or intensity as many previous reports have suggested, even if training conditions changed dramatically overnight.

Fitting an FFM via NLS in practice assumes that a unique optimal solution exists and can be found by the algorithm applied. However, this idealistic scenario may not hold for two reasons: 1) the absolute minimum may not be unique; and 2) local minima, saddle points, and/or plateau features may exist that cause problems for certain algorithms. If there exist different parameter sets in the domain that share the same global minimum under standard NLS, then there is a situation where parameters aren’t uniquely identified without additional constraints or regularisation terms. However, more likely is that problems with the typical FFM fitting process will stem from the existence of local minima, saddles, or plateau features that cause the algorithm to converge to a solution not equal to the global minimum. Local optima can provoke sensitivities in the fitting process for first and second-order algorithms that are by definition local optimisers. This manifests as sensitivity to initial parameter estimates (i.e., the starting point the algorithm initialises the search from). The extent of starting point sensitivity is largely unknown in the context of FFMs for common algorithms adopted and has not been studied directly. Given this concern, research reporting a single model solution derived from ‘one shot’ minimisation of NLS via typical first and second-order algorithms is fundamentally limited by possible uncertainty as to the suitability of fitted estimates as global minimisers. Therefore, the primary aim of this study was to investigate the sensitivity of a classical first-order search algorithm to selection of initial estimates when fitting a fitness-fatigue model (FFM) via nonlinear least-squares (NLS), and to subsequently assess the existence of local optima. A secondary aim of this study was to examine the implications of any findings in relation to previous research and provide considerations for future experimentation. The aims of the study were addressed through a computer experiment (in silico) approach that adopted a deterministic assumption the FFM completely specified athlete response. Under this assumption, two FFMs (standard, and fitness-delay) were simulated under a set of hypothetical model inputs and manually selected ‘true’ parameter values (for each FFM), generating a set of synthetic performance data. The two FFMs were refitted to the synthetic performance data without noise (and under the same model inputs) by the quasi-Newton L-BFGS-B algorithm in a repetitive fashion initiated from multiple starting points in the parameter space, attempting to at each search recover the true parameter values. Estimates obtained from this process were then further transformed into prediction errors quantifying in-sample model fit across the iterations and non-true solutions. Within the standard model scenarios, 69.1-70.3% of solutions found were the true parameters. In contrast, within the fitness-delay model scenarios, 17.6-17.9% of solutions found were the true parameters. A large number of unique non-true solutions were found for both the standard model (N=275-353) and the fitness-delay model (N=383-550) in this idealistic environment. Many of the non-true extrema found by the algorithm were local minima or saddles. Strong in-sample model fit was also observed across non-true solutions for both models. Collectively, these results indicate the typical NLS approach to fitting FFMs is harder for a hill-climbing algorithm to solve than previously recognised in the literature, particularly for models of higher complexity. The findings of this study add weight to the hypothesis that there exists substantial doubt in reported estimates across prior literature where local optimisers have been used or models more complex than the standard FFM applied, particularly when optimisation procedures reported have lacked the relevant detail to indicate that these issues have been considered. Future research should consider the use of global optimisation algorithms, hybrid approaches, or different perspectives (e.g., Bayesian optimisation).

Purpose: compare linear and curvilinear models to describe the force-velocity relationship, especially on the velocity end, in lower limb acyclic extensions. Methods: nine athletes performed horizontal lower limb extensions on a leg press ergometer allowing to set from very high to very low (i.e. horizontal assisted extensions) resistive and inertial conditions. Lower limb force and velocity were continuously measured over the push-off in six resistive conditions to determine individual force-velocity relationships. Goodness of fit (GoF) of the linear model on force and velocity data (using the basic first order polynomial function), was compared to that of curvilinear models (using the basic second order polynomial function, Fenn and Marsh’s, and Hill’s equations) based on the Akaike Information Criterion (AIC). Results: When expressed relative to the theoretical maximal force (F0-L) and velocity (v0) obtained from the linear model, force and velocity data ranged from 26.6±6.6 to 96.0±3.6%F0-L and from 8.3±1.9 to 76.6±7.0%v0-L (range of individual values=5-86%v0-L and 16-99%F0-L). Curvilinear and linear models showed very high GoF (r2=0.951-0.999; SEE=17-159N). Despite higher GoF for curvilinear models, AIC showed that the linear model presented ~99-100 % chance to be the best one to describe the force-velocity relationship. Conclusion: the force-velocity relationship in acyclic lower limb extensions can be considered as linear from its force (from 5%v0-L) to its velocity end (up to 86%v0-L). Assisted horizontal acyclic lower limb extensions allowed achievement of movement velocities very close to v0, representing an interesting modality for training or testing force production capabilities at high velocities, notably for weaker populations.

Athlete external load is typically quantified as volumes or discretised threshold values using distance, speed and time. A framework that accounts for the movement sequences of athletes has previously been proposed using radio frequency data. This study developed a framework to identify sequential movement sequences using GPS-derived spatiotemporal data in team-sports and establish it’s stability. 13 rugby league players during one match were analysed to demonstrate the application of the framework. The framework (Sequential Movement Pattern-mining [SMP]) applies analysis techniques to handle i) geospatial data (i.e., decimal degree latitude and longitude), ii) determined players turning angles, iii) improved movement descriptor assignment thus, improving movement unit formation and iv) improved the classification and identification of players frequent SMP. The SMP framework allows for sub-sequences of movement units to be condensed, removing repeated elements, which offers a novel technique for the quantification of similarities or dissimilarities between players and playing positions. The SMP framework provides a robust and stable method which allows, for the first time the analysis of GPS-derived data and identifies the frequent SMP of field-based team-sport athletes. The application of the SMP framework in practice could optimise the outcomes of training of field-based team-sport athletes by improving training specificity.

INTRODUCTION The nationwide implementation of physical performance test batteries for youth squad players can be valuable for compiling individual physical performance profiles based on age- and gender-specific norm values. This approach is frequently used for optimizing training prescription and thus athletic development. The aim of this study was to introduce a distribution-based approach to derive an effect size scale for assessing athletic development from normative testing data in youth players, which can then be translated to setting performance goals for athletic development.METHODS Secondary analysis of norm values (mixed longitudinal and cross-sectional data [1]). In the age-groups under 12 to under 17, a maximum number of 1,172 and 846 tests were available for male and female basketball squad players, respectively. Biannual testing was conducted as part of a federal research project (20-m sprint, 20-m change of direction sprints with/without basketball, jump & reach, standing long jump, chest pass, mid-range jump shot, multistage fitness test). An effect size scale was derived from norm values which were available as quintile scores (five categories). Trivial changes were defined as the age-related mean annual performance development which was estimated as the average age-group-to-age-group change for the quintiles. Threshold values for small, medium, and large changes were calculated as average changes that were required to increase performance classification by one, two or three categories, respectively. These thresholds were additionally compared to the default effect size scale commonly used for interpreting standardized mean differences (between-player standard deviation: small 0.2, medium 0.6, large 1.2 [2]).RESULTS For example, the age-related mean annual development in the jump & reach for male players was 4 cm (trivial change). To reach one, two or three higher performance categories, jump height must improve by 8, 12 and 15 cm, respectively (i.e., small, medium, large). Compared with the default standardized effect size scale, these quintile-based thresholds were larger.CONCLUSION The quintile-based analysis presents a simple and practical approach to derive effect size thresholds based on norm values created from regular physical performance testing. These effect size scales can be easily visualized and communicated to players and coaches, as they are typically familiar with percentile-based performance classification of testing data. A limitation of this study was that only norm values in the form of quintile scores were used for analysis. Future research should attempt to model longitudinal datasets while accountingfor within- and between-player effects. Furthermore, the choice of appropriate and realistic percentilebased thresholds clearly remains up for debate and requires adequate analysis of original longitudinal data.REFERENCES 1. Stadtmann (2012) PhD thesis, Ruhr University Bochum. 2. Hopkins et al. (2009) MSSE,41,3-12.

PURPOSE: The COVID-19 crisis also affected elite sport severely, as elite athletes either stopped or drastically reduced their training regimen due to the lack of competitions and the mandatory lockdown. The aim of this study was to test whether heart rate variability was a reliable index of training load, which was dramatically altered due to the mandatory lockdown that occurred as a consequence of the COVID-19. METHODS: Training (volume and intensity) and heart rate variability of sixteen professional male (n = 8; body mass index = 22.2 ± 2.0) and female cyclists (n = 8; body mass index = 20.3 ± 1.1) before (4 weeks), during (7 weeks), and after (4 weeks) the mandatory lockdown were monitored. RESULTS: Individual analyses showed that the mandatory lockdown caused reliable reductions in training volume in 13 subjects (-96 to -7 % reductions in minutes), that were followed by an increase after the lockdown in all subjects (5 to 270%). In contrast, changes in training intensity were not homogenous across individuals. Crucially, changes in heart rate variability neither follow training load nor intensity at the individual level. CONCLUSIONS: Heart rate variability did not seem to be a reliable proxy of training load and/or intensity as many previous reports have suggested, even if training conditions changed dramatically overnight.

Purpose: Use ball-by-ball data from the Indian Premier League cricket tournament and machine learning techniques to predict match outcomes based on events occurring in the first inning of a match.Approach: Twelve predictor variables were entered into machine learning models (forward stepwise logistic regression using Akaike’s Information Criterion (AIC); forward stepwise logistic regression using Bayesian Information Criterion (BIC); random forests; naïve Bayes classifier), with match outcome as the dependent variable. Findings: The AIC model reported the highest accuracy in both the training and test datasets (69.92% and 67.18%, respectively). This model contains total runs scored, winning the coin toss, and home-ground advantage as positive predictors, and number of balls with no runs scored and number of balls with one run scored as negative predictors. All four models found that total runs scored in an inning was the most important predictor of match outcome, and no model included number of wickets lost as a predictor, although there could be an indirect effect through total runs scored. Originality: This study is novel in that it used both pre-match variables (home-ground) advantage and real-time measures (e.g., how many runs were scored in the powerplay) in a machine learning context to classify match results. The results can be used to adapt in-game tactics to maximize advantages of batsmen in favorable contexts.

This study aimed to verify the effects of congested fixture and matches’ participation on internal and external workload indexes in professional Brazilian soccer players. Rate of perceived exertion-based training load (sRPE), distance- and accelerometry-based measures were daily monitored over 119 training sessions and 33 matches performed by 29 male outfield players. Weeks were classified as congested (n=11, two or more matches within a 7-day period) and regular (n=10, one match or less within a 7-day period). The players were divided based on the matches’ participation: (i) players who played ≥ 60 minutes (G1); (ii) players who played < 60 minutes (G2); (iii) players who did not participated of the match (G3). The findings showed that independent of the levels of participation during the matches, regular weeks presented greater acute, monotony, and strain indices for internal and external workload measures than congested weeks. The G1 presented the highest values for the most of the workload indices in both regular and congested weeks, with the exception of monotony indices (internal and external load) that G2 showed greater values than G1 and G3. Coaches and practitioners should plan the training “doses” to reduce disparities of these different match’s participation and congested schedule weeks.

This study aimed to compare the match running performance between bottom- and top-ranked teams in professional soccer players. In addition, this study verified the independent and interactive effects of playing position and contextual factors on running outputs between these teams. Forty-eight professional male outfield soccer players participated in this study (top-ranked team, n=24; bottom-ranked team, n=24). The distance- and accelerometry-based measures were recorded during 69 matches using a global position system (10 Hz) integrated with an accelerometer (400 Hz). The top-ranked team covered greater total distance and high-acceleration than the bottom-ranked team in home and away matches, mainly for external defenders and midfielders (p < 0.05, effect size [ES]=moderate). The matches against top-level opponents required high values of running outputs only for the top-ranked team (p < 0.05, ES=small). In general, the match outcome (loss vs. draw vs. win) was not influenced by running performance for both bottom- and top-ranked teams (p > 0.05; ES=small), with exception for Player Load (bottom-ranked team: win > draw = loss; p < 0.05, ES=small). These findings should be taken into account when the coaches and practitioners interpret the match running outputs and when evaluating the effects of training intervention on these performance indicators.

Background. Stress fractures are injuries caused by repetitive loading during activities such as running. The application of advanced analytical methods such as machine learning to data from multiple wearable sensors has allowed for predictions of biomechanical variables associated with running-related injuries like stress fractures. However, it is unclear if data from a single wearable sensor can accurately estimate variables that characterize external loading during running such as peak vertical ground reaction force (vGRF), vertical impulse, and ground contact time. Predicting these biomechanical variables with a single wearable sensor could allow researchers, clinicians, and coaches to longitudinally monitor biomechanical running-related injury risk factors without expensive force-measuring equipment.Purpose. We quantified the accuracy of applying quantile regression forest (QRF) and linear regression (LR) models to sacral-mounted accelerometer data to predict peak vGRF, vertical impulse, and ground contact time across a range of running speeds.Methods. Thirty-seven collegiate cross country runners (24 females, 13 males) ran on a force-measuring treadmill at 3.8 – 5.4 m/s while wearing an accelerometer clipped posteriorly to the waistband of their running shorts. We cross-validated QRF and LR models by training them on acceleration data, running speed, step frequency, and body mass as predictor variables. Trained models were then used to predict peak vGRF, vertical impulse, and contact time. We compared predicted values to those calculated from a force-measuring treadmill on a subset of data (n = 9) withheld during model training. We quantified prediction accuracy by calculating the root mean square error (RMSE) and mean absolute percentage error (MAPE).Results. The QRF model predicted peak vGRF with a RMSE of 0.150 body weights (BW) and MAPE ± SD of 4.27 ± 2.85%, predicted vertical impulse with a RMSE of 0.004 BW*s and MAPE of 0.80 ± 0.91%, and predicted contact time with a RMSE of 0.011 s and MAPE of 4.68 ± 3.00%. The LR model predicted peak vGRF with a RMSE of 0.139 BW and MAPE of 4.04 ± 2.57%, predicted vertical impulse with a RMSE of 0.002 BW*s and MAPE of 0.50 ± 0.42%, and predicted contact time with a RMSE of 0.008 s and MAPE of 3.50 ± 2.27%. There were no statistically significant differences between QRF and LR model prediction MAPE for peak vGRF (p = 0.549) or vertical impulse (p = 0.073), but the LR model’s MAPE for contact time was significantly lower than the QRF model’s MAPE (p = 0.0497).Conclusions. Our findings indicate that the QRF and LR models can accurately predict peak vGRF, vertical impulse, and contact time (MAPE < 5%) from a single sacral-mounted accelerometer across a range of running speeds. These findings may be beneficial for researchers, clinicians, or coaches seeking to monitor running-related injury risk factors without force-measuring equipment.

Recent shifts in professional basketball have led teams to place more urgency in drafting as well as possible. Draft picks must play out their initial years under team-friendly contracts that provide teams with increased salary cap flexibility. Yet, while this urgency has led to widespread discussion and research of how to improve teams' draft decisions, little attention has been given to identifying what teams can do to maximize the performance and potential of their draft picks once they are added to their roster. However, theories of learning and ecological psychology suggest that giving young players as much playing time as possible should lead to concrete improvements in their development and future performance. In this study, I test this causal theory by evaluating the relationship between the minutes a player receives in their first two seasons in the NBA and their fourth-year performance using a novel method of propensity score weighting that enables weighting for continuous treatment variables. I find that players who receive more minutes in their first two seasons have better fourth seasons and make larger jumps from their first two seasons to their fourth season, controlling for a broad set of potential confounders. These results have important implications for teams as they develop organizational strategies for the short- and medium-term.

The standard fitness-fatigue model (FFM) is known to include several limitations described by the linearity assumption, the independence assumption, and the deterministic assumption. These limitations ensure that the modelled response to chronic training does not match the complexity observed in practice. The purpose of part II of this review series was to describe previous extensions to the standard FFM to address these limitations, providing key mathematical insights and resources to both explain technical elements and enable researchers and practitioners to fit these extended models to their own data. To address the linearity assumption of the standard FFM and the associated limitation that doubling the training load predicts twice the performance improvement, two distinct extensions are reviewed including the addition of a non-linear transform to training inputs and inclusion of non-linear terms within the system of differential equations. To address the independence assumption where the response to a training session is unaffected by previous sessions, a popular extension where fatigue is updated as an exponentially weighted moving average of previous training loads is reviewed. Finally, the review introduces the concept of state-space models where uncertainty in the estimates of fitness, fatigue and performance measurement can be directly modelled eliminating the unsuited deterministic assumption of the standard FFM. The review also highlights how state-space models can be further expanded to include features such as the Kalman filter where parameter estimates can be updated with incoming performance measurements to better predict and manipulate training to optimise performance. Collectively, the range of topics covered in this review series and the resources provided should enable researchers and practitioners to better investigate the extensive area of FFMs and determine in what contexts models can assist with training monitoring and prescription.

Purpose: To determine the independent effect of the curved carbon-fiber plate in the Nike Vaporfly 4% shoe on running economy and running biomechanics. Methods: Fifteen healthy male runners completed a metabolic protocol and a biomechanics protocol. In both protocols participants wore 2 different shoes, an intact Nike Vaporfly 4% (VFintact) and a cut Nike Vaporfly 4% (VFcut). The VFcut had 6 medio-lateral cuts through the carbon-fiber plate in the forefoot to reduce the effectiveness of the plate. In the metabolic protocol, participants ran at 14 km/h for 5 min, twice with each shoe, on a force-measuring treadmill while we measured metabolic rate. In the biomechanics protocol, participants ran across a runway with embedded force plates at 14 km/h. We calculated running economy, kinetics, and lower limb joint mechanics. Results: Running economy did not significantly differ between shoe conditions (on average, 0.55% § 1.77% (mean § SD)) worse in the VFcut compared to the VFintact; 95% confidence interval: (-1.44% to 0.40%)). Biomechanical differences were only found in the metatarsophalangeal (MTP) joint with increased MTP dorsiflexion angle, angular velocity, and negative power in the VFcut. Contact time was 1% longer in the VFintact. Conclusion: Cutting the carbon-fiber plate and reducing the longitudinal bending stiffness did not have a significant effect on the energy savings in the Nike Vaporfly 4%. This suggests that the plate’s stiffening effect on the MTP joint plays a limited role in the reported energy savings, and instead savings are likely from a combination and interaction of the foam, geometry, and plate.

Introduction: The issue of integrating transgender athletes into sport is becoming more prominent with the rising numbers of those identifying as transgender in society. Whether it is fair for transgender athletes to be included in their affirmed gender category across all levels of sport from grassroots to elite is the crux of the debate. Previous studies have shown muscle mass loss in transwomen and muscle mass and strength gain in transmen after 1 year of gender-affirming treatment (GAT). Wiik et al., 2020 found that transmen retain a strength disadvantage over cisgender men and transwomen retain muscle mass and strength advantages over cisgender women after 1 year of GAT. Roberts et al., 2020 also found that running performance in transwomen was maintained but not baseline muscular strength. However, very little data on sports performance measures outside muscular strength and running times exist, nor has any of the previous data been compared with a comparative control group. Aim: To investigate the effect of “muscle memory” in transgender athletes and investigate changes in physiology after 2 years of GAT such as bone mineral density, lean muscle mass, and fat mass, coupled with sports performance measures in transwomen and transmen athletes and compare them with a cisgender female athletic cohort. This will elucidate what advantages/disadvantages transgender athletes gain/retain after 2 years of GAT over their cisgender counterparts and this will better inform policymakers who control their integration into their affirmed gender category in sport.

The aim of this study was to investigate the effects of goal-related statistics on match outcome during the Intercontinental Beach Soccer Cup Dubai 2019. The offensive sequences that resulted in goal was analyzed in all 20 matches during the competition (n=138 goals). A set of 35 goal-related statistics were grouped in nine macro-categories: Match-period, Court-zone, Set-play, Open-play, Touches by players before goal, Offensive method, Goalkeeper-line, Number of passes before goal, Ball trajectory. Match outcome in regular time was considered the matches resulting in a loss (n=16), draw (n=8) or win (n=16). The most goals were scored in Open-play (69%), during the 2nd and 3rd periods (36% for each), near to goal (Zone 4; 50%), preceded by 1-touch (67%) and 0-pass (29%), using positional attack (46%), without goalkeeper-line (68%), and with high-ball trajectory (51%). The results of the discriminant function analysis shows the following order of importance to discriminate match outcome, with advantage for winning teams: 4v4 goal-successful (F-Ratio = 12.022), Zone 4, 1-touch, 3rd period, High-ball, Counterattack, Zone 2, Sand-touch (F-Ratio = 4.838). Winning teams scored their goals mainly in open-play situations and without goalkeeper-line, using counterattack to achieve zones near the opponent’s goals, implementing a direct offensive style. Also, goals scored were usually preceded by 1-touch, both through high-ball and sand-touch ball trajectory.

Objectives: To determine the independent effect of the curved carbon-fiber plate in the Nike Vaporfly 4% shoe on running economy and running biomechanics.Methods: Fifteen healthy male runners completed a metabolic protocol and a biomechanics protocol. In both protocols participants wore two different shoe conditions, an intact Nike Vaporfly 4% (VFintact), and a cut Nike Vaporfly 4% (VFcut). The VFcut had 6 medio-lateral cuts through the carbon-fiber plate in the forefoot to reduce the effectiveness of the plate. In the metabolic protocol participants ran at 14 km/h for 5-minutes, twice with each shoe, on a force-measuring treadmill while breathing into an expired gas system. In the biomechanics protocol participants ran across a runway with embedded force plates at 14 km/h. We calculated running economy, kinetics, and joint mechanics of the lower limb.Results: Running economy did not significantly differ between shoe conditions (0.5% higher in the VFcut compared to the VFintact). Biomechanical differences were only found in the metatarsophalangeal joint (MTP) with increased MTP dorsiflexion angle, angular velocity, and negative power in the VFcut. Contact time was 1% longer in the VFcut.Conclusion: Cutting the carbon-fiber plate and reducing the longitudinal bending stiffness did not have a significant effect on the energy savings in the Nike Vaporfly 4%. This suggests that the plate alone plays a limited role in the 4% energy savings, and instead those likely result from a combination and interaction of the foam, geometry, and plate.

Assessing football players’ sprint mechanical outputs is key to the performance management process (e.g. talent identification, training, monitoring, return-to-sport). This is possible using linear sprint testing to derive force-velocity-power outputs (in laboratory or field settings), but (i) testing requires specific efforts and (ii) the movement assessed is not specific to the football playing tasks. This proof-of-concept short communication presents a method to derive the players’ individual acceleration-speed (AS) profile in-situ, i.e. from global positioning system data collected over several football sessions (without running specific tests). Briefly, raw speed data collected in 16 professional male football players over several training sessions were plotted, and for each 0.2 m/s increment in speed from 3 m/s up to the individual top-speed reached, maximal acceleration output was retained to generate a linear AS profile. Results showed highly linear AS profiles for all players (all R2>0.984) which allowed to extrapolate the theoretical maximal speed and accelerations as the individual’s sprint maximal capacities. Good reliability was observed between AS profiles determined 2 weeks apart for the players tested, and further research should focus on deepening our understanding of these methodological features. Despite the need for further explorations (e.g. comparison with conceptually close force-velocity assessments that require, isolated and not football-specific linear sprint tests), this in-situ approach is promising and allows direct assessment of team sport players within their specific acceleration-speed tasks. This opens several perspectives in the performance and injury prevention fields, in football and other team sports, and the possibility to “test players without testing them”.

This systematic review is a student assignment during my MSc in Human Movement Science. In this systematic review, I collected secondary data, I appraised research studies and synthesized findings quantitatively in order to find out which GPS variables can predict non-contact injuries in soccer players.

Rugby sevens is a demanding sport that requires extensive physical preparation. Travel and logistical challenges in rugby sevens mean that coaches often have limited contact time with players, but must ensure adequate physical, technical and tactical preparation. Tactical periodisation (TP) presents a potential solution by simultaneously developing these aspects of performance, but this concept has not been empirically tested. To investigate the effectiveness of TP, microtechnology devices were used to measure total distance, high-speed distance, maximum velocity, mean acceleration, PlayerLoad and collisions in a group of international sevens rugby players (n=22) during four tournaments and two training camps. Differences in the mean and peak demands of matches and training session types (volume, quality, speed, collision) were determined using linear mixed models and effect sizes (ES) with 95% confidence intervals. Volume and quality training types simulated mean and peak match demands effectively with only PlayerLoad demonstrating a practically important reduction from match exertion (match vs. quality ES = -0.97, 95%CI -1.17 to -0.77). Speed training exceeded the peak high-speed running demands of matches over durations from 1 to 5 minutes (ES range 1.78 to 2.54). These results demonstrate that training guided by tactical periodization principles represents an effective method of preparation during the competition period.

Most competitive and recreational road cyclists use stiff-soled shoes designed for cycling and “clipless” pedals that firmly attach to the shoes. There are many unsubstantiated claims by cyclists and industry professionals about the advantages of cycling shoes and clipless pedals. Scientific research has shown that cycling shoes and clipless pedals have no significant effects on the metabolic cost of cycling during submaximal, steady-state efforts. However, a recent study demonstrated that, compared to running shoes, cycling shoes and clipless pedals do provide performance benefits relevant to sprint cycling. Here, we investigated if there was a positive relationship between longitudinal bending stiffness of cycling shoe soles and sprint performance. We measured the mechanical power outputs, velocities, and cadences of 19 healthy male recreational/competitive cyclists during maximal sprint cycling. Participants rode outdoors on a paved asphalt road with a steady, uphill grade of 4.9%. Each subject completed nine 50 m cycling sprints in three (single-blinded) shoe conditions: identical shoe uppers with injection moulded nylon soles, carbon fibre-fibreglass blend soles, and full carbon fibre soles. The same clipless pedals were used throughout all tests. No significant differences were detected between the three shoe soles for: 50 m average and peak 1-second power, average change and peak change in velocity, average and peak cadence, maximal sprint velocity, peak acceleration, and peak crank torque (all p > 0.31). Greater longitudinal bending stiffness of cycling shoe soles had no effect on sprint performance during short uphill sprints.

Context: The physiological determinants of ultramarathon success have rarely been assessed and likely differ in their contributions to performance as race distance increases. Purpose: To examine predictors of performance in athletes who completed either a 50-, 80-, or 160-km trail race over a 20-km loop course on the same day. Methods: Measures of running history, aerobic fitness, running economy, body mass loss, hematocrit alterations, age, and cardiovascular health were examined in relation to race-day performance. Performance was defined as the percentage difference from the winning time at a given race distance, with 0% representing the fastest possible time. Results: In the 50-km race, training volumes, cardiovascular health, aerobic fitness, and a greater loss of body mass during the race were all related to better performance (all P < .05). Using multiple linear regression, peak velocity achieved in the maximal oxygen uptake test (β = −11.7, P = .002) and baseline blood pressure (β = 3.1, P = .007) were the best performancepredictors for the men’s 50-km race (r = .98, r2 = .96, P < .001), while peak velocity achieved in the maximal oxygen uptake test (β = −13.6, P = .001) and loss of body mass (β = 12.8, P = .03) were the best predictors for women (r = .94, r2 = .87, P = .001). In the 80-km race, only peak velocity achieved in the maximal oxygen uptake test predicted performance (β =−20.3, r = .88, r2 = .78, P < .001). In the 160-km race, there were no significant performance determinants. Conclusions: While classic determinants of running performance, including cardiovascular health and running fitness, predict 50-km trail-running success, performance in longer-distance races appears to be less influenced by such physiological parameters.

Background. It has been proposed that muscle architecture can be associated with sprint performance and the risk of sustaining a muscle injury. During puberty, sprint performance as well as muscle injury risk increases in young soccer players. In this study, we investigated the changes in m. biceps femoris long head (BFlh) cross-sectional area (ACSA), fascicle length (FL) and pennation angle (PA) and sprint performance as well as their relationship in under 13 to 15 youth soccer players. Methods. In total, we measured 85 youth soccer players in under 13 (n=29, age=12.5 y (SD=0.1), height=155.3 cm (6.2), weight=43.9 kg (7.6)), under 14 (n=25, age=13.5 y (0.3), height=160.6 y (7.7), weight=47.0 kg (6.8)) and under 15 (n=31, age=14.4 y (0.3) , height=170.0 cm (7.7), weight=58.1 kg (8.8) ) teams of three high level soccer clubs. We used ultrasound to measure BFlh ACSA, FL and PA. We performed sprint tests to assess 10m and 30m sprint time, maximal velocity (vmax) and maximal acceleration (amax). We calculated Pearson’s r and 95% compatibility intervals to assess the relationship between sprint ability, maturity ratio, chronological age and architectural parameters. In addition, we calculated the best set of predictors for sprint ability using multiple regression models.Results. All muscle architectural parameters increased from the under 13 to the under 15 age group (BFlh ACSA: 37%, BFlh FL: 11%, BFlh PA: 8%). All sprint performance parameters improved from the under 13 to under 15 age categories (30m time: 7%, 10m time: 4%, vmax: 9%, amax: 7%). BFlh ACSA was correlated with 30m sprint time (r = -0.61 (95% CI = -0.73, -0.45)) and vmax (r= 0.61 (0.45, 0.72)). The correlation for maturity ratio with assessed parameters were larger compared to the correlation for chronological age. A combination of BFlh ACSA, FL, chronological age and height best predicted sprint parameters. Discussion. Parallel to improvements in sprint performance, muscle architectural parame-ters increase from the under 13 to under 15 age groups. BFlh ACSA seems to be related to sprint performance in youth soccer players. BFlh ACSA and chronological age are the main predictors of most sprint parameters.

Our study aimed to examine athletics, training characteristics, and prevalence of musculoskeletal symptoms of male junior tennis Davis Cup players (DC) in comparison with their regional counterparts, as well as to evaluate the impact of age and performance level on training characteristics. Twelve junior DC (male) and two samples of regional squad players (RS1 n = 60 males, n = 47 females; RS2 n = 59 males) participated in a physical testing, an interview for data evaluation on training characteristics, and a questionnaire survey of orthopedic injury frequency. Results indicate higher physical performance levels (effect size (ES) 0.75–1.26) and training volumes in DC (ES 1.23–1.66). In DC, significant relationships were found between total training volume and tennis ranking ( r = −0.78), age and physical training volume ( r = 0.82), and age and total training volume ( r = 0.62). Injury frequencies showed moderate to high prevalence with no differences ( p > 0.05) between DC and RS. Given the demands of elite tennis and the important role of service in the modern game, more efforts are necessary to develop training prescription for both performance enhancement and prevention strategies.

Purpose: This study described bicycling (C-classes, 1–5) and tricycling (T-classes, 1–2) performance in International Cycling Federation (Union Cycliste Internationale; UCI) road race events between 2011 and 2019. Methods: A total of 3,243 race results (bicycling = 2,571; tricycling = 672) from 33 UCI events held between May 2011 and August 2019 were included in the analysis. Mean race velocity was calculated for each race result. Bicycling and tricycling data were separately modelled using hierarchical regression. Cohen’s d was calculated for the standardised difference between adjacent classes. Results: Road race performance was statistically different between men’s classes C1/C2 (p

Given a set of sequences comprised of time-ordered events, sequential pattern mining is useful to identify frequent subsequences from different sequences or within the same sequence. However, in sport, these techniques cannot determine the importance of particular patterns of play to good or bad outcomes, which is often of greater interest to coaches and performance analysts. In this study, we apply a recently proposed supervised sequential pattern mining algorithm called safe pattern pruning (SPP) to 490 labelled event sequences representing passages of play from one rugby team’s matches in the 2018 Japan Top League season. We obtain patterns that are the most discriminative between scoring and non-scoring outcomes from both the team’s and opposition teams’ perspectives using SPP, and compare these with the most frequent patterns obtained with well-known unsupervised sequential pattern mining algorithms when applied to subsets of the original dataset, split on the label. From our obtained results, line breaks, successful line-outs, regained kicks in play, repeated phase-breakdown play, and failed exit plays by the opposition team were found to be the patterns that discriminated most between the team scoring and not scoring. Opposition team line breaks, errors made by the team, opposition team line-outs, and repeated phase-breakdown play by the opposition team were found to be the patterns that discriminated most between the opposition team scoring and not scoring. It was also found that, probably because of the supervised nature and pruning/safe-screening mechanisms of SPP, compared to the patterns obtained by the unsupervised methods, those obtained by SPP were more sophisticated in terms of containing a greater variety of events, and when interpreted, the SPP-obtained patterns would also be more useful for coaches and performance analysts.

The objective of this research was to determine if three alternative shoe upper closures improve biomechanical performance measures relative to a standard lace closure in court-based movements. NCAA Division 1 and club-level male athletes recruited from lacrosse, soccer, tennis, and rugby performed four court-based movements: Lateral Skater Jump repeats (LSJ), Countermovement Jump repeats (CMJ), Triangle Drop Step drill (TDS), and Anterior-Posterior drill (AP). Each athlete performed the movements in four shoe upper closures: Standard Closure, Lace Replacement, Y Wrap, and Tri Strap. Ground contact time, peak eccentric rate of force development (RFD), peak concentric GRF, peak concentric COM power, eccentric work, concentric work, and movement completion time were measured. Tri Strap saw improvements in four of seven biomechanical variables during CMJ and LSJ and one variable during TDS. Lace Replacement delivered improvements in one performance measure during CMJ, LSJ, and AP, and two variables in TDS. Y Wrap improved performance in three performance measures during LSJ and impaired performance in two measures during CMJ and three measures during AP. Tri Strap provided the most consistent performance improvements across all movements. This study allowed for the mechanical properties of the shoe lower to remain consistent across designs to examine if an alternative shoe upper closure could enhance performance. Our results indicate that increased proprioception and/or mechanical properties due to the alternative closures, especially Tri Strap, improves athlete performance, which concludes that the design of the shoe upper is an essential consideration in shoe design.

ObjectivesThis objective of this study was to evaluate whether combining existing methods of elastic net for zero-inflated Poisson and zero-inflated Poisson regression methods could improve real-life applicability of injury prediction models in football.MethodsPredictor selection and model development was conducted on a pre-existing dataset of 24 male participants from a single English football team’s 2015/2016 season.ResultsThe elastic net for zero-inflated Poisson penalty method was successful in shrinking the total number of predictors in the presence of high levels of multicollinearity. It was additionally identified that easily measurable data, that is, mass and body fat content, training type, duration and surface, fitness levels, normalised period of ‘no-play’ and time in competition could contribute to the probability of acquiring a time-loss injury. Furthermore, prolonged series of match-play and increased in-season injury reduced the probability of not sustaining an injury.ConclusionFor predictor selection, the elastic net for zero-inflated Poisson penalised method in combination with the use of ZIP regression modelling for predicting time-loss injuries have been identified appropriate methods for improving real-life applicability of injury prediction models. These methods are more appropriate for datasets subject to multicollinearity, smaller sample sizes and zero-inflation known to affect the performance of traditional statistical methods. Further validation work is now required.

Free kicks are an important goal scoring opportunity in football. It is an unwritten rule that the goalkeeper places a wall of defending players with the aim of making scoring harder for the attacking team. However, the defensive wall can occlude the movements of the kicker, as well as the initial part of the ball trajectory. Research on one-handed catching suggests that a ball coming into view later will likely delay movement initiation and possibly affect performance. Here, we used virtual reality to investigate the effect of the visual occlusion of the initial ball trajectory by the wall on the performance of naïve participants and skilled goalkeepers. We showed that movements were initiated significantly later when the wall was present, but not by the same amount as the duration of occlusion (~200ms, versus a movement delay of ~70-90ms); movements were thus initiated sooner after the ball came into view, based on less accumulated information. For both naïve participants and skilled goalkeepers this delayed initiation significantly affected performance (i.e., 3.6cm and 1.5cm larger spatial hand error, respectively, not differing significantly between the groups). These performance reductions were significantly larger for shorter flight times, reaching increased spatial errors of 4.5cm and 2.8cm for both groups, respectively. Further analyses showed that the wall-induced performance reduction did not differ significantly between free kicks with and without sideward curve. The wall influenced early movement biases, but only for free kicks with curve in the same direction as the required movement; these biases were away from the final ball position, thus hampering performance. Our results cannot suggest an all-out removal of the wall–this study only considered one potential downside–but should motivate goalkeepers to continuously evaluate whether placing a wall is their best option. This seems most pertinent when facing expert free kick takers for whom the wall does not act as a block (i.e., whose kicks consistently scale the wall).

Changing rules to promote scoring through more ‘high-risk’ play has become common in team sports. Australia’s national netball league (i.e. Suncorp Super Netball) has recently taken this approach–introducing a two-point shooting rule. Teams will be awarded two-points for shots made from an ‘outer circle’ 3.0m-4.9m from the goal in the final five minutes of quarters. We sought to answer a series of questions regarding the implementation and potential strategies surrounding the two-point rule in Suncorp Super Netball. We used video coded data from the 2018 Suncorp Super Netball season to identify the total number of made and missed shots from different distances across the season. We also used shooting statistics from recent Fast5 Netball World Series (a competition with a two-point shooting rule already in place) as a comparator. The reward of two-points is relatively well-aligned to the relative risk of missing shots from the proposed outer versus inner circle (2.22 [1.98, 2.48 95% CIs]) based on existing shooting data from Suncorp Super Netball teams. We found that the relative risk of missing shots from ‘long-’ (i.e. 3.5m-4.0m) versus ‘mid-range’ (i.e. 3.0–3.5m) was only slightly elevated (1.52 [1.21, 1.86 95% CIs])–suggesting teams should favour long- over mid-range shots when the two-point shot is available. Based on the typical number of shots a team receives in a five-minute period, we found that teams may be able to score ~3.51 extra points per quarter when taking all versus no-shots from the two-point outer circle. Analysis of the Fast5 versus Suncorp Super Netball data did, however, reveal that shooting accuracy from long-range may decrease when a two-point shot is available. Teams may need to consider situational factors (e.g. altered opposition defensive strategies) when developing their shooting strategy for taking advantage of the two-point shot.

Performance analysis is a well-established discipline in sports science, supported by decades of research. Comparatively, performance analysis in electronic sports (esports) is limited. Therefore, there is opportunity to accelerate performance outcomes in esports by applying methods grounded in sports science. The current study adopted a coach-centred approach to model performance at the 2018 League of Legends World Championship. Three expert coaches rated the proposed relationship between 43 variables and match outcomes in professional League of Legends competition using a Likert scale (1-10). The Likert scale was anchored with ‘no relationship’ at 1 and ‘very strong relationship’ at 10. The coaches’ median ratings were calculated for each variable. Variables with a median score ≥6 were retained for analyses. A total of 14 variables were collected from the 2018 League of Legends World Championship (n=119) matches via video annotations and match histories. Generalized Linear Mixed Effects Models with binomial logit link function were implemented with respect to the Blue Side winning or losing the match, and individual teams were specified as random effects. Variables were screened for multicollinearity before a step-up approach was utilised. The best model of performance included Tower Percentage (p=0.006) and Number of Inhibitors (p=0.029). This model achieved a classification accuracy of 95.8%. While Tower Percentage and Number of Inhibitors contributed to winning or losing, further research is required to determine effective strategies to improve these variables, to understand the relevance of these variables across the complete time-series of the match, and to determine whether performance indicators remain stable across game updates.

Eliud Kipchoge is scheduled to attempt to run a marathon in 1:59:59 or faster on October 12, 2019. We used publicly available data to determine the undulations in elevation and the radii of the curves on the course. With previously developed equations for the effects of velocity, slope, and curvature on oxygen uptake, we performed simulations to quantify how much the elevation changes and curves of the Vienna course should affect oxygen uptake (at a fixed velocity) or velocity (at a fixed oxygen uptake). We estimate that, beyond a benefit from the downhill in the first 1km of the course, oxygen uptake rates will fluctuate by no more than 2% of the oxygen uptake rates on a flat, straight course for km 1 to 42, leading to an overall increase in oxygen uptake of only 0.11%. Together, we estimate that the undulations and curves of the Vienna course incur a penalty of less than 5 s compared to a perfectly level and straight course. We do not have sufficient data to include aerodynamic drafting in our simulations but the course itself appears to be very well-chosen to minimize the negative effects of elevation changes and curves.

Performance analysis in sports objectively captures aspects of athlete performances to inform coaching. Comparatively, esports is an emerging expertise domain with limited performance analysis research, however, no research has yet investigated the quality of available data. Therefore, this research aimed to: 1) assess the validity of publicly accessible Match History statistics from professional League of Legends matches; 2) assess the agreement of notational analysis between three experienced players; and 3) assess the agreement between a novice and Match Histories. 30 professional matches were randomly selected from the North American and European 2019 seasons. The Match Histories for each match were copied from the publicly accessible repository, while each of the authors independently viewed videos on the public Video On Demand repository, and encoded action variables corresponding to the Match Histories. Data were compared 1) between the most experienced player and Match Histories; 2) between the three experienced authors; and 3) between the novice author and Match Histories. Krippendorff’s Alpha was calculated with acceptable agreement set at α ≥ 0.8. The most experienced player was in good agreement with Match Histories (α=0.868-1.000), while the novice rater was in good agreement except for First Tower Time (α=0.764) and First Inhibitor Team (0.740). The three experienced players were in good agreement (α=0.861-1.000). Match Histories and experienced player annotations can be used interchangeably for all observed measures to facilitate performance analysis in professional League of Legends. A novice can be used to capture some basic statistics, while other measures require domain expertise.

This study analyzed whether the Beta-Alanine (BA) supplementation improves performance and oxidative stress indices during the tapering period. We assessed eleven volleyball athletes over 8-week. The performance was evaluated through the countermovement jump (CMJ). We evaluated Internal Training Load (ITL), questionnaires (Wisconsin Upper Respiratory Symp-tom Survey 21 – WURSS 21) and oxidative stress (Thiobarbituric acid reactive substances - TBARS, uric acid and nitrite). Athletes supplemented with BA or dextrose (PL) at doses of 6.4 g/day. Beta-alanine (BA) supplementation does not modulate the performance (CMJ). Along the treatment period, the internal load of the PL group remained higher than the BA group (P=0.011). The uric acid and nitrite were neither modulated by training nor treatment. Howev-er, the TBARS was lower at post moment than pre, without difference between groups. Thus, BA supplementation neither increased the performance nor decreased oxidative stress in vol-leyball athletes after a period of training intensification.

Objectives: to establish normative performance values for the modified Star Excursion Balance Test and derived Limb Symmetry Index scores in non-injured female adolescent footballers, and identity if there is a relationship between the aforementioned metrics and ageDesign: single measure study design Setting: A single football club’s female regional talent and development teams Participants: Thirty-four uninjured female footballers, aged between 13 to 18 years.Main Outcome Measures: Modified Star Excursion Balance Test and derived Limb Symmetry Index scores.Results: There were no statistically significant differences between dominant and non-dominant leg distance scores in any of the modified Star Excursion Balance Test specific reach direction or composite scores. Across all age groups, mean dominant leg total distance scores ranged from 231.5 cm to 250.4 cm whilst non-dominant total distance scores ranged from 234.3 cm to 253.3 cm. Mean Limb Symmetry Index values ranged from 97.8% to 100.5%. Age accounted for approximately 8% of the variance within dominant, non-dominant total distance and Limb Symmetry Index scores.Conclusions: Our study has established normative performance values for the mSEBT and derived LSI scores in non-injured female adolescent footballers. Age had a very limited ability in accounting for the variance observed for composite scores in dominant, non-dominant and LSI based scores.

Measuring the ground reaction forces (GRF) underlying sprint acceleration is important to understanding the performance of such a common task. Until recently direct measurements of GRF during sprinting were limited to a few steps per trial, but a simple method (SM) was developed to estimate GRF across an entire acceleration. The SM utilizes displacement- or velocity-time data and basic computations applied to the runner’s center of mass and was validated against compiled force plate (FP) measurements; however, this validation used multiple-trials to generate a single acceleration profile, and consequently fatigue and error may have introduced noise into the analyses. In this study, we replicated the original validation by comparing the main sprint kinetics and force-velocity-power variables (e.g. GRF and its horizontal and vertical components, mechanical power output, ratio of horizontal component to resultant GRF) between synchronized FP data from a single sprinting acceleration and SM data derived from running velocity measured with a 100 Hz laser. These analyses were made possible thanks to a newly developed 50-m FP system providing seamless GRF data during a single sprint acceleration. Sixteen trained male sprinters performed two all-out 60-m sprints. We observed good agreement between the two methods for kinetic variables (e.g. grand average bias of 4.71%, range 0.696 ± 0.540–8.26 ± 5.51%), and high inter-trial reliability (grand average standard error of measurement of 2.50% for FP and 2.36% for the SM). This replication study clearly shows that when implemented correctly, this method accurately estimates sprint acceleration kinetics.

Background: Soccer players are at high risk of stress injuries in the foot. While most research addresses this issue in professional athletes, there is little information concerning young athletes. Objective: As soccer is practiced around the world since early infancy, we set out to determine whether young soccer athletes are susceptible to increased foot loading that increase risk factors for foot injuries. Design: Case control study;Setting: LaboratoryParticipants: twenty-six male adolescents (mean age 16 years old) were organized into two groups: soccer players (n=13) and controls (n=13). Interventions: Participants completed a circuit of soccer relevant motor tasks while plantar pressure data were recorded with different footwear conditions. Additionally, foot sensitivity, ankle range of motion and Q-angle were determined for each group. Data were compared between the soccer and control groups within the different footwear conditions.Main Outcome Measures: Groups were compared regarding foot sensitivity, ankle range of motion, Q-angle, and plantar pressure determined during running and cutting movements performed at maximal speed and using different shoes. Results: Foot sensitivity, ankle range of motion and Q-angle did not differ between the groups. During performance of soccer actions, young players showed higher peak pressure in the lateral region of the foot including the fifth metatarsal. These higher peaks were minimized by manipulation of the footwear. Conclusion: In summary, young soccer athletes show dynamic plantar pressure patterns that are related to foot injury in the adult athlete, and this condition can be minimized by the manipulation of the footwear.

To test the hypothesis that cognitive load (low vs. high load) during a 20 min self-paced cycling exercise affects physical performance. Bayes analyses revealed extreme evidence for the 2-back task being more demanding than the 1-back task, both in terms of accuracy (BF10 = 4490) and reaction time (BF = 1316). The data only showed anecdotal evidence for the alternative hypothesis for the power output (BF10 = 1.52), moderate evidence for the null hypothesis for the heart rate (BF10 = 0.172), anecdotal evidence for RPE (BF10 = 0.72) and anecdotal evidence for mental fatigue (BF10 = 0.588). Our data seem to challenge the idea that self-paced exercise is regulated by top-down processing, given that we did not show clear evidence of exercise impairment (at the physical, physiological and subjective levels) in the high cognitive load condition task with respect to the low working memory load condition. The involvement of top-down processing in selfpacing the physical effort, however, cannot be totally discarded. Factors like the duration of the physical and cognitive tasks, the potential influence of dual-tasking, and the participants’ level of expertise, should be taken into account in future attempts to investigate the role of top-down processing in self-paced exercise., This project was supported by grant PSI2016-75956-P from Ministerio de Economía, Industria y Competitividad, awarded to DS and MZ, and grant FPU14/06229 from Ministerio de Educación, Cultura y Deporte, awarded to DH.

The end-spurt and U-shape reflect common pacing patterns across numerous fields. To date, however, the literature lacks a parsimonious, applicable account for these effects. Here, I propose a novel causal explanation for these effects – perceived impact. As one perceives his/her actions to better affect progress within a task, the higher one's motivation. The higher one’s motivation in a given time, the better his/her performance. To illustrate, during a race, if an athlete has five more laps to go, completing a given lap closes 20% of the remaining distance (1/5 laps = 20%). Alternatively, when the athlete has two laps to go, each lap represents 50% of the remaining distance. In the latter case, the impact of completing a single lap on goal progress is perceived to be higher. Accordingly, his/her motivation will increase near the end - giving rise to an end-spurt. I exemplify through simulations how this model can account for previous racing and research outcomes observing end-spurts and U-shaped pacing patterns. In addition to being theoretically insightful, this framework offers practical field implications for coaches and athletes by modifying counting style within sets (e.g., "3, 2, 1" instead of "13, 14, 15"), session outline (e.g., challenging sets in the end, instead of in the middle of the session), etc.

Lower limb maximal power output (Pmax) is a key physical component of performance in many sports. During squat jump (SJ) and countermovement jump (CMJ) tests, athletes produce high amounts of mechanical work over a short duration to displace their body mass (i.e. the dimension of mechanical power). Thus, jump height has been frequently used by the sports science and medicine communities as an indicator of Pmax. However, in this article, we contended that SJ and CMJ height are in fact poor indicators of Pmax in trained populations. To support our opinion, we first detailed why, theoretically, jump height and Pmax are not fully related. Specifically, we demonstrated that individual body mass, distance of push-off, optimal loading and force-velocity characteristics confound the jump height-Pmax relationship. We also discussed the poor relationship between SJ or CMJ height and Pmax measured with a force plate based on data reported in the literature, which added to our own experimental evidence.Finally, we discussed the limitations of existing practical solutions (regression-based estimation equations and allometric scaling), and advocated using a valid, reliable and simple field-based procedure to compute individual Pmax directly from jump height, body mass and push-off distance. The latter may allow researchers and practitioners to reduce bias in their assessment of Pmax by using jump height as an input with a simple yet accurate computation method, and not as the first/only variable of interest.

Objective To examine the effects of transcranial direct current stimulation (tDCS) on objective and subjective indexes of exercise performance. Design Systematic review and meta-analysis. Data sources A systematic literature search of electronic databases (PubMed, Web of Science, Scopus, Google Scholar) and reference lists of included articles up to June 2018. Eligibility criteria Published articles in journals or in repositories with raw data available, randomized sham-controlled trial comparing anodal stimulation with a sham condition providing data on objective (e.g. time to exhaustion or time-trial performance) or subjective (e.g. rate of perceived exertion) indexes of exercise performance. Results The initial search provided 420 articles of which 31 were assessed for eligibility. Finally, the analysis of effect sizes comprised 24 studies with 386 participants. The analysis indicated that anodal tDCS had a small but positive effect on performance g = 0.34, 95% CI [0.12, 0.52], z = 3.24, p = .0012. Effects were not significantly moderated by type of outcome, electrode placement, muscles involved, number of sessions, or intensity and duration of the stimulation. Importantly, the funnel plot showed that, overall, effect sizes tended to be larger in studies with lower sample size and high standard error. Summary The results suggest that tDCS may have a positive impact on exercise performance. However, the effect is probably small and most likely biased by low quality studies and the selective publication of significant results. Therefore, the current evidence does not provide strong support to the conclusion that tDCS is an effective means to improve exercise performance.

Objectives: To investigate the effect of tramadol on performance during a 20-min cycling time-trial (Experiment 1), and to test whether sustained attention would be impaired during cycling after tramadol intake (Experiment 2).Design: randomized, double-blind, placebo controlled trial.Methods: In Experiment 1, participants completed a cycling time-trial, 120-min after they ingested either tramadol or placebo. In Experiment 2, participants performed a visual Oddball task during the time-trial. Electroencephalography measures (EEG) were recorded throughout the session.Results: In Experiment 1, average time-trial power output was higher in the tramadol vs. placebo condition (tramadol: 220 watts vs. placebo: 209 watts; p < 0.01). In Experiment 2, no differences between conditions were observed in the average power output (tramadol: 234 watts vs. placebo: 230 watts; p > 0.05). No behavioural differences were found between conditions in the Oddball task. Crucially, the time frequency analysis in Experiment 2 revealed an overall lower target-locked power in the beta-band (p < 0.01), and higher alpha suppression (p < 0.01) in the tramadol vs. placebo condition. At baseline, EEG power spectrum was higher under tramadol than under placebo in Experiment 1 while the reverse was true for Experiment 2.Conclusions: Tramadol improved cycling power output in Experiment 1, but not in Experiment 2, which may be due to the simultaneous performance of a cognitive task. Interestingly enough, the EEG data in Experiment 2 pointed to an impact of tramadol on stimulus processing related to sustained attention.Trial registration: EudraCT number: 2015-005056-96.

Sports vision training involves eye focusing and movement workouts that center on the visual tracking of objects. The purpose of sports vision training is to improve performance in various sports by improving visual responses and processing, such as by lowering reaction times. In 2015, the Athletic Eye Institute started a sports vision-training program study with the Oregon State University Softball Team in the hopes of increasing the dynamic visual skills of their players. There were two aims of this study. The first aim was to test the hypothesis that softball athletes would show improvement over time in the specific sports vision training tests. The second aim was to test the hypothesis that sports vision training would lead to improvements of offensive batting statistics from the 2015 season, when players did not have vision training, to the 2016 season, after players had begun vision training. Results showed significant improvements in the scores from the initial to final training session for eight out of ten visual training tests. However, OSU softball player offensive batting statistics showed no significant improvement from the 2015 season to the 2016 season, or compared to other teams. This study showed that performances of sports vision tests can be improved over time with training, but that these improvements may not translate into improvements in softball offensive batting statistics.