Elite soccer teams that participate in European competitions need to have players in the best physical and psychological status possible to play matches. As a consequence of congestive schedule, ...controlling the training load (TL) and thus the level of effort and fatigue of players to reach higher performances during the matches is therefore critical. Therefore, the aim of the current study was to provide the first report of seasonal internal and external training load that included Hooper Index (HI) scores in elite soccer players during an in-season period. Nineteen elite soccer players were sampled, using global position system to collect total distance, high-speed distance (HSD) and average speed (AvS). It was also collected session rating of perceived exertion (s-RPE) and HI scores during the daily training sessions throughout the 2015-2016 in-season period. Data were analysed across ten mesocycles (M: 1 to 10) and collected according to the number of days prior to a one-match week. Total daily distance covered was higher at the start (M1 and M3) compared to the final mesocycle (M10) of the season. M1 (5589m) reached a greater distance than M5 (4473m) (ES = 9.33 12.70, 5.95) and M10 (4545m) (ES = 9.84 13.39, 6.29). M3 (5691m) reached a greater distance than M5 (ES = 9.07 12.36, 5.78), M7 (ES = 6.13 8.48, 3.79) and M10 (ES = 9.37 12.76, 5.98). High-speed running distance was greater in M1 (227m), than M5 (92m) (ES = 27.95 37.68, 18.22) and M10 (138m) (ES = 8.46 11.55, 5.37). Interestingly, the s-RPE response was higher in M1 (331au) in comparison to the last mesocycle (M10, 239au). HI showed minor variations across mesocycles and in days prior to the match. Every day prior to a match, all internal and external TL variables expressed significant lower values to other days prior to a match (p<0.01). In general, there were no differences between player positions. Conclusions: Our results reveal that despite the existence of some significant differences between mesocycles, there were minor changes across the in-season period for the internal and external TL variables used. Furthermore, it was observed that MD-1 presented a reduction of external TL (regardless of mesocycle) while internal TL variables did not have the same record during in-season match-day-minus.
This reprint presents information to update the state-of-the-art knowledge on young, professional or recreational, male and female athletes. Moreover, it addresses current gaps in the literature on ...issues that have an impact on athletes (e.g., Crohn’s disease, Olympic weightlifting, and velocity speed loss). Importantly, this reprint contributes to knowledge on how to improve load monitoring (of training and competition) and health care for athletes through direct or indirect research.
•Total distance and average speed were higher in training that preceded win.•High-speed running distance was similar in training that preceded win and defeat.•Hooper index was lower after a win than ...a draw or defeat.•S-RPE seems to vary through the week with no relation to the match result.
The aim of the study was to compare training load (TL) of the days preceding a win, draw or defeat in a sample of elite professional soccer players across the in-season 2015/16.
Twenty elite soccer players participated in this study. Total distance covered, high-speed running distance (HSRD), average speed, session rate of perceived exertion (s-RPE) and Hooper index scores (HI) were collected. Data from 24 weeks with one match were analysed through the match-day (MD-5, 4, 3, 2, 1) and MD+1.
The main finding emerges in MD-1, where a longer training duration preceding draws (95.1 ± 1.5 min) > defeats (91.5 ± 1.6 min) > wins (84.7 ± 0.5 min) was found, while total distance and average speed were higher in wins (3628.6 ± 57.2 m) > draws (3391.3 ± 153.3 m) > defeats (3236.1 ± 113.7 m) and draws (130.7 ± 17.6 m/min) > wins (86.0 ± 6.9 m/min) > defeats (54.8 ± 7.1 m/min), respectively. HSRD was higher in draws (42.8 ± 0.6 m) > wins (36.1 ± 1.7 m) > defeats (35.8 ± 1.7 m). In MD+1, there were differences in HI between wins vs draws (p<0.01).
The results are drawn from one team that participated in UEFA Champions League. It was observed that different TL applied in training sessions can influence match result. Our findings can be considered in future soccer planning and periodization to win matches. This study emphasizes the use of HI especially in the day following the match.
Spectral data describing product samples are typically composed of a large number of noisy and irrelevant wavelengths that tends to undermine the performance of multivariate predictive techniques. ...This paper proposes a two‐phase framework that integrates a preselection wavelength step oriented by wavelength clustering to a wrapper‐based strategy. The first phase performs a pruning process in the data that removes the less informative wavelengths relying on the spectral clustering, a technique deemed suitable to the Fourier transform infrared (FTIR) spectroscopy and near‐infrared (NIR) spectroscopy data at hand. The preselected wavelengths undergo a second phase of selection efforts based on the combination of different wavelength importance indices (i.e., Bhattacharyya distance, Chi‐square, ReliefF, and Gini) and classification techniques (i.e., support vector machine, k‐nearest neighbors, and random forest). When applied to 11 FTIR datasets from different domains, the recommended combination of importance index and classifier increased the average accuracy by 6.37% (from 0.863 to 0.918), while retaining average 3.84% of the original spectra. The framework also improved the selection process regarding computational time.
This paper introduces a two‐phase framework merging wavelength preselection through clustering and a wrapper strategy. Initial spectral clustering eliminates less informative wavelengths. Subsequently, diverse wavelength importance indices and classification methods are integrated. Applied to 11 spectral datasets, the proposed combination (spectral clustering SC‐random forest RF+Gini GI) enhances average accuracy by 6.37%, retaining 3.84% of the original spectra, and reduces computational time.
•The integration of wavelength importance rankings with the Random Forest classifier is proposed to analyze spectral data.•Six different wavelength importance rankings are assessed and the best ...performing is recommended.•Propositions are validated in six binary and multiclass datasets.•The method outperformed competing approaches in terms of percentage of retained wavelengths.
Near Infrared (NIR) is a type of vibrational spectroscopy widely used in different areas to characterize substances. NIR datasets are comprised of absorbance measures on a range of wavelengths (λ). Typically noisy and correlated, the use of such datasets tend to compromise the performance of several statistical techniques; one way to overcome that is to select portions of the spectra in which wavelengths are more informative. In this paper we investigate the performance of the Random Forest (RF) classifier associated with several wavelength importance ranking approaches on the task of classifying product samples into categories, such as quality levels or authenticity. Our propositions are tested using six NIR datasets comprised of two or more classes of food and pharmaceutical products, as well as illegal drugs. Our proposed classification model, an integration of the χ2 ranking score and the RF classifier, substantially reduced the number of wavelengths in the dataset, while increasing the classification accuracy when compared to the use of complete datasets. Our propositions also presented good performance when compared to competing methods available in the literature.
The aims of this study were to: (i) analyse the within-microcycle variations in professional soccer players; (ii) analyse the relationships between wellness and training and match load demands; (iii) ...analyse the relationships between match-day (MD) demands and wellness during the following day (MD+1); and (iv) analyse the relationships between MD and wellness during the day before match-play (MD-1). Thirteen professional soccer players (age: 24.85±3.13 years) were monitored daily over 16-weeks for wellness and training and match-play intensity. The daily wellness measures included fatigue, quality of sleep, muscle soreness, mood and stress using a 1-5 scale. Internal intensity was subjectively measured daily using the rating of perceived exertion (RPE) and the multiplication of RPE by session duration (s-RPE). While external intensity was quantified utilising high-speed running, sprinting, and acceleration and deceleration metrics. Data was analysed from each training session before (i.e., MD-5) or after the match (i.e., MD+1). Repeated measures ANOVA or Friedman ANOVA was used to analyse the aims (i) where Spearman correlation was applied to analyse the relationships between the aims (ii) and (iii) between sleep quality and training intensity. The main results for aim (i) showed that MD+1 presented the lowest values for wellness variables (p < 0.05). While MD-1 presented the lowest internal and external load values (for all variables), with MD presenting the highest values (p < 0.05). Regarding aim (ii), the main result showed significant large negative correlations between fatigue and s-RPE (r = -0.593; p = 0.033). Considering aim (iii), significant small to very large negative correlations were found for sleep quality, fatigue and muscle soreness with all internal and external variables (p < 0.05). Lastly, the main results for aim (iv) showed large negative correlations for fatigue and session duration; fatigue and s-RPE; muscle soreness and session duration; muscle soreness and s-RPE; and muscle soreness and decelerations (p < 0.05, for all). The main conclusions were that MD had an influence on wellness and internal and external training intensity, notably MD-1 and MD+1 were most affected. In this regard, a tendency of higher internal and external intensity on MD was associated with lower wellness measures of sleep quality, muscle soreness and fatigue on MD+1.
Managing customer retention is critical to a company’s profitability and firm value. However, predicting customer churn is challenging. The extant research on the topic mainly focuses on the type of ...model developed to predict churn, devoting little or no effort to data preparation methods. These methods directly impact the identification of patterns, increasing the model’s predictive performance. We addressed this problem by (1) employing feature engineering methods to generate a set of potential predictor features suitable for the banking industry and (2) preprocessing the majority and minority classes to improve the learning of the classification model pattern. The framework encompasses state-of-the-art data preprocessing methods: (1) feature engineering with recency, frequency, and monetary value concepts to address the imbalanced dataset issue, (2) oversampling using the adaptive synthetic sampling algorithm, and (3) undersampling using NEASMISS algorithm. After data preprocessing, we use XGBoost and elastic net methods for churn prediction. We validated the proposed framework with a dataset of more than 3 million customers and about 170 million transactions. The framework outperformed alternative methods reported in the literature in terms of precision-recall area under curve, accuracy, recall, and specificity. From a practical perspective, the framework provides managers with valuable information to predict customer churn and develop strategies for customer retention in the banking industry.
Background: Peripheral nerve disease may lead to physical disability because of decreased muscle strength and/or loss of sensitivity in the dermatomes of affected peripheral nerves. Both human ...immunodeficiency virus (HIV)- and leprosy-affected patients can develop neurological damage; therefore, the coinfection of these diseases presents new challenges to the health care of these patients. Aims and Objective: This study aimed to investigate the motor alterations of patients coinfected with HIV and leprosy and their relationship with clinical and anthropometric characteristics, compared with individuals with isolated diseases. Materials and Methods: In this cross-sectional study, 90 individuals were divided equally into three groups: HIV/acquired immunodeficiency syndrome (AIDS) group, leprosy group and HIV/leprosy group. All individuals underwent an evaluation of muscle strength and upper limb endurance adjusted for the Brazilian standards, a palm print pressure test using a digital dynamometer and anthropometric measurements (weight, height and skin folds). Results: The HIV/leprosy group had the highest mean body mass index, followed by the leprosy group and the HIV/AIDS group. Skinfolds were similar between the groups. Multiple linear regression, adjusted for sex and age, revealed the coinfection of HIV and leprosy as possible contributor to a worse prognosis of muscle function, highlighting the bilateral reduction in the levels of palm print compression strengths compared with isolated diseases (HIV and leprosy). High CD4 count and shorter antiretroviral therapy duration were associated with worse indices of muscle strength, such as gripping and resistance, in coinfected patients. Conclusion: Patients coinfected with HIV and leprosy exhibited greater motor damage than those with isolated diseases. Thus, motor damage may be related to the sum of the neurological manifestations of the two morbidities.
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