AbstractBackground It is crucial to balance load and recovery during short-term match congestion in basketball. Currently, it is unknown if higher total load during short-term match congestion lead to higher injury and illness rates.Objective Aim of this study was to compare injuries and illnesses and total weekly load during 1-match weeks compared to ≥2-match weeks in basketball.Design During this prospective observational study, players were monitored during a full season.Setting Two basketball teams participating in the domestic-league championship, CUP matches and Euro league were followed.Patients (or Participants) Sixteen elite male professional basketball players participated in this study. Characteristics of the players were (mean±SD): age 24.8±2.0 years, height 195.8±7.5 cm, weight 94.8±14.0 kg, body fat 11.9±5.0% and VO2max 51.9±5.3 mL·kg−1·min−1.Interventions (or Assessment of Risk Factors) In total 47 matches by basketball team A (9 players) and 41 matches by team B (7 players) were performed throughout the season. All training sessions and matches were executed as prescribed by the training and coaching staff without interference or manipulation.Main Outcome Measurements The Oslo Sports Trauma Research Center (OSTRC) Questionnaire on Health Problems was used to collect data on injuries and illnesses on a weekly base. Furthermore, players filled in s-RPE and duration for each training and match. Prevalence’s, severity scores, time-loss and total weekly load were compared for 1-match weeks and ≥2-match weeks. The data were analyzed using multi-level modeling.Results Prevalence of injuries and illnesses were 18.1% and 4.6% for 1-match weeks and 17.2% and 3.3% for ≥2-match weeks. Severity scores and time-loss were not significantly different for 1-match weeks compared to ≥2-match weeks. Total weekly load was lower during ≥2-match weeks compared to 1-match weeks.Conclusions No significant differences for injuries and illnesses were observed between 1-match weeks and ≥2-match weeks. Coaches appeared to reduce training load to compensate for multiple matches during short-term match congestion.
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In elite basketball, players are exposed to intensified competition periods when participating in both national and international competitions. How coaches manage training between matches and in reference to match scheduling for a full season is not yet known. Purpose: First, to compare load during short-term match congestion (ie, ≥2-match weeks) with regular competition (ie, 1-match weeks) in elite male professional basketball players. Second, to determine changes in well-being, recovery, neuromuscular performance, and injuries and illnesses between short-term match congestion and regular competition. Methods: Sixteen basketball players (age 24.8 [2.0] y, height 195.8 [7.5] cm, weight 94.8 [14.0] kg, body fat 11.9% [5.0%], VO2max 51.9 [5.3] mL·kg−1·min−1) were monitored during a full season. Session rating of perceived exertion (s-RPE) was obtained, and load was calculated (s-RPE × duration) for each training session or match. Perceived well-being (fatigue, sleep quality, general muscle soreness, stress levels, and mood) and total quality of recovery were assessed each training day. Countermovement jump height was measured, and a list of injuries and illnesses was collected weekly using the adapted Oslo Sports Trauma Research Center Questionnaire on Health Problems. Results: Total load (training sessions and matches; P
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During intensified phases of competition, attunement of exertion and recovery is crucial to maintain performance. Although a mismatch between coach and player perceptions of training load is demonstrated, it is unknown if these discrepancies also exist for match exertion and recovery. Purpose: To determine match exertion and subsequent recovery and to investigate the extent to which the coach is able to estimate players’ match exertion and recovery. Methods: Rating of perceived exertion (RPE) and total quality of recovery (TQR) of 14 professional basketball players (age 26.7 ± 3.8 y, height 197.2 ± 9.1 cm, weight 100.3 ± 15.2 kg, body fat 10.3% ± 3.6%) were compared with observations of the coach. During an in-season phase of 15 matches within 6 wk, players gave RPEs after each match. TQR scores were filled out before the first training session after the match. The coach rated observed exertion (ROE) and recovery (TQ-OR) of the players. Results: RPE was lower than ROE (15.6 ± 2.3 and 16.1 ± 1.4; P = .029). Furthermore, TQR was lower than TQ-OR (12.7 ± 3.0 and 15.3 ± 1.3; P < .001). Correlations between coach- and player-perceived exertion and recovery were r = .25 and r = .21, respectively. For recovery within 1 d the correlation was r = .68, but for recovery after 1–2 d no association existed. Conclusion: Players perceive match exertion as hard to very hard and subsequent recovery reasonable. The coach overestimates match exertion and underestimates degree of recovery. Correspondence between coach and players is thus not optimal. This mismatch potentially leads to inadequate planning of training sessions and decreases in performance during fixture congestion in basketball.
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The maximum capacity of the road infrastructure is being reached due to the number of vehicles that are being introduced on Dutch roads each day. One of the plausible solutions to tackle congestion could be efficient and effective use of road infrastructure using modern technologies such as cooperative mobility. Cooperative mobility relies majorly on big data that is generated potentially by millions of vehicles that are travelling on the road. But how can this data be generated? Modern vehicles already contain a host of sensors that are required for its operation. This data is typically circulated within an automobile via the CAN bus and can in-principle be shared with the outside world considering the privacy aspects of data sharing. The main problem is, however, the difficulty in interpreting this data. This is mainly because the configuration of this data varies between manufacturers and vehicle models and have not been standardized by the manufacturers. Signals from the CAN bus could be manually reverse engineered, but this process is extremely labour-intensive and time-consuming. In this project we investigate if an intelligent tool or specific test procedures could be developed to extract CAN messages and their composition efficiently irrespective of vehicle brand and type. This would lay the foundations that are required to generate big data-sets from in-vehicle data efficiently.
Designing with the Sun is a KIEM-GoCI explorative research project on the theme Energy Transition and Sustainability. The project is aimed at network and agenda building and design research that explores new (cultural) practices of renewable energy consumption, based on a shift from ‘energy blindness’ to ‘energy awareness’. Up until now the solar industry has been propelled forward by technical innovations, offering mostly pragmatic, economic benefits to consumers. Innovation in this field mostly concerns making solar panels more efficient and less costly. However, to succeed, the energy transition also needs new cultural practices. These practices should reflect the ways renewables are different from fossil fuels. For solar, this means using more direct solar energy, when the sun is there, and being able to adapt to periods of low energy. Currently, consumers are mostly ‘blind’ to the infrastructure behind fossil-based energy. However, for energy sources such as solar and wind ‘awareness’ of their availability becomes more important. What could such an awareness look or feel like? How can it be enacted? And how can a change in practice that is more attuned to availability be experienced positively? Solar companies see opportunities in using design to help build motivating practices and narratives within the solar field, enabling awareness through personal relationships between consumer and solar energy. However, the knowledge of how to get there is lacking. In a research-through-design trajectory, and together with partners from the Creative Industries, Designing with the Sun aims to explore new ways of relating citizens to solar energy. Ultimately, these insights should enable the newly emerging field of solar design to contribute to the emergence of more sustainable and rewarding energy awareness and practices.
Positive Energy Districts (PEDs) can play an important part in the energy transition by providing a year-round net positive energy balance in urban areas. In creating PEDs, new challenges emerge for decision-makers in government, businesses and for the public. This proposal aims to provide replicable strategies for improving the process of creating PEDs with a particular emphasis on stakeholder engagement, and to create replicable innovative business models for flexible energy production, consumption and storage. The project will involve stakeholders from different backgrounds by collaborating with the province, municipalities, network operators, housing associations, businesses and academia to ensure covering all necessary interests and mobilise support for the PED agenda. Two demo sites are part of the consortium to implement the lessons learnt and to bring new insights from practice to the findings of the project work packages. These are 1), Zwette VI, part of the city of Leeuwarden (NL), where local electricity congestion causes delays in building homes and small industries. And 2) Aalborg East (DK), a mixed-use neighbourhood with well-established partnerships between local stakeholders, seeking to implement green energy solutions with ambitions of moving towards net-zero emissions.
