Paralympic wheelchair athletes solely depend on the power of their upper-body for their on-court wheeled mobility as well as for performing sport-specific actions in ball sports, like a basketball shot or a tennis serve. The objective of WheelPower is to improve the power output of athletes in their sport-specific wheelchair to perform better in competition. To achieve this objective the current project systematically combines the three Dutch measurement innovations (WMPM, Esseda wheelchair ergometer, PitchPerfect system) to monitor a large population of athletes from different wheelchair sports resulting in optimal power production by wheelchair athletes during competition. The data will be directly implemented in feedback tools accessible to athletes, trainers and coaches which gives them the unique opportunity to adapt their training and wheelchair settings for optimal performance. Hence, the current consortium facilitates mass and focus by uniting scientists and all major Paralympic wheelchair sports to monitor the power output of many wheelchair athletes under field and lab conditions, which will be assisted by the best data science approach to this challenge.
DOCUMENT
Fields neighboring the disciplines of kinesiology and sports science have called for more interdisciplinary work, including the adoption of critical approaches to research. This scoping review explored the degree to which critically-aligned research has developed within these disciplines. The goal was to identify who this research studied, what methods were used, and which theoretical and conceptual frameworks were adopted. Publications between 2010-2022 in six top kinesiology and sports science journals using four databases were searched using keywords to identify critically-aligned research. A multi-step screening process was used to identify and sort articles that adequately fit the criteria of critically-aligned research. The scoping review identified 5666 entries of which 3300 were unique publications. 76 articles were assessed to be critically-aligned. Four themes regarding demographics emerged: Geographic area, gender, race/ethnicity/indigeneity, and inequality/inequity. Regarding methodology, three major theoretical and conceptual frameworks emerged: ecological, socio-economic, and cultural. Overall, a relatively small number of studies fit our search criteria, suggesting that critically-aligned research remains at the margins of the disciplines. For the studies that were critically-aligned, they often centered the Global North and were inconsistent in their application of categories such as race, ethnicity, inequality and equity. These studies were diverse in their methodological approach while relying on ecological, socio-economic, and cultural frameworks. To heed the calls for a more interdisciplinary approach, and to advance the disciplines more generally, kinesiology and sports science should expand their adoption of critical approaches to research.
MULTIFILE
Although causal inference has shown great value in estimating effect sizes in, for instance, physics, medical studies, and economics, it is rarely used in sports science. Targeted Maximum Likelihood Estimation (TMLE) is a modern method for performing causal inference. TMLE is forgiving in the misspecification of the causal model and improves the estimation of effect sizes using machine-learning methods. We demonstrate the advantage of TMLE in sports science by comparing the calculated effect size with a Generalized Linear Model (GLM). In this study, we introduce TMLE and provide a roadmap for making causal inference and apply the roadmap along with the methods mentioned above in a simulation study and case study investigating the influence of substitutions on the physical performance of the entire soccer team (i.e., the effect size of substitutions on the total physical performance). We construct a causal model, a misspecified causal model, a simulation dataset, and an observed tracking dataset of individual players from 302 elite soccer matches. The simulation dataset results show that TMLE outperforms GLM in estimating the effect size of the substitutions on the total physical performance. Furthermore, TMLE is most robust against model misspecification in both the simulation and the tracking dataset. However, independent of the method used in the tracking dataset, it was found that substitutes increase the physical performance of the entire soccer team.
DOCUMENT
The focus of this project is on improving the resilience of hospitality Small and Medium Enterprises (SMEs) by enabling them to take advantage of digitalization tools and data analytics in particular. Hospitality SMEs play an important role in their local community but are vulnerable to shifts in demand. Due to a lack of resources (time, finance, and sometimes knowledge), they do not have sufficient access to data analytics tools that are typically available to larger organizations. The purpose of this project is therefore to develop a prototype infrastructure or ecosystem showcasing how Dutch hospitality SMEs can develop their data analytic capability in such a way that they increase their resilience to shifts in demand. The one year exploration period will be used to assess the feasibility of such an infrastructure and will address technological aspects (e.g. kind of technological platform), process aspects (e.g. prerequisites for collaboration such as confidentiality and safety of data), knowledge aspects (e.g. what knowledge of data analytics do SMEs need and through what medium), and organizational aspects (what kind of cooperation form is necessary and how should it be financed).Societal issueIn the Netherlands, hospitality SMEs such as hotels play an important role in local communities, providing employment opportunities, supporting financially or otherwise local social activities and sports teams (Panteia, 2023). Nevertheless, due to their high fixed cost / low variable business model, hospitality SMEs are vulnerable to shifts in consumer demand (Kokkinou, Mitas, et al., 2023; Koninklijke Horeca Nederland, 2023). This risk could be partially mitigated by using data analytics, to gain visibility over demand, and make data-driven decisions regarding allocation of marketing resources, pricing, procurement, etc…. However, this requires investments in technology, processes, and training that are oftentimes (financially) inaccessible to these small SMEs.Benefit for societyThe proposed study touches upon several key enabling technologies First, key enabling technology participation and co-creation lies at the center of this proposal. The premise is that regional hospitality SMEs can achieve more by combining their knowledge and resources. The proposed project therefore aims to give diverse stakeholders the means and opportunity to collaborate, learn from each other, and work together on a prototype collaboration. The proposed study thereby also contributes to developing knowledge with and for entrepreneurs and to digitalization of the tourism and hospitality sector.Collaborative partnersHZ University of Applied Sciences, Hotel Hulst, Hotel/Restaurant de Belgische Loodsensociëteit, Hotel Zilt, DM Hotels, Hotel Charley's, Juyo Analytics, Impuls Zeeland.
Big data spelen een steeds grotere rol in de (semi)professionele sport. De hoeveelheid gegevens die opgeslagen wordt, groeit exponentieel. Sportbegeleiders (coaches, inspanningsfysiologen, sportfysiotherapeuten en sportartsen) maken steeds vaker gebruik van sensoren om sporters te monitoren. Tijdens trainingen en wedstrijden worden de hartslagen, afgelegde afstanden, snelheden en versnellingen van sporters gemeten. Het analyseren van deze data vormt een grote uitdaging voor het begeleidingsteam van de sporters. Sportbegeleiders willen big data graag inzetten om meer grip te krijgen op sportblessures. Blessures kunnen namelijk desastreuze gevolgen hebben voor teamprestaties en de carrière van (semi)professionele sporters. In totaal stopt maar liefst 33% van de topsporters door blessures met hun sportloopbaan. Daarnaast is uitval door blessures een belangrijke oorzaak van stagnatie van talentontwikkeling. Het lectoraat Sportzorg van de Hogeschool van Amsterdam heeft veel expertise op het gebied van blessurepreventie in de sport. Sportbegeleiders hebben het lectoraat Sportzorg benaderd om antwoord te krijgen op de onderzoeksvraag: Wat zijn op data gebaseerde indicatoren om sportblessures te voorspellen? Deze onderzoeksvraagstelling is opgesplitst in de volgende deelvragen: 1. Hoe kan met sensoren relevante data van sporters verzameld worden om de sportbelasting in kaart te brengen? 2. Welke parameters kunnen blessures voorspellen? 3. Hoe kunnen deze parameters op betekenisvolle en eenvoudige wijze naar sportbegeleiders en sporters teruggekoppeld worden? Het project resulteert in de volgende projectresultaten: - Een overzicht van nauwkeurige en gebruiksvriendelijke sensoren om sportbelasting in kaart te brengen - Een overzicht van relevante parameters die blessures kunnen voorspellen - Een online tool dat per sporter aangeeft of de sporter wel of niet training- of wedstrijdfit is Bij dit project zijn de volgende organisaties betrokken: Hogeschool van Amsterdam, Universiteit Leiden, VUmc, Rijksuniversiteit Groningen (RuG), Amsterdam Institute of Sport Science (AISS), Johan Sports, Centrum voor Topsport en Onderwijs (CTO) Amsterdam, Koninklijke Nederlandse Voetbalbond (KNVB), de Nederlandse Vereniging voor Fysiotherapie in de Sport (NVFS), VV Noordwijk (voetbalclub) en Black Eagles (basketbalclub).
Fietsen in Nederland creëren een afvalprobleem. Zo zijn weesfietsen een voorbeeld van hoe een fietsrijke samenleving geen duurzaam transportsysteem garandeert. Twintig procent van de Nederlandse openbare fietsenstallingen staan vol met weesfietsen (WMD, 2008). Het tijdig en adequaat onderhouden en repareren van de spullen die wij gebruiken, dus ook fietsen, kan helpen om tot minder afval te komen (Ackerman, Mugge and Schoormans, 2018). Reparatie- en onderhoudswerkzaamheden zijn echter niet altijd haalbaar voor alle gebruikers (Makatsoris et al., 2017; Bakker et al., 2023). Het Bike Kitchen (BK) concept is een wereldwijd fenomeen met als kernwaarden het beschikbaar maken van fietsreparatie voor alle mensen (Valentini en Butler, 2023; Batterbury & Dant, 2019; Batterbury & Manga, 2022; Bradley, 2018). Hoewel de uitvoering van verschillende BK’s anders is, heeft het concept als primaire doel gebruikers professioneel te ondersteunen bij het (leren van) repareren en onderhouden van hun eigen fiets om zo de levensduur van de fiets te verlengen. Tijdens dit KIEM-project onderzoeken ontwerpend onderzoekers samen met service designers, sociaal ondernemers en ROC Midden Nederland hoe een BK als Living Lab bij kan dragen aan het (leren over) verminderen van de milieu-impact uit materiaalgebruik. Vanuit eerder opgedane inzichten uit de literatuur en bij de BK Amsterdam, worden twee BK’s ontworpen en geoperationaliseerd, gericht op specifieke plaatsen (Utrecht Science Park en woonwijk Overvecht) en twee specifieke doelgroepen (studenten en wijkbewoners). Door middel van observaties, interviews en focusgroepen zoomen we in op achterliggende waarden en competenties met betrekking tot materialen- en productgebruik en zoomen we uit op de invloed op de samenleving. Zo leren we hoe het BK concept direct invloed kan hebben op milieu-impact en indirect op andere initiatieven en/of maatschappelijke ontwikkelingen en zo bij kan dragen als ‘agent of change’ richting een duurzame samenleving (Valentini en Butler, 2023).
