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Mobile "PLAY CORE" Sports Coach App

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placeDE home_workTélétravail assignmentCDD publicOffre agrégée · DE

eventPubliée le 30 août 2026 · verifiedNous avons confirmé le 30 août 2026 qu'elle est toujours active

€ 12 – € 18 par projet

À propos de l'offre

PLAY CORE App – Initial Brief for Developers Discussion Basis for Feasibility, MVP and Cost Estimation 1. Project Idea PLAY CORE is an extensively developed training and learning system for team sports. The initial focus is on floorball, football/soccer, handball and basketball. Languages: English as the international master language. German for our primary domestic market and the pilot trainers. The aim is to turn this system into the mobile PLAY CORE Coach App. The app is not intended to be a conventional collection of drills. Instead, it should guide coaches through a complete training and learning process: Observe the game → Identify the problem → Define the learning objective → Plan the session → Select suitable games → Run the session → Observe → Intervene → Replay → Check development and transfer → Plan the next session The objective is to provide coaches with a simple tool that helps them design training around perception, decision-making, game understanding and players’ ability to solve game problems independently. 2. What Has Already Been Developed The sports-specific and methodological foundation does not need to be developed from scratch. The existing PLAY CORE system already includes: a comprehensive training and learning concept 30 defined player competencies/skills 42 fully developed training games and Game Cards a system for adjusting games to different difficulty levels a structure for complete training sessions a system for identifying and observing game problems categories for coaching interventions and coaching questions Replay and Transfer Checks a concept for documenting player and team development applications for floorball, football/soccer, handball and basketball The app should connect these existing components and make them easy for coaches to use in everyday practice. 3. Example User Journey A coach opens the app and enters, for example: Sport: Floorball Age group: U14 Players: 12 Training time: 90 minutes Observed problem: “In numerical advantage situations, the ball carrier often passes too early without first engaging the defender.” The app links the observed problem to possible learning competencies and suggests an appropriate training session. For example, the coach could receive: Learning objective: Recognise and exploit numerical advantages more effectively Attention focus: Defender behaviour Training: A sequence of progressively structured small-sided games Progression: Increasing defensive pressure Final phase: Free play without supporting rules or constraints The coach remains free to modify all suggestions. 4. Using the App During Training During a training session, the app should be extremely simple to operate. With only a few taps or by voice input, the coach could record an observation such as: “The ball carrier passes too early again.” The coach could then mark: Observation: Decision-making Intervention: Coaching question The players then receive another opportunity to solve the situation: REPLAY The coach records the outcome: ++ clearly improved | + improved | 0 unchanged | – worse | ? unclear Later, the coaching support or constraint is removed to determine: Does the improved behaviour remain without support? The result can then be used to plan the next training session. 5. Video as a Later Development Stage In a later version, the app could support short smartphone video clips. For example: BEFORE Game situation before the coaching intervention ↓ COACHING Question / feedback / task modification ↓ AFTER / REPLAY A comparable game situation after the intervention The coach could mark key moments, add comments, use slow motion or draw simple lines and arrows onto freeze frames. Automatic AI-based video analysis is not required for the first version and could be evaluated as a later development stage. 6. First Version / MVP The initial goal is deliberately not to develop the complete final app. A first functional Minimum Viable Product (MVP) could focus on: Create team / select sport ↓ Select or describe a game problem ↓ Select a relevant competency ↓ Generate a suggested training session ↓ Display Game Cards ↓ Start and run the training session ↓ Record observations and coaching interventions ↓ Evaluate Replay ↓ Complete a short session review ↓ Recommend the next training step The primary purpose of the MVP would be to test: Does PLAY CORE actually help coaches turn observations from the game into better, more systematic training decisions? 7. Possible Future Extensions Following successful testing of the MVP, the system could gradually be expanded with: smartphone video analysis voice control and automatic transcription AI support for interpreting and categorising game problems long-term team and player development profiles match observation coach dashboards a web application for planning and video analysis integrated coach education club, academy and federation solutions potentially AI-assisted video and movement analysis 8. Potential Business Models The business model has not yet been finalised and should be evaluated as part of the project. Possible models include: Coach Subscription Monthly or annual subscription for individual coaches Club Licence Access for multiple coaches and teams within one club Academy / Federation Licence Larger user groups combined with coach education PLAY CORE Education App + online courses + workshops / certification A combination of a free entry-level version and paid advanced features could also be considered. 9. Questions for a Potential Development Partner For an initial discussion, the following questions are particularly important: Is the concept technically feasible and sensible in this form? How would you define the smallest MVP that could already be tested with real coaches? Would you recommend starting with a web app, native mobile apps or a cross-platform solution? What technical architecture would allow video and AI functionality to be added later? What approximate development effort, timeline and bu

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