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SSAs - Evidence Based Planning Rochelle Eime VicHealth Research Practice Fellow- Physical Activity r.eime@ballarat.edu.

SSAs - Evidence Based Planning Rochelle Eime VicHealth Research Practice Fellow- Physical Activity r.eime@ballarat.edu.au. Background history of project development. VicHealth research practice fellowship- 2011-2015 Aim: Data analysis to inform growth in sport participation in Victoria

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SSAs - Evidence Based Planning Rochelle Eime VicHealth Research Practice Fellow- Physical Activity r.eime@ballarat.edu.

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  1. SSAs- Evidence Based PlanningRochelle EimeVicHealth Research Practice Fellow- Physical Activityr.eime@ballarat.edu.au

  2. Background history of project development • VicHealth research practice fellowship- 2011-2015 • Aim: Data analysis to inform growth in sport participation in Victoria • VicHealth, SRV, VicSport • Spatial mapping of data • Helen Thompson, Paul Feely- Centre for eCommerce and Communications (UB) • Aust. Sports Commission/VU collaborative partnership- 2012-2013 • Funding for spatial mapping and statistical support • Development of business plan- Competitive Edge 2013

  3. Sport and Recreation Spatial • The first Victorian and National data collection, management, knowledge and research system to inform program and policy decision making for the national sport and recreation sector in the areas of participation, facilities and health • Includes a repository of sport and recreation data

  4. Vision • To become Australia’s leading provider of innovative and pragmatic research, to assist the sports and recreation sector and government, optimise the development of participation programs, facilities, and community health and wellness

  5. Mission • Provide leading-edge GIS/spatial know-how and research techniques to measure the impact of current sports industry on health, community wellness, facilities and future sports participation. • Collaborate with universities, Government, health agencies and sports organisations to create a sustainable repository of national data to inform future knowledge and policy for sport and recreation industry • Facilitating and delivering leading edge research and development to determine the relationship between sports, recreation and exercise participation, facilities and a healthy, educated society and community

  6. Key Areas • Participation levels and trends • Influences on participation • Value of sport: health benefits of participation • Places to play: nexus between facilities and participation • Development of Indicators

  7. Data • Exercise, Sport and Recreation Survey (ERASS) 2000-2010 • Sport participation data- SSA’s • Player, coach and official • Over 2 million records to date • Sport and recreation facility data • Population demographics • Population projection data • Health data

  8. Scope • Currently 8 Victorian State Sporting Associations • AFL • Basketball • Cricket • Football Federation • Hockey • Lawn Bowls • Netball • Tennis

  9. Different levels of use • Organisations directly use the GIS to spatially visualise and analyse • sector-wide data • their own data • derived and customised indicators • Knowledge and evidence to inform program and policy developments • Demonstration and training • Sector level research

  10. Benefits • Centralised sport and recreation data repository • Collaborative project with sport, health, university and government sectors • Economic benefits of one data management and research system for sport and recreation sector • Geographical Information System- spatially visualise and analyse data • Knowledge and evidence to inform program and policy development • Ability to respond in proactive rather than reactive manner • Integration of large datasets • Standardised data • Derived and customised indicators • Capacity building of sector through training workshops • Research capabilities • Translation and dissemination of sector-wide research

  11. Benefits for sport sector • Participation and membership • Participation trends, penetration and influences on participation • Player development • Talent development trends and influences • Infrastructure • Plan infrastructure development • Coach and umpire development • Target coach and umpire development strategies • Marketing • Understanding of participation and population and programs for targeted marketing • Schools • Relationship between school based strategies and community participation opportunities • Finance • Where best to invest for player, coach, facility developments • Ability to evaluate investments

  12. Benefit for Government • Quality data for the sport and recreation sector to make informed program and policy decisions to grow participation • Consistency of data and data reporting across sector • Measure key objectives of growing sport participation • Nexus between participation and health • Focussing on partnership approaches • Ensuring a long term strategic approach applicable across governments • Adopting the ethos of continuous improvement and evidence based policy and practice

  13. Participation numbers- Postcode - Demographic breakdowns

  14. Participation filters

  15. Yearly total participation- LGA

  16. Yearly participation rate- LGA

  17. Details of participation

  18. Participation- use of the data

  19. Changes in participation- previous year

  20. Population projections

  21. Population projections Planning for change, future

  22. Infrastructure

  23. Details of facilities

  24. Participation and SEIFA

  25. Health- Obesity

  26. Collection of data • Reason for data collection • Membership collection • Insurance • Informing decisions • Internal and external reporting • Good data in- good data out

  27. Collection of data • Accuracy of data • Single ID records • How to achieve this? • Complete data • How is data collected? • Individual versus club/team • Online participant systems • Integrated data management systems • Player, coach and umpire • Within and between organisations • Repeated collection of data –season/year • Turning data into knowledge

  28. Data to be collected • Participant, coach and official/umpire • ID • Lowest common denominator • Date of birth • Potential only collect once • Postcode • Residential address • Club(s) • Program • Consistency- electronic drop-down • Year • Level of accreditation • Other target groups

  29. Making the most of the data • What do you do with your date? • What would you like to do with your data? • Consistency • Collection, data management, reporting • Cubs, leagues, SSAs, NSO • Cleaning data • Analyse based on priorities • What are they?

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