1. SSAs- Evidence Based Planning Rochelle Eime VicHealth Research Practice Fellow- Physical Activity r.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 Australias 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- SSAs – 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

11. 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

12. 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

13. 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

15. Participation numbers- Postcode - Demographic breakdowns

16. Participation filters

17. Yearly total participation- LGA

18. Yearly participation rate- LGA

19. Details of participation

20. Participation- use of the data

21. Changes in participation- previous year

22. Population projections

23. Planning for change, future

24. Infrastructure

25. Details of facilities

26. Participation and SEIFA

27. Health- Obesity

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

29. 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

30. 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

31. 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?