Background Female participation in Australian football (AF) has increased substantially over the last 5 years. Measures for reducing injury, whether through coaching, training or rules, are currently based on anecdotal injury experiences and research from male participants. To ensure the safety of female participants, consideration of their specific injury profile is required.
Objective To provide the first understanding of injury in women's AF.
Design Two approaches were used.  compilation of four data sources: hospital-admissions, emergency department presentations, insurance claims, club-based collection;  online self-report survey of the worst injury sustained in the previous season.
Patients (or Participants) Female AF participants.
Interventions (or Assessment of Risk Factors) Not applicable.
Main Outcome Measurements Injury frequencies, injury types.
Results The survey provided information on 431 self-considered ‘worst’ injuries. Over half (55%) were lower limb injuries of which joint ligament tears/sprains (29%), muscle strains (18%) and fractures (13%) dominated. The knee (18%), hand/fingers (16%), and ankle (14%) were most common body parts injured. Concussion comprised 6% of all injuries. Upper limb injuries were featured in the hospital admissions (n=500 injuries in total) and emergency presentations (n=1879), 47% and 51% of all injuries, respectively. These were largely wrist/hand injuries (32% and 40%). Most (65%) insurance claim injuries (n=522) involved the lower limb, 27% for knee ligament damage. A high proportion of concussions (33%) were reported in the club collected data (n=49).
Conclusions Three injuries of particular significance were identified (knee joint ligament injuries, concussion, and wrist/hand/finger fractures, dislocations and sprains), which differ from key injuries identified in men's football where lower limb muscle strains are most prevalent, particularly hamstring/groin strains. A comprehensive prospective injury study in women's Australian football is now needed to support a robust collection of injury data, with a focus on identifying the cause and injury rates.