Effective coaching starts with understanding who you’re coaching and that begins with the data we collect. Numbers are often seen as neutral, but in sport, what we choose to measure (and what we don’t) can shape who feels included, seen, and supported.
Across the country, sport organizations are starting to look deeper at what their data actually says and who’s missing from it. From national governing bodies to local clubs, leaders are realizing that inclusion isn’t just a program; it’s a practice that starts with awareness, goals, and action.
STEP 1: Look at the Data and What’s Missing
Before you can build inclusion, you have to see the gaps. Ask:
- Do we collect the right data?
- Who’s participating — and who isn’t?
- Who’s coaching — and who’s leaving?
- What experiences are being tracked — and which aren’t?
For instance,
NICA’s GRiT (Girls Riding Together) initiative began after data showed girls made up only 20% of youth mountain biking. By naming that gap, NICA built new mentorship and community programs that boosted girls’ participation across several states.
USA Ultimate’s GUM program (Girls’ Ultimate Movement) used similar insights, realizing girls were underrepresented in local leagues, and partnered with schools to build girls-only clinics that introduced thousands of new athletes to the sport.
Data snapshot: Girls from lower-income households, girls of color, and girls with disabilities are less likely to participate in sport (Canadian Women & Sport, 2024), data that has not changed significantly (Tucker Center Research Report, 2018).
STEP 2: Set Goals That Reflect Equity, Not Just Growth
Once you know who’s missing, set specific goals for inclusion, not just total participation. That means tracking:
- Gender and race in athlete and coach pipelines
- Retention rates by age and identity
- Access points like scholarships, uniform policies, and equipment fit
But tracking data is only the first step. The real progress comes from what you do with that insight. That means investing in programming and education that helps coaches and leaders understand and support the athletes who aren’t yet being reached.
The USTA’s Coach Inclusion Summit is a great example: they didn’t just measure representation, they built intentional training and mentorship to help coaches connect with and reflect the communities they serve.
Research reinforces this link: Coaches with gender-responsive training are more likely to reject stereotypes and coach based on the individual and their skill rather than gender (Goorevich & LaVoi, 2024). When organizations pair inclusive data tracking with education, they move from awareness to action, creating environments where every athlete can belong and thrive.
STEP 3: Create Opportunities That Invite Everyone In
Numbers and goals only matter if they lead to action. Inclusion happens when organizations create visible, accessible entry points that meet real needs.
PSIA–AASI (the Professional Ski Instructors of America and American Association of Snowboard Instructors) has invested in equity and inclusion programs to bring more women, adaptive athletes, and instructors of color into snow sports.
Remember: 61% of girls say body image concerns keep them from sport (Women in Sport, 2022). Sometimes, inclusion starts with something as tangible as what she wears.
Companies like Nobody’s Princess are rethinking gear design so women and girls of every body shape can feel confident and comfortable on the slopes.
These examples show: that equity isn’t only about policy, it’s about everyday choices that shape who feels they belong in sport.
The Takeaway
Inclusion doesn’t start with programs, it starts with awareness.
By looking at who’s missing from the data, setting equity-centered goals, and designing programs that welcome every girl, leaders can turn insight into impact.
As one basketball coach put it: “Coaches set the tone for how inclusive a team feels. Inclusion isn’t a policy —it’s a daily choice.”
Data Check for Inclusion:
5 Questions Every Sport Leader Should Ask
Not all data tells the whole story. For decades, most sport science research, equipment design, and performance analytics have been based on male bodies. Injury-prevention models, heart rate algorithms, and even uniform design rarely account for female bodies, preferences, and physiology. Even your existing data can carry hidden bias. Use these quick questions to make sure your numbers tell the whole story, not just part of it.
1. Who’s Missing?
Does your participation data include all genders, races, and abilities, or only those who already feel welcome to register?
2. What Are You Measuring?
Are your metrics focused on outcomes (wins, speed, strength) or on growth, belonging, satisfaction, and confidence?
3. Whose Bodies Built the Data?
Are injury rates, uniforms, or equipment decisions based on research from boys and men, or are girls and women represented too?
4. Where Are the Blind Spots?
Do your surveys or feedback forms ask about experience satisfaction, cost, or inclusion, or just competition level?
5. Who Interprets the Data?
When reviewing results, are girls and underrepresented voices at the table to interpret what the data really means?
Remember: Bias doesn’t just live in behavior it lives in the numbers, too. Equity starts by asking better questions about the data we already have.
References
- Aspen Institute Project Play (2020). Stay of Play Report
- Canadian Women & (2022). The Rally Report 2022: A Call for Better, Safer Sport for Girls
- Canadian Women & Sport (2024). The Rally Report 2024: A Call to Reimagine Sport so All Girls Can Play
- Tucker Center for Research on Girls & Women in Sport (2018). Tucker Center Research Report: Developing Physically Active Girls: An Evidence-based Multidisciplinary Approach.