Week 3 — Culture, Self-Determination Theory, and Better Tools

Outcome

Use competence, autonomy, and relatedness to evaluate both team culture and the athlete experience of performance technology.

Required preparation

Choose one rslts or APOPT workflow to test with your own information: watch analysis, a workout or training summary, form analysis, or heart/ECG analysis when compatible personal data is available.

Part 1 — 5–7 minute instructional script

Team culture is often described with slogans: work hard, trust the process, be a family. But culture is not primarily what is printed on a shirt. Culture is what athletes repeatedly experience. Who receives attention? Who gets choices? What happens after a mistake? Does the data start a conversation, or does it become a weapon? Technology does not sit outside culture. Every dashboard, ranking, notification, and coach message teaches athletes what the group values.

Self-Determination Theory gives us three useful questions. Competence: Does the athlete feel capable of learning and improving? Autonomy: Does the athlete have appropriate ownership and a meaningful voice? Relatedness: Does the athlete feel known, respected, and connected? Motivation becomes more durable when these needs are supported. Coaches still set standards, but the athlete experiences standards as part of growth and belonging rather than control alone.

Consider competence. A useful app can make improvement visible, show how a workout matched its purpose, or break a complex skill into one achievable cue. The same app can damage competence if it floods the athlete with red warnings, compares unlike athletes, or presents uncertain estimates as judgments. The coaching question is not simply, “Is the metric accurate?” It is also, “What belief about capability will this presentation create?”

Consider autonomy. Data can help an athlete notice patterns and participate in decisions. A coach might ask, “What do you notice in the second half?” before giving an answer. Autonomy does not mean athletes prescribe everything or ignore the plan. It means they understand purpose, contribute relevant context, and gradually learn to make responsible choices. Technology undermines autonomy when athletes are monitored without explanation or told that a score knows them better than they know themselves.

Consider relatedness. A coach who uses data well can notice someone who is quietly struggling, remember an athlete’s goal, or follow up after a hard session. But dashboards can also narrow attention to the fastest, most complete, or easiest-to-measure athletes. If an athlete appears only as a row of numbers, the tool has made the relationship thinner rather than stronger. Data should create better questions for a human conversation.

This week you will test one app as both a coach and a participant. Complete a real workflow with your own information. Notice where you feel capable or confused, where you have meaningful control or feel trapped, and where the experience invites or discourages conversation. Product feedback becomes more valuable when it names a specific moment and a desired result.

“Make the app better” is not actionable. A useful feedback statement follows a chain. Workflow: what were you trying to do? Evidence: what happened? Friction: why did that make the task harder or less trustworthy? Request: what feature or change do you want? Desired result: what should the coach or athlete be able to understand or do? Acceptance test: what observable experience would show the change worked?

For example: “While reviewing an easy run, I could not tell whether high heart rate came from a hill or a sustained flat section. Add an elevation-aligned view to the intensity chart. The desired result is that a coach can distinguish terrain-driven effort from pacing error. Success means the same time selection highlights pace, heart rate, and elevation together.” The request is grounded in a real coaching job and a clear result.

Feedback should also identify what already works. A product team needs to know which explanation, sequence, or visual supported the task so an improvement does not remove it. Describe both the useful moment and the friction. This makes your recommendation more balanced, more credible, and easier to translate into a testable change.

The best feature is not always more analysis. Sometimes the needed change is clearer uncertainty, a simpler explanation, a prompt to ask the athlete how the session felt, or a way to hide detail until it becomes relevant. A good tool supports competence without pretending certainty, autonomy without abandoning guidance, and relatedness without replacing conversation.

Your challenge is to evaluate one workflow through all three needs. Then recommend one change that improves the athlete or coach experience. Technology becomes part of healthy culture when it helps people understand, choose, connect, and act.

Three takeaways

• Culture is the repeated athlete experience, including how coaches collect and discuss data.

• Evaluate technology through competence, autonomy, and relatedness—not accuracy alone.

• Product feedback should connect observed friction to a requested change and measurable desired result.

Part 2 — 30–45 minute application lab

1. Select a workflow — 3 minutes: Name one real job and the app you will test.

2. Complete it — 12 minutes: Use your own data. Record key steps, confusion, and useful moments.

3. SDT audit — 8 minutes: Rate competence, autonomy, and relatedness support from 1–5 and cite evidence.

4. Write the feedback brief — 12 minutes: Complete workflow, evidence, friction, request, desired result, and acceptance test.

5. Peer usability review — 5 minutes: A partner checks whether the request is specific enough for a product team to test.

Data-driven participation assignment

Provide one app feedback brief with these required fields: app and workflow; data source; what worked; observed friction; requested feature or change; desired coach or athlete result; and acceptance test. Do not include personal files or direct identifiers in the brief.

Literature + Generative-AI discussion preparation

Search Self-Determination Theory in sport, autonomy-supportive coaching, athlete motivation, or technology adoption. Use and verify the standard AI summary. Prepare one example of a data practice that strengthens competence, autonomy, and relatedness—and one that could undermine them.

Multi-sport adaptation

Choose the tool that fits the sport: APOPT movement analysis for starts, jumps, strength, throws, basketball, tennis, cycling, swimming, and other skills; watch or training summaries where workload and intensity are relevant.

Protect athlete data and interpret cautiously

Use personal data for this test. Product feedback should describe the workflow and result, not expose raw files, names, health details, or screenshots containing private information.

Resources and next week

• rslts: https://rslts.run/

• APOPT apps: https://apopt.com/

• APOPT Watch Analysis: https://apopt.com/watch/

• APOPT Running Form Analysis: https://apopt.com/form/form.php

• APOPT Heart Analysis: https://apopt.com/heart/

• Next: Week 4 — Turning Outcomes into Measurable Goals