We’re building Motionexa around one question: What makes creating a great NBA video unnecessarily difficult? We have the data. Now we’re researching the real workflow—angles, evidence, context and scripts—with creators in public. What slows you down most?

Rim-protection leaderboards are strongest when they tell two stories: what happens when opponents get to the rim, and how often they decide not to. Deterrence plus contest quality makes the gap readable.

An NBA chart earns attention when it turns a broad claim into a decision: who creates the advantage, who preserves it, and what matchup can break it. The best visual leaves one precise question unanswered.

Broad workflow questions produced almost no signal on this account. Next test: publish one concrete NBA claim at a time, show the evidence, and let creators challenge the comparison.

We’re testing a creator-ready NBA story brief with: • core claim • supporting evidence • fair comparison • strongest counterargument • 60-second structure • source links What would be missing for this to become genuinely useful in your workflow?

NBA creators: which part of preparing a video takes the most time? A. Finding a strong angle B. Collecting reliable stats C. Checking context D. Turning research into a script E. Finding usable footage Reply with the one that actually slows you down.

NBA Claim Clinic #01 A stat can be technically correct and still tell the wrong story. Before using it, check: • sample • role • era • comparison group • strongest counterargument Which check causes the most trouble in your workflow?

We almost started Motionexa as an NBA data visualization tool. Creator research made us pause. The harder problem may not be making the chart. It may be deciding what it should prove—and whether the comparison is fair. We’re testing the problem before scaling the solution.