This week on Slappin’ Glass, we’re joined by data scientist and creator of the rapidly growing college basketball analytics platform EvanMiya.com, Evan Miyakawa. Evan’s work has become a trusted resource for coaches at every level—particularly those looking to cut through the noise of early-season statistics and understand which metrics actually matter.

In this conversation, Evan shares how coaches can separate interesting numbers from useful ones, why certain teams have unique statistical fingerprints that predict success, and how lineup data can be leveraged far more effectively than most programs currently use it. We also unpack defensive priority stats (threes, rim, free throws), halftime box score interpretation, and the origins of Evan’s “kill shot” metric—his way of measuring and predicting momentum swings across a season.

Whether you’re analytics-comfortable or analytically curious, Evan offers a clear, practical roadmap for applying data without drowning in it.

What You’ll Learn

1. How to Separate Useful Analytics from Interesting Noise

Evan explains why the highest-value decisions come from combining your coaching intuition with clean, adjusted data—not relying fully on either side. He details how to weigh early-season sample sizes, refine priors, and avoid overreacting to statistical outliers.

2. Identifying the 2–3 Metrics That Predict Your Team’s Success

Teams often win and lose in repeatable ways. Evan breaks down how programs can identify their own “keys to victory,” giving coaches clarity on what to prioritize in practice, scouting, and game planning.

3. Making Better Lineup Decisions (and Avoiding the Small-Sample Trap)

Learn why 30 possessions can reveal a spark worth exploring, why 100+ possessions create real confidence, and how lineup data—properly adjusted for opponent strength—helps avoid misleading results.

4. How to Read a Halftime Box Score with Meaningful Purpose

Evan shows which stat pairings matter most and how to judge whether a discrepancy is signaling a real problem or simply reflecting tempo and game context.

5. Prioritizing Defensive Outcomes: Threes, Rim, Free Throws

A clear breakdown of how these three areas interact, and why understanding your opponent’s tendencies can simplify what your defense should take away.

6. The “Kill Shot”: Understanding and Predicting Momentum Runs

Evan’s 10–0 run metric reveals why preventing opponent runs is more predictive of elite performance than generating them—and why the duration of a run often tells the real story.
7. Coaching the Moments Around Runs

From smart timeout usage to identifying schematic breakdowns, you’ll learn how to stop a slide early or create momentum without burning resources unnecessarily.

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