Expected Value of an NBA Draft Pick

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DESCRIPTION

Explored the relationship between NBA draft position and player performance across 22 draft classes (1989–2011) and 1,322 draftees.

TOOLS

PythonPandasNumPystatsmodelsScipyMatplotlibSeaborn

TIMELINE

May 2025

The Expected Value of an NBA Draft Pick examines a question every front office quietly wrestles with: how much does draft position actually matter?

Using data from Stathead.com, I built a dataset of 1,322 draftees across 22 NBA draft classes (1989–2011), measuring each player's value through "Prime Win Shares" — the sum of their five best seasons by Win Shares, a metric adapted from Brocato Prime Wins. Players who never appeared in the NBA are included with zero production, since a pick that goes nowhere is still a pick spent.

The analysis progressively refines the model: starting with a simple OLS regression, testing its assumptions, applying a log transformation to address skewness and non-linearity, grouping picks into draft tiers (Top Pick / Lottery / First Round / Second Round), and using bootstrap aggregation (bagging) to stabilize coefficient estimates.

The final models achieve an R² of ~0.326–0.328 — meaningful, but deliberately modest. The results highlight something the numbers make clear: draft position sets an expectation, not a guarantee. The variance in outcomes is the story.

Expected Value of an NBA Draft Pick - Image 1