The NBA Draft through modeling statistics

Nothing in sports represents quite the crapshoot that a draft is. Scouts spend all year studying prospects, yet every year teams blow high picks on busts and unearth steals in the later rounds.

Statistical analysis can theoretically aid that accuracy rate, yet at the end of the day, no matter how good your model is, some players will outperform how good they are supposed to be and vice versa.

Yet that does not mean we should ignore models all together, like the one Kevin Pelton wrote about on ESPN.com in which he ranks prospects by projected future WARP:

Age isn’t the most important factor in projecting NBA success — how players have performed in the past is still more important — but because we’re comparing prospects at different stages of the development process, we can really only understand that performance in the context of age. That’s the fundamental truth on which my draft projections are built.

I start by translating a player’s college statistics to his NBA equivalents. That produces a per-minute rating, player win% (equivalent to PER), that projects how we can expect rookies to perform in the NBA next season. By adding age, I come up with a projection of how many Wins Above Replacement Player (WARP) prospects will produce over their first five years — the amount of time teams control a first-round pick between the four-year rookie contract and one year as a restricted free agent.

As with any statistical projection, the results are far from perfect. There’s too much uncertainty about how any individual will develop to tell the difference between prospects whose projections are decimal points apart. But larger differences can be meaningful indicators of over- or undervalued players.


The biggest surprise to me in Pelton rankings is how low Victor Oladipo and Ben McLemore are, as the two potential Suns picks fell all the way to Nos. 17 and 18, respectively. Oladipo was hurt by the emphasis on previous years since he has improved so steadily each season and McLemore for his low usage rate and high turnover rate.

Unsurprisingly Nerlens Noel and Otto Porter top the list, but then Colorado forward Andre Roberson shoots out of nowhere to be No. 3 on the WARP projection list with a projected rating of 2.6. As a Pac-12 guy, I’ve always respected Roberson’s game, but this ranking seems a bit much. Writes Pelton of Chad Ford’s No. 39 player:

Roberson fits a second-round stereotype — an undersized power forward with big-time athleticism. He struggled last season trying to play more on the perimeter, but has excelled defensively and on the glass against bigger players. Consider Roberson a poor man’s Kenneth Faried.

Potential Suns pick C.J. McCollum ranks sixth thanks to having “the highest translated usage rate of any player in the top 30.”

The Suns’ old analytics team built a proprietary draft model, and new GM Ryan McDonough is no secret to the concept either, so the Suns’ selections will likely be informed by such a model.

However, as Pelton’s most recent piece in which he showcases major hits and misses of his system over the past few years shows, we have yet to get to the point where making draft picks can be boiled down to a science.

Tags: Nba Draft Statistics

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