Bucket getters. Ethical Hoopers. “That-boy-nice”. The Pure Hooper. Whatever way you would like to phrase it, there is a beauty to watching a player hit his defender with a hesi-cross to swish a contested stepback jumper with 23 seconds left on the shot clock. Is it an efficient shot? No. But can the volume and efficiency of these tough buckets be an indicator of self-creation for top college prospects? Potentially…
The Metrics
Todd Whitehead (@crumpledjumper on Twitter) and the people of Synergy Sports recently created a Synergy Shot Quality metric, measuring the quality of each and every shot. Through various components explained below, shots are compiled into a single score, ranging from high (>80th %tile of shot quality) to low (<20th %tile of shot quality). Swish Theory’s Tyler recently used this metric for a piece on shotmaking prospects Brandon Miller and Jett Howard, for example.
Along with the metric, Synergy has labeled each player with an offensive archetype that best resembles their playstyle/role, analyzing their usages and tendencies to develop 3 primarily roles: Ball Handlers, Wings, and Bigs, including sub-archetypes within each role.
The Data
Coming back to the original topic of difficult shot-making, I wanted to see how college players in Swish Theory’s Top 40 Prospects stacked up in their frequency of low quality shots and the efficiency of these shots. The x-axis measures the share of each player’s field goal attempts categorized by Synergy as low quality looks, while the y-axis displays how well each player shot on those attempts.
The further to the right on this graph, the greater share of difficult attempts; the further up near the top, the better the shotmaking.
I divided the results by archetype as well to best compare each player relative to their own role. To add the finishing touch, I included multiple historical examples to see how some of the NBA’s best match up.
The number one standout in this study is Jalen Hood-Schifino, terrorizing drop coverages with his mid-range prowess (sad Purdue noises) with the highest share of shots being difficult. While Nate Oats preaches the paint-and-three approach more than maybe any other coach, seeing Brandon Miller in the lower left corner is slightly concerning for hopes as a late shot-clock creator. Nick Smith Jr. had a messy freshman campaign battling injuries and consistent playing time, but his main sell circling around his tough shot-making spells some concerns as he lands at the bottom of this graph (albeit on limited volume compared to others).
If you look up a bit higher you can see ol’ Jalen Brunson hanging around on an island. His upper echelon functional strength, change of pace, and sweet footwork worked wonders in the trenches, and his outlier shot-making was one of the key indicators of his future success.
Jarace Walker did not have an easy shot diet, especially for an athletic/defensive inclined big wing, but maintaining respectable efficiency in spite of that provides some hope of a higher-end offensive outcome. Brice Sensabaugh was made for this graph, and his elite in-between and pull-up game scorched the Big Ten. Mikal Bridges is an interesting case study, as he was rarely tasked with difficult shots in college, but showcased elite efficiency that has shown to pay dividends for his self-creation jump.
As we move to bigs, we see a massive increase in the quality of looks these bigs are getting, as the high-percentile shots right at the rim occur at a sizably higher rate than their counterparts. No surprise to see the rim-running Dereck Lively and Adem Bona slotted in the top left corner, with a combined mere 13 low-quality shot attempts between the two. Domantas Sabonis is the biggest outlier of any NBA player I’ve looked at, the soft touch + bruising strength steamrolled over the poor WCC. Taylor Hendricks and DaRon Holmes II are the only two bigs in this class with over 10% of their looks being difficult shots and above average efficiency with those shots, though one can be certain Victor Wembanyama would break this graph entirely.
Conclusion
While more research needs to be done to truly make an assessment whether these low quality metrics can stand as a predictor for self-creation/difficult shot-making, there is value in locating those flashes of outperformance. Whether it be in volume or efficiency, taking shots late in the shot-clock, off the dribble, in isolation or contested with some degree of success is a bright green flag for future NBA contributions.
It is worth a reminder that these are small samples by their nature, and may say as much about a prospect’s context as their performance. As well, taking a more difficult shot diet is neither a good or bad thing, but a means of the talent of a player and the needs of a team.
At the end of the day, you can look at these stats as glass half-empty or half-full: a player takes too many bad shots or it shows promise of higher usage at the next level. Or, a third option: lean into your inner hooper, shatter the glass on the floor, make some popcorn, and delight yourself to a BallDontStop highlight mix. Something we should all do a bit more.
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