Domantas Sabonis Stats
The Enigma of Domantas Sabonis: A Statistical Deep Dive Domantas Sabonis, the Lithuanian powerhouse and two-time NBA All-Star, has long been a polarizing figure in basketball analytics.
On the surface, his numbers are undeniably impressive: a career double-double machine, an elite passer for his position, and a relentless rebounder.
Yet, beneath the glossy averages lies a more complicated story one of efficiency quirks, defensive limitations, and the eternal debate over how much traditional stats truly capture his impact.
Thesis Statement While Domantas Sabonis’s box-score statistics paint him as a dominant, all-around big man, a closer examination reveals critical flaws in his game particularly on defense and in high-leverage situations that challenge the narrative of his being a franchise cornerstone.
The Allure of the Box Score: Sabonis as a Stat-Sheet Stuffer Sabonis’s raw numbers demand attention.
In the 2022-23 season, he averaged 19.
1 points, 12.
3 rebounds, and 7.
3 assists per game, joining Nikola Jokić and Wilt Chamberlain as the only centers in NBA history to post such numbers.
His 25.
5% assist rate ranked in the 98th percentile for big men, per Cleaning the Glass, underscoring his playmaking brilliance.
But do these stats tell the full story? - Volume vs.
Efficiency: Sabonis’s scoring efficiency (60.
5% true shooting in 2022-23) is strong, but his reliance on post-ups (5.
1 per game, 48.
4% efficiency) pales in comparison to elite scorers like Joel Embiid (56.
8% on 7.
9 post-ups).
- Playmaking Brilliance or System Dependency? His assist numbers are inflated by the Sacramento Kings’ league-leading pace and heavy dribble-handoff actions with De’Aaron Fox.
While his passing is elite, his lack of a reliable jumper (32.
4% career 3PT) limits spacing.
The Defensive Conundrum: A Liability in Disguise? Sabonis’s defensive metrics are a red flag.
Despite his rebounding prowess, his -0.
8 Defensive Box Plus/Minus (DBPM) in 2022-23 ranked 45th among centers.
Opponents shot 5.
2% better at the rim when he was the primary defender, per NBA.
com tracking data.
- Mobility Issues: Sabonis struggles in space, making him a target in switch-heavy schemes.
The Kings’ 25th-ranked defense in 2022-23 was no coincidence.
- Rebounding vs.
Rim Protection: His 12.
3 rebounds per game mask his inability to deter shots.
For comparison, Rudy Gobert (11.
6 rebounds) held opponents to 8.
1% worse at the rim.
The Playoff Problem: Do His Stats Hold Up Under Pressure? Sabonis’s postseason performances raise concerns.
In the 2023 playoffs, his stats dipped to 16.
4 PPG, 11.
0 RPG, 4.
7 APG on 52.
9% TS, while the Warriors targeted him relentlessly on defense.
His net rating plummeted to -8.
9, per NBA Advanced Stats.
- Shrinking in the Spotlight: His career playoff TS% (54.
1%) is 4 points lower than his regular-season mark, suggesting struggles against elite defenses.
- The Jokić Comparison: Unlike Jokić, whose advanced metrics (32.
8 PER in 2023 playoffs) soar in the postseason, Sabonis’s impact wanes when schemes tighten.
The Analytics Divide: Traditional vs.
Advanced Metrics Sabonis’s case highlights the tension between old-school and modern analytics: - Pro-Sabonis: His 7.
6 Estimated Wins Added (EWA) in 2022-23 ranked 12th in the NBA, per NBA.
com.
His on/off numbers (+6.
1 net rating) suggest he drives winning.
- Anti-Sabonis: His -1.
3 Defensive RAPTOR ranked 278th in the league, and his 0.
9 Playoff PIPM (Player Impact Plus-Minus) was middling.
Conclusion: A Star, But With an Asterisk Sabonis is a statistical marvel, but his limitations particularly on defense and in the playoffs cast doubt on his ability to anchor a contender.
While his box-score dominance earns accolades, modern contenders increasingly demand two-way excellence from their stars.
Unless he evolves defensively or elevates in clutch moments, Sabonis may remain a fascinating case study in the gap between counting stats and championship impact.
The broader implication? In an era obsessed with triple-doubles, Sabonis’s career forces us to ask: Do traditional stats overvalue certain skills while obscuring fatal flaws? The answer could reshape how we evaluate big men in the analytics age.