NBA 2025โ€“26 Season

Interactive Analysis โ€” Top 25 Scorers

How to Use This Page

Click on any underlined player name in the analysis sections below to highlight their row in the data table. Click stat category names to spotlight those columns. Use this page to explore patterns and connections in the data.

Interactive Info Box

Click any highlighted player name or stat category in the analysis below to see details here.

Data Reference Table

# Player Team PTS FG% 3P% FT% REB AST STL BLK TOV EFF
1Luka Donฤiฤ‡LAL 33.647.634.878.08.08.81.50.54.234.0
2Shai Gilgeous-AlexanderOKC 32.055.639.089.44.46.21.30.82.032.9
3Anthony EdwardsMIN 29.449.540.979.95.23.71.30.82.725.9
4Jaylen BrownBOS 29.448.536.277.66.94.81.00.43.625.9
5Tyrese MaxeyPHI 29.247.238.988.54.26.92.00.92.428.5
6Donovan MitchellCLE 29.148.438.484.24.75.81.50.23.126.4
7Kawhi LeonardLAC 27.749.639.593.66.13.52.10.62.127.8
8Lauri MarkkanenUTA 27.447.635.988.97.12.21.10.61.525.8
9Stephen CurryGSW 27.246.839.193.13.54.81.10.42.823.8
10Jalen BrunsonNYK 27.247.238.385.33.26.10.70.12.323.3
11Kevin DurantHOU 26.251.040.588.65.44.60.70.93.025.2
12Jamal MurrayDEN 25.849.244.788.14.37.41.00.32.426.5
13Michael Porter Jr.BKN 25.648.239.885.17.33.21.10.32.524.5
14Deni AvdijaPOR 25.546.735.680.07.26.70.80.63.926.0
15Devin BookerPHX 25.445.631.386.44.06.20.90.33.322.5
16James HardenLAC 25.441.934.790.14.88.11.30.43.725.3
17Cade CunninghamDET 25.246.032.480.95.69.81.50.93.727.5
18Keyonte GeorgeUTA 24.245.937.789.34.06.61.10.33.323.1
19Victor WembanyamaSAS 24.150.436.483.311.12.70.92.62.729.4
20Pascal SiakamIND 23.848.337.768.96.94.01.10.52.222.6
21Jalen JohnsonATL 23.149.936.078.010.58.01.30.53.530.0
22Norman PowellMIA 23.047.239.284.43.72.61.20.22.019.2
23Julius RandleMIN 22.349.333.581.96.95.41.20.22.624.2
24Brandon IngramTOR 21.947.035.883.65.93.70.80.82.620.6
25Shaedon SharpePOR 21.945.834.677.84.62.71.50.13.117.0

Analysis Walkthroughs

Analysis 1: Shooting Efficiency vs. Volume

Among the elite scorers of the 2025-26 season, the relationship between volume and efficiency is more nuanced than expected. Shai Gilgeous-Alexander stands apart with a remarkable 55.6% FG%, the highest in the group, showing that the highest efficiency doesn't always come with the highest scoring rank. He achieves this by generating free throws at an elite rate (9.3 FTA/g) and keeping his three-point volume low.

By contrast, James Harden posts the lowest FG% (41.9%) among all top-25 scorers, relying more heavily on high-volume three-point attempts and a league-leading 90.1% from the free throw line. His approach prioritizes drawing fouls and creating offense through passing (8.1 APG) over field goal efficiency.

This contrast illustrates that Kevin Durant's 51.0% FG% represents the ideal combination โ€” high efficiency maintained alongside deep shot creation, a hallmark of his elite status even later in his career.

Analysis 2: The All-Around Contributor

Scoring averages alone don't capture a player's full value. Luka Donฤiฤ‡ leads all scorers with 33.6 PPG while simultaneously averaging 8.8 APG and 8.0 RPG โ€” approaching a true triple-double average and demanding double teams that open opportunities for teammates.

Victor Wembanyama offers a unique case: ranked 19th in scoring at 24.1 PPG, his 11.1 RPG and 2.6 BPG are far ahead of any other player in this dataset. His efficiency rating of 29.4 actually exceeds several players who outscore him, reflecting his multi-dimensional impact.

Meanwhile, Jalen Johnson at #21 in scoring quietly posts 10.5 RPG and 8.0 APG โ€” a statistical profile more reminiscent of a traditional point forward than a shooting guard. His EFF rating of 30.0 ranks among the top 5 in this group, despite his lower PPG rank.

Analysis 3: Free Throw Generation โ€” The Hidden Scoring Lever

Free throws are often undervalued in casual analysis, but for elite scorers they can make or break a night. Kawhi Leonard leads all top-25 scorers with a staggering 93.6% from the line โ€” an elite mark that effectively makes every free throw trip worth near-maximum value.

Stephen Curry closely follows at 93.1%, making both players among the most reliable free throw shooters in league history. Their high percentages mean these players benefit disproportionately from getting fouled compared to players like Pascal Siakam, who converts just 68.9% โ€” the lowest in this group by a wide margin.

The gap is consequential: Siakam takes 6.0 FTA per game. At 68.9%, that yields 4.1 points per trip. Had he converted at even 85%, those same trips would generate 5.1 points โ€” nearly a full point of extra scoring per game from free throws alone.

Analysis 4: Turnover Efficiency โ€” Scoring Without the Giveaways

High-usage scorers must manage turnovers to remain net positives. Lauri Markkanen is remarkably low-turnover at just 1.5 per game despite averaging 27.4 PPG โ€” suggesting an efficient, catch-and-shoot, low-dribble offensive style that minimizes risk.

Luka Donฤiฤ‡, on the other end, leads the group with 4.2 turnovers per game. However, his elite scoring and creation output (and EFF of 34.0) suggests this cost is well outweighed by his overall impact โ€” the turnovers come from taking on high-risk playmaking responsibilities others can't or won't attempt.

For comparison, Cade Cunningham also shows 3.7 TOV but pairs that with league-leading 9.8 APG โ€” the highest assist rate in this group โ€” demonstrating that some turnovers are an inherent cost of elite playmaking at the point guard position.