NBA Mid-Season Statistical Briefing: February 2, 2026

As the NBA season progresses, team performance data provide a clearer picture of the league’s competitive landscape. Analysis of team-level statistics and individual player performance through February 1 reveals distinct tiers of contention and highlights several key trends. The data show a strong association between a positive point differential—the difference between points scored and points allowed per game—and a team’s overall success. While established stars populate the top of most statistical leaderboards, the distribution of wins suggests multiple pathways to building a successful team in the current season.

One of the most notable patterns is the comprehensive performance of the Oklahoma City Thunder. Holding the league’s best record at 39 wins and 11 losses (a 78% win percentage), their success is built on elite performance on both ends of the court. The Thunder lead all teams with a median point differential of +12.5, a figure significantly higher than that of the next closest teams. This advantage is associated with pairing a top-tier offense, which scores a median of 121.5 points per game (second highest), with the league’s most stringent defense, allowing a median of just 106.5 points per game. This two-way excellence suggests a well-balanced roster that does not rely on one specific facet of the game to secure victories.

In contrast, the Detroit Pistons present another notable pattern, achieving the league’s second-best record (36-12, 75%) through a different model. While not possessing the same overwhelming statistical profile as the Thunder, the Pistons have found consistent success, evidenced by their +6.5 median point differential. Their performance appears to be anchored by a strong defense, which allows a median of 112 points per game (tied for seventh-best in the league). Offensively, the team is led by Cade Cunningham, who attempts the most field goals in the league (19.3 per game) and ranks 10th in assists (9.8). The Pistons’ record, achieved without a player in the top ten for points per game, could indicate a disciplined system that maximizes the contributions of its core players.

Beyond the top two teams, the data underscore the reliability of point differential as an indicator of team quality. All of the top eight teams by win percentage possess a median point differential of +4.0 or higher. Conversely, the nine teams with the lowest win percentages all have negative median point differentials, ranging from -3.0 to -12.0. The Utah Jazz, for example, have the league’s leading scorer in Lauri Markkanen (27.4 points per game), yet their median point differential of -9.0 aligns with their 15-35 record. This situation may reflect how elite individual scoring does not always translate directly to team wins, especially when defensive performance lags, as evidenced by Utah allowing a median of 128 points per game.

Examining individual statistics requires context, as the leaderboards present potential limitations. For instance, categories like Field Goal Percentage and 3-Point Percentage are often topped by players with very low shot volumes, which can create a misleading impression of league-wide shooting efficiency. Furthermore, these cumulative box score data do not account for variables such as strength of schedule, player injuries, or the quality of opposing defenses faced, all of which can influence both team and player performance. The high turnover rates among several top offensive players, such as Luka Dončić (4.2 per game) and Nikola Jokić (3.5 per game), suggest that their substantial offensive creation also comes with a higher risk of losing possessions.

Histograms

This figure displays histograms of game-level point differentials for each National Basketball Association (NBA) team during the current season. Each bar represents the number of games with a given scoring margin, using a bin width of five points. Positive differentials correspond to wins, while negative values correspond to losses. Bars are colored according to game outcome, distinguishing victories from defeats. Teams whose histograms are skewed to the right tend to win by larger margins or more frequently, reflecting stronger performance and offensive dominance. In contrast, teams with distributions clustered near zero or skewed to the left tend to play in closer or less favorable contests. This visualization provides a clear snapshot of each team’s competitiveness, consistency, and margin of victory throughout the season.

Graph Prepared By: Isaac H. Michaels, DrPH
Data Source: www.basketball-reference.com

Trends

This figure presents game-by-game point differentials for each National Basketball Association (NBA) team throughout the current season. Each vertical bar represents a single game, with its height showing the margin of victory or defeat — positive values for wins and negative values for losses. Bars are colored green for wins and red for losses. The plot provides a visual timeline of each team’s season, highlighting streaks of dominance, close contests, and periods of inconsistency. Teams with consistently tall positive bars tend to win decisively or maintain strong offensive and defensive balance, while those with frequent negative or alternating bars exhibit more erratic outcomes. By visualizing game results in sequence, the chart offers a clear picture of momentum shifts, performance stability, and overall competitiveness over time.

Graph Prepared By: Isaac H. Michaels, DrPH
Data Source: www.basketball-reference.com

Per-Game Stats

This table summarizes individual performance statistics for all National Basketball Association (NBA) players who have appeared in at least 10 games during the current season. It provides a comprehensive overview of offensive and defensive contributions across multiple dimensions of play. Core indicators such as games played (G), games started (GS), and minutes per game (MP) establish each player’s level of participation and role within their team. Scoring efficiency is reflected through field goal (FG%), three-point (3P%), two-point (2P%), and free throw (FT%) percentages, along with related per-game averages for made and attempted shots.

Rebounding and playmaking statistics—offensive rebounds (ORB), defensive rebounds (DRB), total rebounds (TRB), and assists (AST)—capture control of possession and ball distribution, while defensive metrics such as steals (STL) and blocks (BLK) reflect individual defensive impact. Turnovers (TOV) and personal fouls (PF) provide additional context on possession management and defensive discipline. Points per game (PTS) serve as a key summary measure of scoring productivity.

Together, these statistics offer a balanced portrait of player performance across offensive efficiency, defensive activity, and overall on-court effectiveness. Awards and recognitions are included where applicable, highlighting standout achievements during the season.

Note: Table displays rows only for players who played in at least 10 games.
Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.basketball-reference.com

G – Games
GS – Games Started
MP – Minutes Played Per Game
PTS – Points Per Game
FG – Field Goals Per Game
FGA – Field Goal Attempts Per Game
FG% – Field Goal Percentage
3P – 3-Point Field Goals Per Game
3PA – 3-Point Field Goal Attempts Per Game
3P% – 3-Point Field Goal Percentage
2P – 2-Point Field Goals Per Game
2PA – 2-Point Field Goal Attempts Per Game
2P% – 2-Point Field Goal Percentage
eFG% – Effective Field Goal Percentage
FT – Free Throws Per Game
FTA – Free Throw Attempts Per Game
FT% – Free Throw Percentage
ORB – Offensive Rebounds Per Game
DRB – Defensive Rebounds Per Game
TRB – Total Rebounds Per Game
AST – Assists Per Game
STL – Steals Per Game
BLK – Blocks Per Game
TOV – Turnovers Per Game
PF – Personal Fouls Per Game

Distributions and Leaders in Selected Statistics