NBA Player Stats Leaders for 2024-25 Season

Welcome to our NBA Player Stats page, your go-to destination for detailed performance metrics, real-time updates, and in-depth analyses of every player's game contributions; discover comprehensive stats and trends that highlight the impact of each player on the court, and be sure to check out our NBA starting lineups for a complete view of who’s making the plays.

Welcome to our NBA Player Stats page, your go-to destination for detailed performance metrics, real-time updates, and in-depth analyses of every player's game contributions; discover comprehensive stats and trends that highlight the impact of each player on the court, and be sure to check out our NBA starting lineups for a complete view of who’s making the plays.

Name Pos Team Rating
Shai Gilgeous-Alexander S. Gilgeous-Alexander PG OKC
86
Giannis Antetokounmpo G. Antetokounmpo PF MIL
98
Nikola Jokić N. Jokić C DEN
95
Luka Dončić L. Dončić PG LAL
94
Anthony Edwards A. Edwards SG MIN
87
Jayson Tatum J. Tatum SF BOS
92
Kevin Durant K. Durant PF PHO
95
Jalen Brunson J. Brunson PG NY
82
Tyrese Maxey T. Maxey PG PHI
86
Cade Cunningham C. Cunningham PG DET
83
Devin Booker D. Booker SG PHO
90
LaMelo Ball L. Ball PG CHA
86
Anthony Davis A. Davis C DAL
89
Paolo Banchero P. Banchero PF ORL
77
Damian Lillard D. Lillard PG MIL
88
Kyrie Irving K. Irving PG DAL
88
LeBron James L. James SF LAL
97
Karl-Anthony Towns K. Towns PF NY
90
Zion Williamson Z. Williamson PF NO
88
Joel Embiid J. Embiid C PHI
95
Franz Wagner F. Wagner SF ORL
79
Victor Wembanyama V. Wembanyama PF SA
67
Trae Young T. Young PG ATL
91
Cam Thomas C. Thomas SG BKN
75
Donovan Mitchell D. Mitchell SG CLE
87
Stephen Curry S. Curry PG GS
97
Tyler Herro T. Herro SG MIA
83
De'Aaron Fox D. Fox PG SA
83
Zach LaVine Z. LaVine SG SAC
89
Jaylen Brown J. Brown SG BOS
86
Norman Powell N. Powell SG LAC
79
Jaren Jackson Jr. J. Jackson Jr. PF MEM
84
James Harden J. Harden SG LAC
88
Brandon Ingram B. Ingram SF TOR
87
DeMar DeRozan D. DeRozan SF SAC
88
Ja Morant J. Morant PG MEM
94
Jamal Murray J. Murray PG DEN
85
Jalen Green J. Green SG HOU
81
Jalen Williams J. Williams SF OKC
71
Brandon Miller B. Miller SF CHA
67
Trey Murphy III T. M. III SF NO
76
RJ Barrett R. Barrett SG TOR
85
CJ McCollum C. McCollum PG NO
84
Miles Bridges M. Bridges SF CHA
81
Pascal Siakam P. Siakam PF IND
87
Darius Garland D. Garland PG CLE
88
Jordan Poole J. Poole PG WAS
84
Coby White C. White SG CHI
75
Kawhi Leonard K. Leonard SF LAC
95
Scottie Barnes S. Barnes SF TOR
83
Name Pos Team Rating MIN/G PTS AST REB STL BLK TOV ORB 3PM 3PA FTM FTA PF USG%
Shai Gilgeous-Alexander S. Gilgeous-Alexander PG OKC
86
33.8 32.7 6.3 4.9 1.7 1 2.5 0.9 2.1 5.7 8 8.9 2.2 34.6
Giannis Antetokounmpo G. Antetokounmpo PF MIL
98
33.4 30.1 5.9 11.9 0.8 1.1 3.2 2.4 0.1 0.8 6.2 10.3 2.5 35.7
Nikola Jokić N. Jokić C DEN
95
36.1 29.5 10.4 12.9 1.8 0.7 3.2 3 1.9 4.6 5.1 6.2 2.3 29.7
Luka Dončić L. Dončić PG LAL
94
34.5 27.8 7.8 8.2 1.9 0.4 3.8 0.8 3.5 9.8 5.9 7.6 2.6 34.9
Anthony Edwards A. Edwards SG MIN
87
36.2 27.5 4.7 5.7 1.2 0.6 3.3 0.8 4.1 10.2 5.5 6.5 1.8 31.7
Jayson Tatum J. Tatum SF BOS
92
36 27.1 6 8.6 1.1 0.5 3 0.7 3.6 10.2 5.1 6.3 2.2 31.6
Kevin Durant K. Durant PF PHO
95
36.5 26.9 4.3 6.2 0.8 1.3 3.2 0.4 2.6 5.9 5 6 1.7 29
Jalen Brunson J. Brunson PG NY
82
34.9 26.5 7.4 2.9 0.9 0.1 2.5 0.4 2.3 5.9 5.7 6.9 2.2 30
Tyrese Maxey T. Maxey PG PHI
86
37.1 26.1 6.2 3.3 1.7 0.4 2.3 0.3 3 9.2 4.8 5.4 2.2 30.2
Cade Cunningham C. Cunningham PG DET
83
34.5 25.9 9.1 6 1.1 0.7 4.5 0.8 2.2 6.1 4.6 5.3 2.8 33.3
Devin Booker D. Booker SG PHO
90
36.9 25.4 7.1 4.1 1 0.2 2.9 0.9 2.5 7.3 6 6.7 2.7 28.9
LaMelo Ball L. Ball PG CHA
86
31.8 25.4 7.2 5 1.1 0.3 3.6 1 3.8 11.5 4.2 4.9 3.3 35.8
Anthony Davis A. Davis C DAL
89
33.5 25.1 3.5 11.7 1.3 2.1 2.1 2.8 0.7 2.1 5.9 7.4 1.9 30.2
Paolo Banchero P. Banchero PF ORL
77
33.8 25.1 4.6 7.2 0.8 0.7 2.8 1.1 1.9 5.8 6.1 8.4 2.1 33
Damian Lillard D. Lillard PG MIL
88
35.5 25 7.1 4.7 1.2 0.2 2.8 0.5 3.4 9.1 6.2 6.8 1.6 28
Kyrie Irving K. Irving PG DAL
88
35.4 24.9 4.5 4.8 1.3 0.4 2.2 1.2 2.9 7.3 4.1 4.4 2 27.9
LeBron James L. James SF LAL
97
34.4 24.8 8.5 8 0.9 0.6 3.9 0.9 2.2 5.8 3.6 4.6 1.4 31
Karl-Anthony Towns K. Towns PF NY
90
34.3 24.6 3 12.6 1 0.7 2.5 3 2.1 4.9 4.7 5.6 3.4 27.3
Zion Williamson Z. Williamson PF NO
88
28 24.5 5.1 7.1 1.3 0.9 3 2.5 0.1 0.4 5.4 8.2 2.8 34.8
Joel Embiid J. Embiid C PHI
95
30.4 24.4 4.4 8.4 0.8 1 3.4 1.9 1.2 4.2 8.1 9.2 2.3 35.1
Franz Wagner F. Wagner SF ORL
79
33.1 24.3 4.8 5.7 1.3 0.4 2.4 1 1.7 5.8 4.6 5.3 2.6 31.7
Victor Wembanyama V. Wembanyama PF SA
67
32.7 24.3 3.5 11.1 1.2 3.8 3.2 1.8 3.2 8.9 3.3 4 2.2 30.7
Trae Young T. Young PG ATL
91
35.5 24 11.4 3.1 1.2 0.2 4.8 0.5 2.8 8.4 6.4 7.4 1.9 29.9
Cam Thomas C. Thomas SG BKN
75
30.7 24 3.8 3.3 0.6 0.1 2.5 0.6 2.7 7.8 5.3 6 1.8 33.6
Donovan Mitchell D. Mitchell SG CLE
87
30.7 23.9 4.8 4.3 1.3 0.2 2.1 0.8 3.3 8.9 4.1 5 2 31.5
Stephen Curry S. Curry PG GS
97
31.6 23.6 6 4.4 1 0.4 3 0.5 4.2 11 3.9 4.2 1.4 29.5
Tyler Herro T. Herro SG MIA
83
35.1 23.5 5.7 5.3 0.9 0.2 2.6 0.4 3.3 9 3.6 4.2 1.2 28.3
De'Aaron Fox D. Fox PG SA
83
35.6 23.5 6.3 4.8 1.5 0.4 2.8 0.8 1.9 6.1 4.2 5.1 2.6 28.2
Zach LaVine Z. LaVine SG SAC
89
34.3 23.2 4.3 4.5 0.8 0.2 2.8 0.3 3.1 7.2 3.3 4 1.4 25.8
Jaylen Brown J. Brown SG BOS
86
34.8 22.9 4.6 6 1.2 0.3 2.6 1.4 1.8 5.9 4 5.3 2.5 28.9
Norman Powell N. Powell SG LAC
79
32 22.7 2.1 3.4 1.3 0.2 2 0.4 3.1 7.4 4 4.8 1.8 26.7
Jaren Jackson Jr. J. Jackson Jr. PF MEM
84
29 22.4 2.1 5.7 1.2 1.6 2.2 1.2 1.9 5.2 4.3 5.6 3.4 28.9
James Harden J. Harden SG LAC
88
34.7 22.3 8.8 5.9 1.5 0.7 4.4 0.7 3 8.7 6.5 7.4 2.1 29.7
Brandon Ingram B. Ingram SF TOR
87
32.6 22.2 5.2 5.6 0.9 0.6 3.8 0.9 2.4 6.4 2.6 3.1 2.5 30.8
DeMar DeRozan D. DeRozan SF SAC
88
35.5 22.2 4.3 3.9 0.8 0.4 1.4 0.6 1.1 3.3 4.8 5.5 1.9 24.8
Ja Morant J. Morant PG MEM
94
29.5 22.2 7.4 3.9 1.2 0.3 3.7 0.5 1.5 5.2 5.5 6.5 2.2 31.7
Jamal Murray J. Murray PG DEN
85
35.8 21.6 6.1 3.9 1.4 0.5 2 0.7 2.4 6 3.3 3.8 2 24.1
Jalen Green J. Green SG HOU
81
33.1 21.6 3.4 4.6 0.8 0.3 2.4 0.6 3 8.5 3.4 4.2 1.6 27.5
Jalen Williams J. Williams SF OKC
71
32 21.4 5.3 5.4 1.7 0.7 2.2 0.8 1.8 5.1 3.3 4.2 2.4 26.8
Brandon Miller B. Miller SF CHA
67
33.7 21.4 3.6 4.8 1.1 0.7 2.7 1 4 10.8 2.6 3 2.8 28.2
Trey Murphy III T. M. III SF NO
76
34.3 21.4 3.7 5.1 1.1 0.7 2 0.9 3 8.1 3.9 4.4 2.1 24
RJ Barrett R. Barrett SG TOR
85
32.3 21.4 5.4 6.4 0.8 0.2 2.9 1 1.9 5.3 3.4 5.4 2.5 28.5
CJ McCollum C. McCollum PG NO
84
32.1 21 4.2 3.8 0.8 0.5 1.9 0.7 3 8.2 2.2 3.2 2.2 27.3
Miles Bridges M. Bridges SF CHA
81
31.8 21 3.8 7.8 0.8 0.7 2.1 1.2 2.4 7.1 3.6 4.2 1.5 27.6
Pascal Siakam P. Siakam PF IND
87
32.4 20.8 3.4 7 0.9 0.5 1.5 1.7 1.7 4.3 3 4.1 2.6 24.8
Darius Garland D. Garland PG CLE
88
30 20.8 6.6 2.8 1.2 0.2 2.4 0.6 2.9 7.1 3 3.4 2 27.5
Jordan Poole J. Poole PG WAS
84
29.4 20.6 4.4 3.1 1.3 0.4 3.1 0.5 3.5 9.2 3.6 4.1 3 29.1
Coby White C. White SG CHI
75
32.8 20.3 4.5 3.6 0.9 0.2 2.3 0.3 3 8.3 3.5 3.9 2.1 24.6
Kawhi Leonard K. Leonard SF LAC
95
30.1 19.9 3 5.6 1.5 0.5 2 1 2 5 2.3 3 1.5 28.1
Scottie Barnes S. Barnes SF TOR
83
33 19.6 5.9 7.8 1.5 1 2.9 1.7 1.2 4.5 3.8 4.9 1.9 27.2

What to Know About NBA Player Stats

NBA player stats shine a spotlight on individual performances, revealing how each athlete contributes to their team’s success (or struggles). Beyond raw points and rebounds, advanced metrics like Player Efficiency Rating (PER), True Shooting Percentage (TS%), and Usage Rate help paint a nuanced picture of a player’s value. By examining these numbers in the context of roster fit and game strategy, you can uncover insights that a simple box score might not provide.

Staying current on player stats is essential for bettors, DFS enthusiasts, and fantasy managers. Even a short-term scoring surge can signal a bigger breakout if paired with rising usage rates or better shooting efficiency. Conversely, a player putting up impressive numbers on unsustainably hot shooting may regress in the near future. Consistently monitoring these patterns will keep you ahead of casual observers who rely only on headline performances.

Metrics and Methodologies

Different analysts lean on various statistical frameworks to evaluate NBA players. Traditional box-score stats—points, rebounds, assists—offer a quick read, but advanced metrics provide a deeper dive. For instance, PER (Player Efficiency Rating) summarizes a player’s per-minute productivity, while Win Shares estimate how much an individual contributes to team victories. Plus-Minus and On/Off metrics show how a squad fares with or without a certain player on the court.

Additionally, shot-tracking data (e.g., shot charts, catch-and-shoot percentages) can reveal whether a player thrives off dribble penetration or excels in spot-up opportunities. Understanding which metrics drive a player’s perceived value helps you evaluate if their production is sustainable or matchup dependent. You can also look at **defensive** advanced stats—like Defensive Box Plus-Minus (DBPM) or Deflections—to gauge impact beyond highlight plays.

Strength of Competition

While some players rack up gaudy numbers against weaker opposition, others maintain strong efficiency even when facing top-tier defenses. Evaluating player performance in marquee matchups—like prime-time games or clashes against elite defenders—can clarify whether recent output is merely a product of soft matchups. A guard who lights up a poor perimeter defense might struggle against a physical, well-coordinated unit, so factoring in quality of competition is key.

This context also matters for situational stats. Clutch scoring (points in the final five minutes of close games) and efficiency under pressure provide clues about a player’s poise. Similarly, game tempo impacts raw numbers; a fast-paced opponent can inflate counting stats like points and rebounds. Adjust your assessment by considering how each player’s skill set meshes with the pace and defensive style of the teams they face.

Injuries and Roles

Player stats can fluctuate dramatically when key teammates are sidelined, offering increased usage for the healthy ones. A second option might temporarily become the primary scorer, boosting shot attempts and point totals. Conversely, a player who thrives off a certain teammate’s playmaking could see his own production dip if that teammate is out. Tracking roster health and changes in starting lineups helps you interpret short-term statistical spikes or slumps.

Depth charts also factor in. A deep team can spread around touches, capping individual stats, while a top-heavy roster may feature players with sky-high usage rates. By recognizing which situations boost or reduce a player’s stat production, you can adapt your fantasy and betting strategies accordingly. Look for evidence—like increased pick-and-roll possessions or more isolation sets—to validate whether a stat bump truly reflects an expanded role.

How Player Stats Impact Betting

Player stats heavily influence prop bets (e.g., total points, rebounds, assists) and can affect broader markets like point spreads or over/unders. If a star is on a hot streak, sportsbooks may inflate their scoring line, potentially creating opportunities for savvy bettors who see signs of regression. On the flip side, a player stepping into a bigger role might be undervalued if the public hasn’t caught on to emerging trends.

Bettors often correlate a team’s success with a player’s statistical output—e.g., if a particular guard consistently dominates weaker perimeter defenders, taking the over on points (and possibly the team’s overall scoring) could be profitable. Monitoring how stats shift when the player faces elite defenses or tough road environments can help you gauge the true odds of repeating a strong performance.

Analyzing Over/Under Potential

Prop bets for points, assists, or rebounds typically hinge on a player’s recent output and average usage. If a forward’s rebounding numbers spike after an injury to the team’s starting center, oddsmakers may eventually catch up, but there’s often a lag. Capitalizing on that gap can net quick gains—especially if advanced metrics show that the forward’s rebound rate is sustainable (e.g., an uptick in box-outs or contested rebound percentages).

Conversely, if a perimeter scorer’s three-point percentage is skyrocketing due to favorable matchups, you might expect a dip against stronger wing defenders, making the under a tempting proposition. Tracking shot selection—like attempts at the rim vs. mid-range jumpers—also reveals how stable a player’s efficiency might be moving forward.

Identifying Breakout or Slump Alerts

Short-term stats can be deceptive. A player might average 25 points over a week on unsustainably hot shooting or feast on subpar defenses. By reviewing advanced data—like shot quality or free throw rate—you can determine whether a breakout is legitimate or a mirage. If a guard’s assist totals jump due to inflated minutes, that uptick may not last when the rotation normalizes.

Alternatively, a mild slump in scoring could hide other improvements, such as a higher assist percentage or lower turnover rate, signaling an eventual return to form once the shooting regresses to the mean. Spotting these underlying trends before the betting public does can yield value across the prop markets. It can also help you avoid overreacting to superficial cold streaks or surges.

Best Sportsbook Promos for NBA Betting

When you leverage player stats to spot favorable prop bets or lines, sportsbook promos can enhance your potential returns. Common offers include odds boosts, risk-free bets, or parlay boosts that multiply your winnings if you combine multiple prop wagers. Such promos help offset risk if a hot-shooting guard reverts to the mean sooner than you anticipated.

Late-Shifting Player Stats: How They Affect DFS & Props

Player stats aren’t static—they can spike if a veteran rests, or dip if a key ball-handler returns from injury. DFS prices and prop lines may not adjust quickly enough, creating windows of opportunity. If a newcomer thrives in an expanded role, their DFS salary might remain low for a game or two, and prop bets could undervalue their scoring or rebounding potential. Conversely, a returning star’s presence could siphon touches from a bench scorer, deflating that player’s fantasy value.

Matching your predictions against real-time data is crucial. If a player’s usage climbs in the first quarter, indicating the coach has shifted more offense through them, in-game DFS swaps or live prop bets might be especially appealing. Being nimble and informed can amplify your edge.

Matchup-Driven DFS Insights

Some players thrive against specific defensive schemes. For example, a pick-and-roll maestro might feast on teams lacking disciplined rim protection, while a spot-up shooter could excel if a defense overcommits on help rotations. Reviewing a player’s track record against various lineups can reveal under-the-radar DFS gems—like a backup forward who punishes smaller lineups.

Additionally, check synergy data for two-man lineups. If a center consistently sees increased touches whenever a certain playmaking guard is on the floor, that synergy could boost daily fantasy returns. You can also monitor game pace: players reliant on fast-break points or transition threes may underperform in grind-it-out matchups.

Live Betting and Changing Dynamics

As a game progresses, foul trouble or in-game injuries may thrust bench players into bigger roles. A scorer who typically sees 25 minutes might get 35 if the starter picks up early fouls. Recognizing such shifts early can yield profit on real-time props—like total points or rebounds for the newly elevated player.

On the other hand, a star might get shut down if the score margin becomes lopsided, minimizing second-half production. Savvy bettors and DFS managers track these in-game developments, balancing a player’s upside with the risk of limited minutes. If you anticipate blowouts, consider focusing on the role players who benefit from extended garbage-time usage.

Using Player Stats for Season-Long Fantasy

Season-long fantasy basketball hinges on player performance over weeks and months, making it vital to track evolving stats. A shooter stuck in a slump might be a prime buy-low target if advanced metrics suggest their form remains solid. Meanwhile, a bench player climbing the depth chart could maintain expanded minutes all season if they keep delivering consistent per-minute production.

Factor in roster construction too. If you’re heavy on scorers but lack assists, seeking out players who’ve upped their playmaking duties (perhaps due to a coaching adjustment) can balance your categories. The best fantasy managers blend short-term momentum with long-term trends in advanced stats to create a balanced yet dynamic roster.

Identifying Sleeper Players

A second-year forward or rookie guard can break out when their team shapes a new offensive system around their strengths. By comparing raw box scores with advanced data—like Usage Rate or Assist Percentage—you might detect a future star’s upward trajectory. If their improvement coincides with lineup changes or an injury to a teammate, you have a chance to scoop them off waivers before the rest of your league notices.

Be mindful, however, of short-term anomalies. Sometimes high shooting percentages or inflated block rates are unsustainable. Dig into shot-location data or defensive scheme influences to verify whether that production is likely to continue. If you sense regression, consider selling high via trade offers while the hype is strong.

Reacting to Coaching & Rotation Changes

Coaches regularly shuffle lineups to spark better results, which can drastically shift player stats. An athletic wing transitioning from the bench to the starting five might see a jump in scoring if they pair well with the lead guard, while a high-usage bench scorer might lose touches next to a ball-dominant superstar. Keeping tabs on local beat reporters and postgame quotes can give you an early heads-up when a coach plans to alter rotations.

Those who spot rotation changes first can exploit them in fantasy. For instance, if a marginal role player is rumored to get starter-level minutes, a speculative add could pay dividends if the coach’s plan stays intact. Conversely, a once-solid contributor might fade if their coach shifts them to a diminished role in favor of a defensive specialist.

Balancing Schedule and Player Stats

Hot or cold streaks sometimes correspond to a series of matchups against specific defensive styles. If you see that a guard’s recent scoring surge came against teams weak in perimeter defense, they might slow down against tougher wing stoppers. Evaluate upcoming schedules to gauge which streaks could sustain or fizzle.

In deeper leagues, slight scheduling advantages—like extra back-to-back sets—can boost a fringe player’s cumulative stats over a week. If you notice a high-tempo opponent coming up, you might stash a bench big who’s adept at collecting boards in transition-heavy contests. Awareness of both schedule quirks and a player’s underlying skill set maximizes your fantasy roster’s efficiency.

Why Player Stats Matter

NBA player stats extend far beyond the scoreboard, revealing nuances of a player’s role, efficiency, and impact that casual fans might overlook. Interpreting these metrics effectively can elevate your strategy in betting markets, DFS competitions, and fantasy leagues. By factoring in advanced statistics, you uncover patterns that signal growth or regression, allowing you to make decisions rooted in data rather than hype.

A star’s flashy scoring average might obscure defensive liabilities or poor shot selection, while a seemingly modest stat line could hide an elite role player who excels in efficiency or secondary creation. By peeling back the layers of raw totals, you gain clarity about each player’s contributions—and how those might evolve under shifting team dynamics. Staying curious and up-to-date on advanced player metrics is key to keeping pace in the ever-evolving NBA.

Historically Elite Players

Some NBA legends delivered staggering stat lines that stood the test of time, either through sheer volume or unmatched efficiency. Their success often stemmed from a combination of skill, opportunity, and a system tailored to their strengths. Modern-day analytics can illuminate why these icons were so dominant and how their methods might translate—or not—in today’s game.

Michael Jordan (1986–87 Season)

  • Why His Stats Stood Out: Jordan averaged over 37 points per game while posting an elite True Shooting Percentage. He also led his team in steals, showcasing a two-way mastery rarely seen.
  • Key Takeaway: MJ’s ability to create his own shot—and convert at high efficiency—exemplified scoring excellence. Even advanced analytics back up his remarkable usage-to-production ratio, underscoring his role as the ultimate go-to option.

Jordan’s athleticism and scoring instincts were complemented by a relentless drive that propelled him in clutch situations. Modern analytics highlight his killer mid-range game and innate knack for drawing defenders, fueling assists and open shots for teammates. By studying his shot distribution and pacing, today’s analysts glean insights into how unwavering confidence and skill can shape an all-time great’s statistical profile.

Stephen Curry (2015–16 Season)

  • Why His Stats Stood Out: During his unanimous MVP campaign, Curry shattered the single-season three-point record and led the league in scoring, often resting in fourth quarters due to blowouts.
  • Key Takeaway: Curry’s deep-range shooting not only boosted his own point totals but also stretched defenses to unprecedented levels, creating lanes for teammates. Advanced metrics, like offensive Real Plus-Minus, pegged him as a transformative force in spacing.

His scorching efficiency from beyond the arc, combined with high-volume attempts, redefined how teams approach perimeter defense. Modern shot-tracking data shows how Curry’s gravity bent defensive schemes, opening up easy cuts and short rolls for the Warriors’ supporting cast. This synergy underlines how one player’s unique skill can drastically reshape on-court dynamics and transform a franchise into a juggernaut.