The Charlotte Hornets team stats page offers a complete breakdown of the team's performance across all major statistical categories. From scoring efficiency and assist numbers to defensive metrics and rebounding totals, this page gives you everything you need to analyze the Hornets’ play. Whether you're following player development, managing a fantasy team, or studying matchup trends, these stats provide valuable insight. For daily updates on starters, visit the latest Hornets lineup page.
Team Ratings | Offense Stats | Defense Stats | ||||||||||||||||||||||
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Overall | OFF RTG | DEF RTG | PPG | ORB | AST | TO | FGM | FGA | 3PA | 3-PM | FG% | 3PT% | FT% | Pace | PPG Allow | DRB | AST Allow | STL | BLK | FG% Allow | 3P% Allow | FORCE TO | ||
70 | 70 | 70 | 105.1 | 12.2 | 24.3 | 14.9 | 38.3 | 89.1 | 38.3 | 13 | 43 | 33.9 | 78.3 | 97.2 | 114.2 | 33 | 26.8 | 7.4 | 4.5 | 46.7 | 35.5 | 12.4 |
Team Rankings | Offense Rankings | Defense Rankings | ||||||||||||||||||||||
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Overall | OFF RTG | DEF RTG | PPG | ORB | AST | TO | FGM | FGA | 3PA | 3-PM | FG% | 3PT% | FT% | Pace | PPG Allow | DRB | AST Allow | STL | BLK | FG% Allow | 3P% Allow | FORCE TO | ||
27 | 29 | 5 | 30 | 6 | 26 | 27 | 28 | 19 | 11 | 18 | 30 | 28 | 14 | 21 | 16 | 17 | 16 | 26 | 21 | 16 | 9 | 24 |
Opponent | Vegas | Points Scored | Shooting | Rebounding | Assists | TO | ||||||||||||||
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| | | | | | | | | | | | | | | | | | | | |
12/16/24 | PHI | +2.5 | 0 | 0 | 108 | 0 | 0 | 0 | 0 | 83 | 42 | 38 | 12 | 31.6 | 50.6 | 29 | 9 | 38 | 30 | 20 |
12/13/24 | CHI | +5.5 | None | 0 | 95 | 0 | 0 | 0 | 0 | 98 | 35 | 46 | 8 | 17.4 | 35.7 | 37 | 17 | 54 | 22 | 16 |
Opponent | Vegas | Points Allowed | Shooting (Allowed) | Rebounding (Allowed) | AST Allow | Defensive | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| | | | | | | | | | | | | | | | | | | | | |
12/16/24 | PHI | -2.5 | None | 0 | 121 | 0 | 0 | 0 | 0 | 80 | 41 | 38 | 16 | 42.1 | 51.2 | 33 | 9 | 42 | 21 | 8 | 12 |
12/13/24 | CHI | -5.5 | 0 | 0 | 109 | 0 | 0 | 0 | 0 | 93 | 37 | 51 | 14 | 27.5 | 39.8 | 38 | 14 | 52 | 27 | 5 | 7 |
| | | | | | | | | | | | | | | | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 67 | 34.2 | 21 | 3.6 | 4.9 | 1.1 | 0.7 | 2.8 | 40.3 | 7.3 | 3.9 | 10.9 | 35.5 0 | 2.5 | 2.9 | 86.1 |
| 86 | 32 | 25.2 | 7.4 | 4.9 | 1.1 | 0.3 | 3.6 | 40.5 | 8.6 | 3.8 | 11.2 | 33.9 0 | 4.1 | 4.9 | 84.3 |
| 81 | 31.7 | 20.3 | 3.9 | 7.5 | 0.7 | 0.7 | 2.1 | 43.1 | 7.3 | 2.2 | 7 | 31.3 0 | 3.5 | 4 | 87 |
| 73 | 29.9 | 10.4 | 2.3 | 5.1 | 1.1 | 0.8 | 1.8 | 43.9 | 3.4 | 1.7 | 4.6 | 36.5 0 | 1.9 | 2.3 | 83.8 |
| 74 | 27.8 | 7.4 | 1.6 | 2.5 | 1.1 | 0.2 | 1 | 42.8 | 2.6 | 1.4 | 3.6 | 39.1 0 | 0.7 | 1.1 | 68.1 |
| 73 | 26.6 | 15.2 | 2.5 | 10.2 | 0.7 | 1.2 | 1.6 | 60.4 | 6.1 | 0 | 0.1 | 0 0 | 3 | 3.7 | 80.4 |
| 67 | 24.7 | 7.3 | 3.7 | 3.3 | 1 | 0.1 | 2.1 | 32.3 | 2.8 | 0.8 | 3.7 | 21.4 0 | 0.9 | 1 | 86.7 |
| 74 | 24.5 | 14.1 | 3 | 2.9 | 0.5 | 0.3 | 1.9 | 43.5 | 5.4 | 1.8 | 4.6 | 40 0 | 1.5 | 1.6 | 90.5 |
| 67 | 23.4 | 7.8 | 3.1 | 3 | 0.9 | 0.2 | 1.6 | 34.6 | 2.9 | 0.9 | 3.6 | 25.4 0 | 1.1 | 1.4 | 82 |
| 67 | 22.8 | 6.7 | 1.1 | 2.9 | 0.6 | 0.5 | 0.7 | 40.5 | 2.5 | 1.2 | 3.5 | 33.5 0 | 0.5 | 0.6 | 80 |
| 67 | 22.8 | 9.8 | 2.4 | 2.1 | 0.3 | 0.1 | 1.4 | 39.1 | 3.7 | 1.7 | 5.1 | 34 0 | 0.7 | 0.8 | 93.5 |
| 81 | 20.8 | 8.9 | 2.3 | 7.8 | 0.8 | 0.7 | 1.9 | 47.7 | 3.3 | 0.6 | 2.1 | 30.5 0 | 1.7 | 2.5 | 66.4 |
| 67 | 20.7 | 5.9 | 1.2 | 4.7 | 0.5 | 0.2 | 1 | 33 | 1.9 | 1 | 3.4 | 28.3 0 | 1.1 | 1.6 | 71.3 |
| 68 | 19.8 | 7 | 3.2 | 1.5 | 0.8 | 0.5 | 1.5 | 40.7 | 2.8 | 0.8 | 2 | 37.5 0 | 0.8 | 1 | 75 |
| 67 | 18.5 | 7 | 2 | 1 | 0.5 | 0.2 | 1.3 | 42.9 | 2 | 1 | 2.5 | 40 0 | 2 | 2.5 | 80 |
| 68 | 17.5 | 5.7 | 0.8 | 6.2 | 0.6 | 0.6 | 0.9 | 59.6 | 2.4 | 0 | 0.1 | 0 0 | 1 | 1.6 | 59.5 |
| 79 | 15.6 | 6.5 | 0.9 | 1.7 | 0.4 | 0.1 | 0.5 | 47.8 | 2.4 | 1.2 | 2.7 | 45.6 0 | 0.5 | 0.6 | 84.6 |
| 70 | 15.6 | 7.1 | 0.8 | 2.8 | 1.2 | 0.5 | 0.8 | 44.3 | 2.4 | 0.8 | 2.3 | 34.8 0 | 1.6 | 2.1 | 74.1 |
| 70 | 13.8 | 4.2 | 1.2 | 2.6 | 0.6 | 0.1 | 0.8 | 46.8 | 1.6 | 0.4 | 1.1 | 34.1 0 | 0.5 | 0.6 | 81.8 |
| 67 | 13.2 | 6 | 1.4 | 1.6 | 0.6 | 0 | 0.9 | 39 | 2 | 0.7 | 1.6 | 39.4 0 | 1.2 | 1.7 | 73.5 |
| 75 | 11 | 2.9 | 0.6 | 3.2 | 0.2 | 0.5 | 0.7 | 49.5 | 1.3 | 0 | 0.1 | 50 0 | 0.3 | 0.5 | 60 |
| 75 | 10.8 | 4 | 1.8 | 1.8 | 0.8 | 0 | 1 | 38.5 | 1.2 | 0.2 | 1 | 25 0 | 1.2 | 1.5 | 83.3 |
Contents
The Charlotte Hornets are increasingly relying on advanced analytics to refine their game strategies and improve overall performance. Every play is broken down through detailed metrics—from shooting efficiency to pace of play—providing fans, bettors, DFS players, and fantasy managers with a deep understanding of the team's dynamics.
Approximately 30 minutes before tip-off, the Hornets reveal their starting lineup, offering early projections on points, rebounds, and efficiency ratings. Key players like LaMelo Ball, Terry Rozier, and Miles Bridges drive these numbers, and even small changes in the lineup can have a notable impact on the expected statistical output.
Effective minute management is critical for maintaining the Hornets’ performance over the long season. Advanced metrics such as usage rate, player efficiency rating (PER), and average minutes per game help indicate how the coaching staff allocates playing time, especially during heavy travel schedules or back-to-back games.
Injuries and last-minute scratches are quickly factored into the Hornets’ statistical models, which update key numbers like effective field goal percentage (eFG%) and defensive efficiency. Real-time injury updates, combined with recalibrated projections, provide essential insights that bettors and fantasy managers can use to adjust their strategies on the fly.
The Hornets’ defensive performance is quantified using advanced metrics such as opponent shooting percentages and overall defensive ratings. Detailed analyses of how Charlotte contests perimeter shots and disrupts pick-and-roll plays provide a clearer picture of their impact on game flow.
Charlotte’s rotation depth is evaluated through metrics like bench scoring averages, per-minute production, and second-unit plus-minus ratings. These statistics reveal how role players contribute throughout the game and are critical for assessing overall team performance and momentum shifts.
Advanced statistical trends from the Hornets’ gameplay create numerous opportunities for smart betting decisions. Metrics such as pace of play, turnover ratios, and shooting efficiencies provide the foundation for projecting points spreads and spotting value in player prop bets.
Detailed evaluations using metrics like true shooting percentage (TS%), PER, and usage rate shed light on individual contributions. For example, analyzing LaMelo Ball’s performance against top defenses can highlight his scoring and playmaking potential, providing an objective basis for refining betting selections.
Reviewing long-term trends in scoring averages, shooting percentages, and on/off splits forms a solid foundation for predicting future performance. Combining historical data with current metrics helps to identify consistent patterns or shifts, offering valuable insight before betting lines adjust.
Incorporating sophisticated metrics such as Player Impact Estimate (PIE), plus-minus ratings, and pace-adjusted statistics deepens your understanding of the Hornets’ performance. These dynamic models continuously update with in-game data and convert complex numbers into actionable insights that enhance your betting and DFS strategies.
While star players often capture the headlines, the contributions from the Hornets’ bench are crucial for a complete statistical picture. Secondary metrics like bench scoring averages and efficiency ratings reveal the often-underappreciated impact of role players, providing opportunities for live betting and DFS adjustments.
Enhance your data-driven betting strategy by taking advantage of sportsbook promotions that offer risk-free bets and odds boosts. These promotions complement real-time performance metrics and lineup updates, adding extra value to your wagers.
Last-minute adjustments and unexpected load management decisions can significantly alter the Hornets’ statistical projections. Advanced models rapidly update key metrics like offensive efficiency and points per possession when lineup changes occur. Bettors and fantasy managers can leverage these real-time updates to fine-tune their strategies on the fly. Swift, data-driven responses to late-breaking news are essential for capitalizing on emerging betting opportunities.
When a key player is unexpectedly ruled out, sportsbooks recalibrate moneylines and point spreads based on the latest statistical insights. These adjustments reflect shifts in team efficiency and production, opening up new opportunities for wagering. Continuous real-time data monitoring ensures you catch these changes as they occur, enabling you to act with precision.
Changes in the starting lineup often lead to a re-evaluation of expected scoring, influencing both overall game totals and individual player prop bets. Updated advanced stats illustrate how substitutions impact the pace and offensive output of the game. Meticulous tracking of these fluctuations enables fine-tuning of betting strategies on totals and props, revealing opportunities even in volatile market conditions.
Occasionally, the betting market overreacts to sudden lineup changes, resulting in temporary mispricing of key contributions. Advanced analytics help identify these discrepancies by comparing current data with historical benchmarks. Swift, data-driven responses to such market inefficiencies can yield significant profit opportunities. Detailed trend analysis allows you to pinpoint undervalued bets before the market corrects itself.
Constructing winning DFS lineups for the Hornets begins with a deep dive into advanced statistics such as usage rates, effective field goal percentage, and per-minute production. A successful DFS strategy blends star power with role players whose high-efficiency metrics ensure consistent value. Continuous evaluation of both individual and team data is essential for assembling a competitive roster. Leveraging comprehensive analytics provides your DFS lineup with a measurable edge.
Core players like Trae Young are analyzed not only by their scoring outputs but also through efficiency metrics like TS% and PER, which underscore their overall value. Building your DFS roster on proven, data-backed performers sets a solid foundation with reduced risk. Their consistent production and reliable minute allocations ensure a stable core for your lineup. An analytical approach to these performance indicators is key to DFS success.
Evaluating opponent defensive ratings, historical head-to-head performance, and other advanced metrics helps identify the most favorable matchups for DFS. Quantitative comparisons illuminate which teams struggle defensively against the Hornets, guiding smarter player selections. Detailed, numbers-driven analysis uncovers opportunities that conventional evaluations might miss. A focus on objective data ensures that your DFS picks are both strategic and well-supported.
Situational factors such as home-court advantage, back-to-back games, and travel fatigue are quantifiable and directly affect player performance. Adjusting your DFS roster based on these contextual statistics helps optimize overall lineup efficiency. Incorporating these variables ensures that your selections are in line with real-time game conditions. A data-centric approach to situational analysis offers clear insights into potential performance shifts.
In season-long fantasy basketball, maintaining consistent rotations and stable minute distributions is crucial for building a competitive roster. Long-term trends and detailed evaluations of player performance guide drafting and roster management decisions. By monitoring minute averages alongside key efficiency metrics, fantasy managers can anticipate fluctuations and adjust their rosters accordingly. Data-driven insights empower smarter, long-term fantasy strategies.
The Hornets' core rotation is reflected in steady usage rates and consistent efficiency statistics from key players. Continuous tracking of performance metrics provides a reliable baseline for fantasy success over the season. These stable data points indicate predictable contributions that help with long-term planning. Ongoing monitoring is essential for understanding and forecasting rotational trends.
Beyond the starting lineup, advanced metrics such as bench scoring averages and plus-minus ratings reveal the overall depth of the roster. These statistics help identify undervalued role players who can boost fantasy value when given additional playing time. Monitoring bench contributions is especially important during injury periods or lineup changes. A thorough data analysis of roster depth offers a significant competitive edge in season-long fantasy play.
Maintaining a competitive fantasy team requires continuous monitoring of real-time statistics, including minute fluctuations and efficiency updates. Adjusting your roster based on the most recent data allows you to capitalize on emerging opportunities before they become widely recognized. A proactive, data-driven approach ensures that your team remains optimized throughout the season. Regular updates and prompt roster adjustments based on current metrics are critical for sustained fantasy success.