The San Antonio Spurs team stats page gives you a detailed look at how the team is performing across all major statistical categories. From offensive production and assist totals to defensive ratings and rebounding, this page highlights the key numbers behind the Spurs’ season. Whether you're tracking player development, analyzing fantasy value, or studying matchup trends, these stats deliver the insights you need. For daily starting lineup updates, visit the Spurs 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 | ||
72 | 76 | 71 | 113.9 | 10.9 | 28.6 | 13.3 | 41.8 | 89.8 | 39.6 | 14.1 | 46.5 | 35.7 | 77.4 | 98.8 | 116.7 | 32.7 | 28 | 8.2 | 5.5 | 47.4 | 36.5 | 12.8 |
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 | 20 | 6 | 16 | 18 | 6 | 15 | 14 | 16 | 7 | 9 | 17 | 19 | 21 | 14 | 23 | 21 | 23 | 12 | 5 | 23 | 22 | 20 |
Opponent | Vegas | Points Scored | Shooting | Rebounding | Assists | TO | ||||||||||||||
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| | | | | | | | | | | | | | | | | | | | |
12/15/24 | MIN | +4.5 | 0 | 0 | 92 | 0 | 0 | 0 | 0 | 91 | 37 | 45 | 11 | 24.4 | 40.7 | 38 | 12 | 50 | 34 | 18 |
12/13/24 | POR | -3.5 | None | 0 | 118 | 0 | 0 | 0 | 0 | 85 | 44 | 30 | 14 | 46.7 | 51.8 | 28 | 13 | 41 | 32 | 14 |
Opponent | Vegas | Points Allowed | Shooting (Allowed) | Rebounding (Allowed) | AST Allow | Defensive | |||||||||||||||
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| | | | | | | | | | | | | | | | | | | | | |
12/15/24 | MIN | -4.5 | None | 0 | 106 | 0 | 0 | 0 | 0 | 100 | 40 | 35 | 12 | 34.3 | 40 | 37 | 14 | 51 | 26 | 8 | 6 |
12/13/24 | POR | +3.5 | 0 | 0 | 116 | 0 | 0 | 0 | 0 | 82 | 42 | 41 | 16 | 39 | 51.2 | 28 | 8 | 36 | 25 | 6 | 5 |
| | | | | | | | | | | | | | | | |
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| 83 | 36.1 | 23.5 | 6.3 | 4.8 | 1.5 | 0.4 | 2.8 | 46.3 | 8.7 | 1.9 | 6.1 | 31 0 | 4.2 | 5.1 | 82.7 |
| 67 | 33.2 | 24.3 | 3.7 | 11 | 1.1 | 3.8 | 3.2 | 47.6 | 8.9 | 3.1 | 8.8 | 35.2 0 | 3.4 | 4.1 | 83.6 |
| 75 | 31 | 16.3 | 2.9 | 4 | 1.3 | 0.5 | 1.4 | 44.3 | 6.2 | 2.5 | 6.7 | 36.8 0 | 1.5 | 1.9 | 79.2 |
| 91 | 28 | 8.8 | 7.4 | 3.6 | 1.3 | 0.3 | 1.6 | 42.7 | 3 | 1.7 | 4.5 | 37.7 0 | 1 | 1.1 | 92.4 |
| 79 | 27.2 | 12.3 | 1.7 | 3.8 | 0.5 | 0.2 | 0.6 | 50.8 | 4.2 | 1.9 | 4.4 | 43.3 0 | 2 | 2.4 | 80.9 |
| 67 | 26.7 | 14.7 | 4.1 | 3.7 | 0.9 | 0.3 | 2.2 | 42.8 | 5.2 | 1.2 | 4.1 | 28.5 0 | 3.1 | 4.2 | 72.4 |
| 72 | 25.2 | 11.4 | 2.4 | 6.5 | 0.8 | 0.5 | 1.6 | 53.5 | 4.6 | 0.5 | 1.7 | 30.8 0 | 1.6 | 2.3 | 69.6 |
| 83 | 23.9 | 12.7 | 1.6 | 4.8 | 0.6 | 0.3 | 1 | 48.2 | 4.8 | 1.1 | 3.6 | 31.8 0 | 1.9 | 2.5 | 77.3 |
| 69 | 23.6 | 9.9 | 1.4 | 3.9 | 0.7 | 0.4 | 0.9 | 41.5 | 3.4 | 2.2 | 5.9 | 37.1 0 | 1 | 1.1 | 90.4 |
| 71 | 18.8 | 5.1 | 1.1 | 5.6 | 0.6 | 0.8 | 1 | 58.8 | 2.4 | 0 | 0 | 0 0 | 0.4 | 0.9 | 40 |
| 72 | 11.8 | 3.7 | 2 | 1.1 | 0.6 | 0.1 | 0.9 | 43.5 | 1.4 | 0.3 | 1 | 29.3 0 | 0.7 | 1.1 | 62.3 |
| 70 | 11.2 | 6.3 | 0.8 | 3.1 | 0.4 | 0.3 | 0.4 | 50.2 | 2.3 | 1 | 2.6 | 37.3 0 | 0.7 | 1 | 74.1 |
| 70 | 10.4 | 4.4 | 0.5 | 4.2 | 0.4 | 0.8 | 0.6 | 58.1 | 1.9 | 0 | 0 | 0 0 | 0.6 | 0.9 | 63.6 |
| 73 | 9.1 | 5 | 0.8 | 1.1 | 0.2 | 0 | 0.7 | 45.8 | 1.9 | 0.7 | 1.8 | 40.5 0 | 0.6 | 0.7 | 81.8 |
| 76 | 6.8 | 2.1 | 1.1 | 0.7 | 0.3 | 0 | 0.3 | 43.1 | 0.7 | 0.4 | 1 | 41.3 0 | 0.4 | 0.5 | 77.3 |
| 67 | 6.8 | 0.8 | 0.6 | 1.8 | 0.6 | 0 | 0.2 | 50 | 0.4 | 0 | 0.2 | 0 0 | 0 | 0 | 0 |
| 67 | 6 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 0 | 0 | 0 | 0 |
| 73 | 5.5 | 2.7 | 0.7 | 0.8 | 0.2 | 0 | 0.3 | 42.9 | 1 | 0.5 | 1 | 50 0 | 0.2 | 0.3 | 50 |
Contents
The San Antonio Spurs are renowned for their methodical, statistics-driven approach to the game. Every aspect—from shooting efficiencies and pace of play to defensive metrics and turnovers—is meticulously tracked. This data-centric perspective offers fans, bettors, DFS players, and fantasy managers deep insights into the Spurs’ performance and strategic execution.
Typically announced about 30 minutes before tip-off, the Spurs’ starting lineup provides early projections in areas such as points, rebounds, and efficiency ratings. With key players driving the team’s output, even slight changes in the lineup can result in notable shifts in advanced metrics. Real-time updates combined with historical performance data enable more informed betting and DFS decisions.
The Spurs have long been pioneers of efficient minute management. Advanced metrics like usage rate, player efficiency rating (PER), and average minutes per game reveal how the coaching staff strategically allocates playing time to sustain high performance. These data points help predict which players will see increased minutes in pivotal matchups, guiding smarter wagering and DFS strategies.
Injuries and last-minute lineup changes are swiftly integrated into the Spurs’ statistical models, updating metrics such as effective field goal percentage (eFG%) and defensive efficiency almost immediately. Quality substitutes step in to fill gaps, and real-time injury updates ensure that projections remain current. Bettors and fantasy managers benefit from these rapid recalibrations to uncover hidden value when key players are sidelined.
San Antonio’s defensive prowess is measured using advanced statistics, including opponent shooting percentages and overall defensive ratings. Detailed matchup analysis—examining how the Spurs contest pick-and-rolls or limit scoring opportunities—provides a granular view of their defensive impact. This analytical approach goes beyond traditional box scores, offering clearer insights into game flow and individual contributions.
The depth of the Spurs’ rotation is reflected in key statistics such as bench scoring averages, per-minute production, and second-unit plus-minus ratings. Coach Gregg Popovich’s disciplined approach to bench utilization is evident in these numbers, which highlight the role of reserve players in maintaining team momentum. Detailed analysis of bench contributions is invaluable for live betting and DFS strategies, revealing opportunities that might be overlooked by conventional statistics.
Leveraging advanced statistical trends from the Spurs’ gameplay offers a robust framework for smart betting decisions. Metrics such as pace of play, turnover ratios, and shooting efficiencies are critical for projecting point spreads and identifying value in player prop bets. By comparing current performance with historical data, bettors can uncover discrepancies that signal favorable wagering opportunities. A data-driven approach turns complex numbers into clear, strategic insights.
In-depth evaluations using metrics like true shooting percentage (TS%), PER, and usage rate illuminate the contributions of key Spurs players in various matchups. For example, analyzing how a standout guard performs against top-tier defenders can reveal his scoring potential and overall impact. These quantitative measures provide an objective foundation for refining prop bets and overall betting strategy.
Long-term trends in scoring averages, shooting percentages, and on/off splits form a strong predictive framework for future Spurs performances. By merging historical data with current metrics, patterns of consistency or change become evident before the betting lines adjust. This detailed trend analysis serves as a reliable benchmark for anticipating game flow and spotting emerging betting value.
Incorporating sophisticated metrics such as Player Impact Estimate (PIE), plus-minus ratings, and pace-adjusted statistics deepens the understanding of the Spurs’ performance dynamics. These continually updated models are invaluable for real-time betting and DFS decisions, translating complex data into actionable insights. Advanced analytics give you the measurable edge required to accurately forecast both individual contributions and overall team outcomes.
While star players often dominate headlines, the statistical impact of the Spurs’ bench is equally essential for a complete analysis. Secondary metrics such as bench scoring averages and efficiency ratings highlight the contributions of role players that can shift momentum. Recognizing these numbers through detailed data analysis can reveal live betting and DFS opportunities that might otherwise be overlooked.
To further enhance your data-driven betting strategy for Spurs games, consider sportsbook promotions that offer risk-free bets and odds boosts. These promotions are designed to align with real-time performance metrics and lineup updates, adding additional value to your wagers. Monitoring these dynamic offers can help maximize your betting returns as updated analytics become available.
Last-minute adjustments and unexpected load management decisions can significantly alter the Spurs’ statistical projections. Advanced models rapidly update key metrics—such as 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 critical for capturing emerging betting opportunities.
When a pivotal player is unexpectedly sidelined, sportsbooks quickly recalibrate moneylines and point spreads based on the latest statistical insights. These adjustments reflect shifts in team efficiency and overall production, unveiling new wagering opportunities. Continuous, real-time monitoring ensures you catch these updates as they occur, enabling precise betting decisions.
Changes in the starting lineup often necessitate a re-evaluation of expected scoring outcomes, influencing both overall game totals and individual player prop bets. Updated advanced statistics illustrate how substitutions affect the game’s pace and offensive output. Meticulous tracking of these fluctuations enables precise adjustments to your betting strategy on totals and props, revealing value even in dynamic market conditions.
Occasionally, the betting market overreacts to sudden lineup changes, resulting in temporary mispricing of key statistical contributions. Advanced analytics help identify these discrepancies by comparing current data with historical benchmarks. Quick, data-driven responses to market inefficiencies can yield significant profit opportunities. Detailed trend analysis enables you to pinpoint undervalued bets before the market corrects itself.
Constructing winning DFS lineups for the Spurs begins with a comprehensive analysis of advanced statistics such as usage rates, effective field goal percentage, and per-minute production. A successful DFS strategy blends star power with role players who consistently deliver high value based on key metrics. Continuous evaluation of both individual and team data is critical for assembling a competitive roster, giving your DFS lineup a measurable edge.
Core players are assessed not only on their scoring outputs but also on efficiency metrics like TS% and PER, underscoring their overall impact. Building your DFS roster on proven, data-backed performers creates a stable foundation with minimal risk. Their consistent production and predictable minute allocations form a robust core for your lineup. An analytical approach to these performance indicators is essential for achieving DFS success.
Evaluating opponent defensive ratings, historical head-to-head data, and other advanced metrics helps identify the most favorable matchups for DFS success. Quantitative comparisons reveal which teams struggle defensively against the Spurs, guiding smarter player selections. Detailed, numbers-driven analysis uncovers opportunities that traditional evaluations might overlook, ensuring 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 significantly affect player performance. Adjust your DFS roster based on these contextual statistics to optimize overall lineup efficiency. Incorporating these variables ensures that your selections align 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 vital for assembling a competitive roster. Detailed evaluations of individual performance and long-term trends guide drafting decisions and roster management. Monitoring minute averages alongside key efficiency metrics allows fantasy managers to anticipate fluctuations and adjust their teams proactively. Data-driven insights empower smarter, long-term fantasy strategies.
The Spurs’ core rotation is reflected in steady usage rates and consistent efficiency statistics from key players. Continuous tracking of performance metrics provides a dependable baseline for long-term fantasy success, highlighting predictable contributions throughout the season. This ongoing monitoring supports strategic planning and accurate forecasting of rotational trends.
Beyond the starting lineup, detailed bench statistics—such as scoring averages and plus-minus ratings—reveal the overall depth of the Spurs’ roster. These metrics help identify undervalued role players who can contribute significantly when given extra minutes, particularly during injuries or lineup changes. Comprehensive data analysis on roster depth offers a competitive edge in season-long fantasy play.
Maintaining a competitive fantasy roster requires constant monitoring of real-time statistics, including minute fluctuations and efficiency updates. Adjusting your lineup based on the most current data allows you to capitalize on emerging opportunities before they gain widespread attention. A proactive, data-driven approach ensures that your team remains optimized throughout the season, with regular updates and swift adjustments based on current metrics.