San Antonio Spurs Team Stats 2024-25 Spurs Team Stats

34-48, 4th in West Southwest

TOR 118 @ SA 125 Final

Final

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.

Home Record: 0-0 Away Record: 0-0 Conference Record: 0-0 Division Record: 0-0

Spurs Team Stats

Team Ratings Offense Stats Defense Stats
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

Spurs Team Rankings

Team Rankings Offense Rankings Defense Rankings
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

Spurs Team Offensive Stats

Opponent Vegas Points Scored Shooting Rebounding Assists TO
Date Team Spread ML O/U TOT PTS Q1 PTS Q2 PTS Q3 PTS Q4 PTS FGA FGM 3PTA 3PTM 3PT% FG% DREB OREB TOT REB TOT ASS TO
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

Spurs Team Defensive Stats

Opponent Vegas Points Allowed Shooting (Allowed) Rebounding (Allowed) AST Allow Defensive
Date Team Spread ML O/U TOT PTS Q1 PTS Q2 PTS Q3 PTS Q4 PTS FGA FGM 3PTA 3PTM 3PT% FG% DREB OREB TOT REB TOT ASS BLK STL
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

Spurs Team Leaders

Points Per Game
H. Barnes
H. Barnes: 0
C. Paul: 0
H. Ingram: 0
S. Castle: 0
V. Wembanyama: 0
Assists Per Game
H. Barnes
H. Barnes: 0
C. Paul: 0
B. Biyombo: 0
D. Fox: 0
J. McLaughlin: 0
Rebounds Per Game
H. Barnes
H. Barnes: 0
C. Paul: 0
H. Ingram: 0
S. Castle: 0
V. Wembanyama: 0
Steals Per Game
D. Fox
D. Fox: 1.5
C. Paul: 1.3
D. Vassell: 1.3
V. Wembanyama: 1.1
S. Castle: 0.9
Blocks per Game
D. Fox
D. Fox: 0
C. Paul: 0
M. Branham: 0
D. Duke Jr.: 0
J. McLaughlin: 0

Spurs Player Stats

NAME RTG MINS PTS AST REB STL Blk TO FG% FGM 3PTM 3PA 3P% FTM FTA FT%
De'Aaron Fox
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
Victor Wembanyama
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
Devin Vassell
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
Chris Paul
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
Harrison Barnes
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
Stephon Castle
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
Jeremy Sochan
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
Keldon Johnson
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
Julian Champagnie
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
Bismack Biyombo
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
Blake Wesley
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
Sandro Mamukelashvili
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
Charles Bassey
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
Malaki Branham
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
Jordan McLaughlin
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
Harrison Ingram
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
Riley Minix
67
6 0 0 2 0 0 0 0 0 0 1 0 0 0 0 0
David Duke Jr.
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

San Antonio Spurs Stats: A Data-Driven Analysis

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.

Pre-Game Lineup and Statistical Projections

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.

Load Management and Minute Allocation Metrics

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.

Injury Impact and Real-Time Data Adjustments

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.

Matchup Analysis and Defensive Efficiency Metrics

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.

Rotation Depth and Bench Contribution Metrics

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.

Data-Backed Betting Strategies for Spurs Games

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.

Player Performance and Positional Splits

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.

Trend Analysis: Scoring, Efficiency, and Game Flow

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.

Leveraging Advanced Analytics for Outcome Prediction

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.

Identifying Value in Bench and Role Player Contributions

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.

Best Sportsbook Promotions for Spurs Betting

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.

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Late Lineup Changes and Their Statistical Impact

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.

Data-Driven Adjustments to Moneylines and Spreads

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.

Impact on Game Totals and Player Prop Projections

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.

Capitalizing on Market Overreactions with Advanced Analytics

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.

DFS Success with a Focus on Advanced Data

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.

Prioritize Players with High Usage and Efficiency Metrics

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.

Matchup Analysis Grounded in Quantitative Data

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.

Optimizing DFS with Contextual and Situational Metrics

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.

San Antonio Spurs Rotations and Season-Long Fantasy Insights

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.

Assessing Rotational Stability Through Consistent Metrics

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.

Evaluating Roster Depth with Advanced Bench Metrics

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.

Proactive Roster Management with Real-Time Data

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.