Portland Trail Blazers Team Stats 2024-25 Blazers Team Stats

36-46, 4th in West Northwest

LAL 81 @ POR 109 Final

Final

The Portland Trail Blazers team stats page gives you a detailed look at how the team is performing across all key areas of the game. From scoring averages and shooting splits to defensive metrics and rebounding totals, this page offers everything you need to evaluate the Blazers' season. Whether you're analyzing matchups, tracking fantasy value, or following team trends, these stats keep you informed. For daily updates on who’s in the starting five, check out the latest Blazers lineup page.

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

Trail Blazers 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
78
86
70
110.9
13.4
23.8
15.1
40.5
90.2
37.7
12.9
45
34.2
76.2
98.3
113.9
31.4
26.2
8.3
5.3
47.1
36.1
14.5

Trail Blazers 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
16
11
4
22
2
27
29
24
9
15
19
26
26
26
17
15
27
13
11
8
20
16
7

Trail Blazers 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 PHX +11 None 0 109 0 0 0 0 94 42 49 15 30.6 44.7 36 12 48 30 13
12/13/24 SAS +3.5 0 0 116 0 0 0 0 82 42 41 16 39 51.2 28 8 36 25 13

Trail Blazers 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 PHX -11 0 0 116 0 0 0 0 89 43 39 15 38.5 48.3 34 12 46 23 4 6
12/13/24 SAS -3.5 None 0 118 0 0 0 0 85 44 30 14 46.7 51.8 28 13 41 32 5 9

Trail Blazers Team Leaders

Points Per Game
J. Grant
J. Grant: 0
J. Walker: 0
T. Camara: 0
S. Cissoko: 0
K. Murray: 0
Assists Per Game
J. Grant
J. Grant: 0
D. Ayton: 0
A. Simons: 0
R. Williams III: 0
D. Reath: 0
Rebounds Per Game
J. Grant
J. Grant: 0
J. Walker: 0
T. Camara: 0
S. Cissoko: 0
K. Murray: 0
Steals Per Game
M. Thybulle
M. Thybulle: 2.2
T. Camara: 1.5
S. Henderson: 1
T. Moore: 1
D. Avdija: 1
Blocks per Game
M. Thybulle
M. Thybulle: 0
D. Banton: 0
S. Cissoko: 0
D. Reath: 0
R. Rupert: 0

Trail Blazers Player Stats

NAME RTG MINS PTS AST REB STL Blk TO FG% FGM 3PTM 3PA 3P% FTM FTA FT%
Anfernee Simons
81
32.7 19.3 4.8 2.7 0.9 0.1 2 42.6 6.8 3.1 8.5 36.3 0 2.5 2.8 90.2
Toumani Camara
67
32.7 11.3 2.2 5.8 1.5 0.6 1.4 45.8 4.2 1.7 4.6 37.5 0 1.2 1.6 72.2
Jerami Grant
83
32.4 14.4 2.1 3.5 0.9 1 1.4 37.3 4.6 2.3 6.3 36.5 0 3 3.5 84.9
Shaedon Sharpe
71
31.3 18.5 2.8 4.5 0.9 0.2 2.1 45.2 6.9 2 6.6 31.1 0 2.6 3.4 78.5
Deandre Ayton
86
30.1 14.4 1.6 10.2 0.8 1 1.7 56.6 6.6 0.1 0.8 18.8 0 1 1.5 66.7
Deni Avdija
77
30 16.9 3.9 7.2 1 0.5 2.7 47.6 5.6 1.7 4.8 36.5 0 4 5.2 78
Scoot Henderson
67
26.7 12.7 5.1 3 1 0.2 2.7 41.9 4.3 1.6 4.5 35.4 0 2.4 3.1 76.7
Matisse Thybulle
78
20.8 7.5 1.9 3.5 2.2 0.6 0.9 47.7 2.8 1.4 3.2 43.8 0 0.5 1 46.7
Donovan Clingan
67
19.7 6.5 1.1 7.9 0.5 1.6 1.1 53.9 2.7 0.2 0.7 28.6 0 0.9 1.6 59.6
Robert Williams III
86
17.6 5.8 1.1 5.9 0.7 1.6 0.8 64.1 2.5 0.1 0.1 33.3 0 0.8 0.8 88.2
Dalano Banton
71
16.7 8.3 2.4 2 0.6 0.5 1.3 39.1 3 1.1 3.3 32.4 0 1.4 1.9 72.8
Kris Murray
67
15.1 4.2 1 2.6 0.5 0.2 0.6 41.9 1.7 0.4 1.7 22.5 0 0.4 0.8 45.6
Jabari Walker
67
12.5 5.2 0.6 3.5 0.6 0.1 0.6 51.5 2 0.5 1.2 38.9 0 0.8 1.2 69
Duop Reath
67
10.2 4.2 0.6 2 0.3 0.3 0.3 42.2 1.5 0.7 2.3 32.1 0 0.4 0.5 90.9
Taze Moore
67
9.5 3 0.5 4 1 0 1 20 1 0.5 2 25 0 0.5 1 50
Rayan Rupert
67
8.8 3 0.5 1.3 0.3 0.1 0.6 40.8 1.1 0.3 1.1 27.1 0 0.4 0.6 76.7
Justin Minaya
67
5.3 0.9 0.4 0.5 0.3 0.1 0.3 38.1 0.4 0.1 0.5 20 0 0 0.1 0
Sidy Cissoko
67
5.2 1.5 0.7 1 0.1 0 0.5 43.3 0.6 0.1 0.6 23.1 0 0.1 0.4 33.3
Bryce McGowens
69
2.5 1 0.2 0.2 0.1 0 0.3 28.6 0.3 0 0.3 0 0 0.4 0.5 83.3

Portland Trail Blazers Stats: A Data-Driven Analysis

The Portland Trail Blazers use advanced analytics to optimize their gameplay and improve overall efficiency. Every aspect of their performance—from shooting percentages and offensive pace to defensive metrics and turnovers—is meticulously tracked. This data-centric approach provides fans, bettors, DFS players, and fantasy managers with deep insights into the Blazers’ impact on the court.

Pre-Game Lineup and Statistical Projections

Typically announced about 30 minutes before tip-off, the Trail Blazers’ starting lineup offers an early glimpse into expected production in points, rebounds, and efficiency ratings. With key players like Damian Lillard, CJ McCollum, and Anfernee Simons leading the team, even slight lineup modifications can cause significant shifts in crucial metrics. Real-time updates alongside historical data empower informed decisions for betting and DFS.

Load Management and Minute Allocation Metrics

Effective minute management is essential to maintaining peak performance for the Blazers over a long season. Advanced metrics such as usage rate, player efficiency rating (PER), and average minutes per game reveal how the coaching staff strategically allocates time to balance rest and productivity. These insights help predict which players might see an increase in minutes during critical matchups, guiding smarter wagering and DFS strategy.

Injury Impact and Real-Time Data Adjustments

When injuries or last-minute lineup changes occur, the Blazers’ statistical models quickly update key metrics such as effective field goal percentage (eFG%) and defensive efficiency. The depth of the roster means that quality substitutes can step in, and real-time injury reports facilitate rapid recalibration of projections. Bettors and fantasy managers benefit from these timely adjustments, which uncover potential value when key players are unavailable.

Matchup Analysis and Defensive Efficiency

Portland’s defensive performance is quantified with advanced statistics like opponent shooting percentages and overall defensive ratings. Detailed matchup analyses—examining how the Blazers contest on-ball screens, limit scoring opportunities, or disrupt pick-and-roll plays—offer granular insights into their defensive impact. This analytical approach goes beyond traditional box scores, providing a clearer picture for predicting game flow and individual performances.

Rotation Depth and Bench Contribution Metrics

The depth of the Blazers’ rotation is assessed through key statistics such as bench scoring averages, per-minute output, and second-unit plus-minus ratings. Coach Terry Stotts’ (or current coach’s) decisions on deploying bench players are reflected in these numbers, highlighting their impact on overall team performance and momentum shifts. Thorough analysis of bench contributions is essential for live betting and DFS strategies, revealing opportunities that might be missed by conventional stats.

Data-Backed Betting Strategies for Blazers Games

Leveraging detailed statistical trends from the Blazers’ gameplay offers a robust framework for smart betting decisions. Metrics such as pace of play, turnover ratios, and shooting efficiencies are integral to projecting point spreads and identifying value in player prop bets. Comparing current performance with historical trends enables bettors to pinpoint discrepancies before market adjustments occur, turning raw numbers into strategic advantages.

Player Performance and Positional Splits

Detailed evaluations using metrics like true shooting percentage (TS%), PER, and usage rate shed light on the contributions of key Blazers players in various matchups. For instance, assessing Damian Lillard’s performance against elite defenses provides insight into his scoring and playmaking potential. These objective, data-driven measures create a solid framework for refining prop bets and overall wagering strategy.

Trend Analysis: Scoring, Efficiency, and Game Flow

Long-term trends in scoring averages, shooting percentages, and on/off splits build a strong predictive foundation for future Blazers performances. Integrating historical data with current metrics reveals patterns of consistency, improvement, or decline before betting lines shift. 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 Blazers’ overall performance. These continuously updated models are invaluable for real-time betting and DFS decisions, converting complex data into clear, actionable insights. Advanced analytics provide the measurable edge necessary to forecast both individual contributions and team outcomes accurately.

Identifying Value in Bench and Role Player Contributions

While star players often capture the headlines, the statistical impact of the Blazers’ bench is equally important. Secondary metrics like bench scoring averages and efficiency ratings reveal the contributions of role players that can affect game momentum. Recognizing these contributions through detailed data analysis can uncover opportunities for both live betting and DFS strategies that traditional stats might overlook.

Best Sportsbook Promotions for Blazers Betting

To complement your data-driven betting strategy for Blazers games, take advantage of sportsbook promotions offering risk-free bets and odds boosts. These promotions are designed to work in tandem with real-time performance metrics and lineup updates, providing additional value for your wagers. Monitoring these dynamic offers can further optimize your betting returns as updated analytics are released.

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Late Lineup Changes and Their Statistical Impact

Last-minute adjustments and unexpected load management decisions can significantly alter the Blazers’ statistical projections. Advanced models rapidly update key metrics—such as offensive efficiency and points per possession—when roster changes occur. Bettors and fantasy managers can use these real-time updates to fine-tune their strategies on the fly. Accurate, data-driven responses to late-breaking news are crucial for capturing emerging betting opportunities.

Data-Driven Adjustments to Moneylines and Spreads

When a pivotal player is unexpectedly sidelined, sportsbooks 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 that you catch these updates as soon as they happen, enabling precise betting decisions.

Impact on Game Totals and Player Prop Projections

Changes in the starting lineup often prompt a re-evaluation of expected scoring outputs, influencing both overall game totals and individual player prop bets. Updated advanced statistics illustrate how substitutions can impact the pace and offensive output of the game. Meticulous tracking of these fluctuations allows for precise adjustments to your betting strategy on totals and props, revealing value even in volatile market conditions.

Capitalizing on Market Overreactions with Advanced Analytics

Occasionally, the betting market overreacts to sudden lineup changes, leading to temporary mispricing of key statistical contributions. Advanced analytics help identify these discrepancies by comparing updated data with historical benchmarks. Swift, data-driven responses to such market inefficiencies can yield significant profit opportunities. Detailed trend analysis enables you to pinpoint undervalued bets before the market readjusts.

DFS Success with a Focus on Advanced Data

Constructing winning DFS lineups for the Blazers begins with an in-depth 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 building a competitive roster. Leveraging comprehensive analytics gives your DFS lineup a measurable edge.

Prioritize Players with High Usage and Efficiency Metrics

Core Blazers players, such as Lillard and McCollum, are evaluated not only on scoring outputs but also on efficiency metrics like TS% and PER, which highlight their overall impact. Building your DFS roster on proven, data-backed performers creates a stable foundation with minimal risk. Their consistent production and reliable minute allocations ensure a robust core for your lineup. An analytical approach to these performance indicators is key to achieving DFS success.

Matchup Analysis Grounded in Quantitative Data

Evaluating opponent defensive ratings, historical head-to-head data, and other advanced metrics helps pinpoint the most favorable matchups for DFS success. Quantitative comparisons reveal which teams struggle defensively against the Blazers, guiding smarter player selections. Detailed, numbers-driven analysis uncovers opportunities that traditional evaluations might miss, 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 game scenarios, and travel fatigue are quantifiable and significantly influence 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.

Portland Trail Blazers Rotations and Season-Long Fantasy Insights

In season-long fantasy basketball, maintaining consistent rotations and stable minute distributions is fundamental for a competitive roster. Long-term trends and detailed evaluations of individual performance provide critical guidance for drafting and roster management decisions. Monitoring minute averages alongside key efficiency metrics enables fantasy managers to anticipate performance fluctuations and adjust their teams proactively. Data-driven insights empower smarter, long-term fantasy strategies.

Assessing Rotational Stability Through Consistent Metrics

The core rotation of the Blazers is reflected in steady usage rates and consistent efficiency statistics from key players. Continuous tracking of performance metrics offers a reliable baseline for long-term fantasy success, highlighting predictable contributions throughout the season. This ongoing monitoring supports strategic planning and 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 Blazers’ roster. These metrics help identify undervalued role players who can significantly contribute when given extra minutes, especially during injuries or lineup rotations. Thorough analysis of bench data provides a competitive edge in season-long fantasy play.

Proactive Roster Management with Real-Time Data

Maintaining a competitive fantasy team requires constant monitoring of real-time statistics, including minute fluctuations and efficiency updates. Adjusting your roster based on the most up-to-date data enables 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, with regular adjustments based on current metrics.