Toronto Raptors Team Stats 2024-25 Raptors Team Stats

30-52, 4th in East Atlantic

TOR 118 @ SA 125 Final

Final

The Toronto Raptors team stats page gives you a comprehensive look at how the squad is performing across all major statistical categories. From shooting efficiency and ball movement to defensive ratings and hustle stats, this page breaks down what’s driving the Raptors’ success or struggles. Whether you’re scouting matchups, betting trends, or fantasy opportunities, these numbers provide the insight you need. For the latest starting five info, head over to the Raptors lineup page.

Home Record: 18-23 Away Record: 12-29 Conference Record: 21-31 Division Record: 8-8

Raptors 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
80
77
110.9
12.6
28.5
14.7
41.6
91
34
11.8
45.8
34.8
74.8
99.6
115.2
32.5
25.9
8.1
4.2
46.6
34.9
14.2

Raptors 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
22
21
15
23
4
7
25
17
6
28
29
20
23
29
9
18
24
11
16
28
14
4
9

Raptors 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
12/16/24 CHI +1 0 0 121 0 0 0 0 92 45 26 9 34.6 48.9 34 10 44 28 18
12/12/24 MIA +10.5 None 0 104 0 0 0 0 92 41 32 11 34.4 44.6 33 9 42 29 11

Raptors 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
12/16/24 CHI -1 None 0 122 0 0 0 0 93 43 40 14 35 46.2 33 8 41 33 6 7
12/12/24 MIA -10.5 0 0 114 0 0 0 0 83 40 32 13 40.6 48.2 41 11 52 21 5 8

Raptors Team Leaders

Points Per Game
G. Temple
G. Temple: 0
B. Ingram: 0
U. Chomche: 0
J. Shead: 0
J. Mogbo: 0
Assists Per Game
G. Temple
G. Temple: 0
B. Ingram: 0
J. Poeltl: 0
C. Boucher: 0
R. Barrett: 0
Rebounds Per Game
G. Temple
G. Temple: 0
B. Ingram: 0
U. Chomche: 0
J. Shead: 0
J. Mogbo: 0
Steals Per Game
S. Barnes
S. Barnes: 1.4
J. Poeltl: 1.2
O. Agbaji: 0.9
B. Ingram: 0.9
J. Mogbo: 0.9
Blocks per Game
S. Barnes
S. Barnes: 0
J. Poeltl: 0
E. Omoruyi: 0
B. Fernando: 0
J. Battle: 0

Raptors Player Stats

NAME RTG MINS PTS AST REB STL Blk TO FG% FGM 3PTM 3PA 3P% FTM FTA FT%
Brandon Ingram
87
33.1 22.2 5.2 5.6 0.9 0.6 3.8 46.5 8.6 2.4 6.4 37.4 0 2.6 3.1 85.5
Scottie Barnes
83
32.8 19.3 5.8 7.7 1.4 1 2.8 44.6 7.3 1.2 4.3 27.1 0 3.5 4.6 75.5
RJ Barrett
85
32.2 21.1 5.4 6.3 0.8 0.3 2.8 46.8 7.9 1.8 5.3 35 0 3.4 5.4 63
Jakob Poeltl
77
29.6 14.5 2.8 9.6 1.2 1.2 1.9 62.7 6.4 0 0.1 33.3 0 1.7 2.5 67.4
Gradey Dick
67
29.4 14.4 1.8 3.6 0.9 0.2 1.5 41 4.9 2.1 6 35 0 2.5 2.9 85.8
Immanuel Quickley
76
27.8 17.1 5.8 3.5 0.7 0.1 1.8 42 5.6 2.6 6.8 37.8 0 3.4 3.9 86.7
Ochai Agbaji
72
27.2 10.4 1.5 3.8 0.9 0.5 0.8 49.8 4.2 1.6 4 39.9 0 0.5 0.8 70.8
Ja'Kobe Walter
67
21.2 8.6 1.6 3.1 0.8 0.2 1 40.5 3.1 1.2 3.6 34.9 0 1.3 1.6 79.5
Jonathan Mogbo
67
20.4 6.2 2.3 4.9 0.9 0.5 1.1 43.8 2.5 0.3 1.1 24.3 0 1 1.3 73.2
Jamal Shead
67
19.5 7.1 4.2 1.5 0.8 0.1 1.6 40.5 2.7 1 3 32.3 0 0.7 0.9 76.8
A.J. Lawson
67
18.7 9.1 1.2 3.3 0.5 0.2 0.6 42.1 3.1 1.3 3.9 32.7 0 1.7 2.4 68.3
Jamison Battle
67
17.6 7.1 0.9 2.7 0.3 0.2 0.5 42.9 2.5 1.8 4.4 40.5 0 0.3 0.3 88.9
Orlando Robinson
67
17.5 6.9 1.8 5 0.4 0.4 1.1 44.4 2.6 0.4 1.2 32.7 0 1.2 1.6 77.1
Chris Boucher
71
17.2 10 0.7 4.5 0.5 0.5 0.6 49.2 3.6 1.4 3.9 36.3 0 1.4 1.7 78.2
Cole Swider
68
16.9 5.9 0.3 2.7 0.4 0.2 0.4 34.9 2.2 1.5 4.7 31.9 0 0 0.1 0
Colin Castleton
67
16.6 4.7 1.1 4.7 0.3 0.4 0.9 46.9 1.8 0.1 0.6 12.5 0 1.1 1.5 76.3
Jared Rhoden
67
16.1 8.4 1.1 3 0.7 0.1 0.6 48.3 3 0.9 2.8 30.8 0 1.6 1.8 88
Bruno Fernando
72
8.6 3.4 1.1 3 0.2 0.5 0.8 53.1 1.5 0 0 0 0 0.4 0.5 75
D.J. Carton
67
8.2 0.8 0.8 1 0.5 0 1 14.3 0.2 0 0.8 0 0 0.2 0.2 100
Garrett Temple
69
8.1 1.9 1.1 1 0.6 0.1 0.4 30 0.6 0.2 1 21.4 0 0.4 0.4 91.7
Ulrich Chomche
67
4.6 0.7 0.3 1.1 0 0.1 0.3 40 0.3 0 0 0 0 0.1 0.3 50
Eugene Omoruyi
69
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Toronto Raptors Stats: A Data-Driven Analysis

The Toronto Raptors have built a reputation on speed, versatility, and smart analytics. Their game strategy is dissected by advanced metrics that reveal insights into shooting efficiency, pace, and defensive performance. For fans, bettors, DFS players, and fantasy managers, understanding the statistical nuances of the Raptors is key to unlocking their on-court impact.

Pre-Game Projections and Lineup Insights

Just before tip-off, the Raptors’ starting lineup is announced, providing early projections on points, rebounds, assists, and efficiency ratings. With core players like Pascal Siakam, Fred VanVleet, and OG Anunoby playing pivotal roles, even subtle lineup changes can significantly alter team stats. Real-time data from reputable sources allows you to benchmark these pre-game projections against historical performance, guiding more informed betting and DFS decisions.

Load Management and Minute Allocation Metrics

The Raptors emphasize effective minute management to maintain peak performance over the long season. Advanced metrics such as usage rate, player efficiency rating (PER), and minutes per game help quantify how rest and rotation adjustments impact overall production. Coaches use these insights to strategically allocate playing time during back-to-back games or taxing road trips. This data-driven approach helps predict which players will see changes in minutes, informing smarter wagering and fantasy lineup choices.

Injury Impact and Statistical Adjustments

Injuries and late scratches are factored into the Raptors’ performance models, quickly adjusting expectations like effective field goal percentage (eFG%) and defensive efficiency. The depth of the roster means that when a key player is unavailable, substitutes step in with measurable impact. Real-time injury updates integrated with statistical models assist bettors and fantasy managers in identifying emerging value among the role players. These recalibrated projections are essential for adapting your strategy on game day.

Matchup Analysis and Defensive Efficiency

Toronto’s defensive schemes are closely analyzed using advanced stats such as opponent shooting percentages and defensive ratings. By examining how the Raptors contest top scoring offenses and disrupt pick-and-roll plays, you gain a clearer picture of their defensive efficiency. This approach goes beyond traditional box scores by incorporating metrics like on-ball pressure and defensive switches. Such detailed analysis is invaluable for predicting both team outcomes and individual player contributions.

Rotation Depth and Bench Contribution Metrics

The Raptors’ rotation depth is measured by key statistics including bench scoring averages, per-minute output, and second-unit plus-minus ratings. Coach Nick Nurse’s strategic use of the bench is reflected in how these numbers influence game flow and momentum. Deep statistical analysis of bench contributions can highlight subtle shifts that affect overall performance, providing insights that support live betting and DFS decisions. Recognizing these trends helps underscore the importance of every roster spot.

Data-Backed Betting Strategies for Raptors Games

Advanced statistical trends from the Raptors’ gameplay open up valuable opportunities in various betting markets. Metrics such as pace of play, turnover rates, and shooting efficiencies help project points spreads and identify value in player prop bets. By comparing current performance data with historical trends, bettors can uncover disparities before market adjustments occur. This rigorous, data-driven approach transforms raw numbers into actionable betting strategies.

Player Performance Metrics and Positional Splits

Detailed evaluations using metrics like true shooting percentage (TS%), PER, and usage rates provide critical insights into how Raptors players perform against different defenses. For example, analyzing Siakam’s performance in high-pressure matchups can reveal his scoring potential and overall efficiency. These quantitative measures create an objective framework for assessing matchups and refining prop bets. Data-driven comparisons support more informed wagering decisions across the board.

Trend Analysis: Scoring, Efficiency, and Game Flow

By reviewing long-term trends in scoring averages, shooting percentages, and on/off splits, you can build a strong predictive foundation for upcoming games. Detailed statistical records help pinpoint patterns of consistency, regression, or improvement well before betting lines adjust. Historical data combined with current performance trends offers a reliable benchmark for assessing the Raptors’ game flow. This granular analysis is key to spotting emerging value in the betting market.

Leveraging Advanced Analytics for Outcome Prediction

Incorporating sophisticated metrics such as Player Impact Estimate (PIE), plus-minus ratings, and pace-adjusted statistics offers a deeper understanding of the Raptors’ overall performance. These models continuously update in real time, making them indispensable for both live betting and DFS decisions. Advanced analytics convert complex data sets into actionable insights, allowing you to anticipate game outcomes with greater accuracy. This comprehensive approach gives you a competitive edge in a dynamic market.

Unlocking Value in Bench and Role Player Contributions

While star players often dominate the headlines, the contributions of the Raptors’ bench are equally essential. Secondary metrics like bench efficiency and scoring averages provide a window into how role players can shift game momentum during key stretches. Recognizing the statistical impact of these contributions enhances both live betting strategies and DFS lineup optimizations. Detailed bench data often uncovers opportunities that traditional stats might overlook.

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To complement a data-driven betting strategy for Raptors games, be sure to capitalize on sportsbook promos offering risk-free bets and odds boosts. These promotions are designed to work in conjunction with real-time performance metrics and lineup updates. Monitor special offers that adjust with the latest data, giving you an added advantage. Such promos, when paired with detailed analytics, can amplify your potential returns.

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Late Lineup Changes and Their Statistical Impact

Last-minute adjustments and unexpected load management decisions can significantly alter the Raptors’ statistical projections. Advanced models rapidly update key metrics like offensive efficiency and points per possession when lineup changes occur. Bettors and fantasy managers can use these real-time updates to adapt their strategies on the fly. Accurate, data-driven responses to late-breaking news are essential for capitalizing on shifting market dynamics.

Data-Driven Adjustments to Moneylines and Spreads

When a critical player is unexpectedly sidelined, sportsbooks recalibrate moneylines and point spreads based on the latest statistical data. These adjustments reflect updated efficiency metrics and shifts in production, revealing fresh betting opportunities. Continuous data monitoring ensures that you catch these changes as soon as they occur. Real-time insights ensure that your wagering decisions are grounded in the most current information.

Impact on Game Totals and Player Prop Projections

Changes in the starting lineup often prompt a reassessment of expected scoring totals, impacting both overall game totals and individual player prop bets. Updated metrics illustrate how substitutions influence the game’s pace and offensive efficiency. Tracking these fluctuations allows you to refine your betting strategy with precision. Adaptive approaches anchored in detailed data create opportunities even in rapidly changing markets.

Capitalizing on Market Overreactions with Advanced Analytics

Sometimes the betting market overreacts to sudden lineup changes, leading to temporary mispricing of key contributions. Advanced analytics help identify these discrepancies by comparing updated figures with historical averages. Quick, data-driven responses to these market inefficiencies can result in substantial profit opportunities. Detailed trend analysis enables you to pinpoint undervalued bets before the market corrects itself.

DFS Success with a Focus on Advanced Data

Building winning DFS lineups for the Raptors starts 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 advanced metrics provide consistent value. Continuous evaluation of both individual and team data is essential to constructing a competitive roster. Leveraging these comprehensive statistics gives your DFS lineup a measurable edge.

Prioritize Players with High Usage and Efficiency Metrics

Key players like Siakam and VanVleet are evaluated not only on their scoring ability but also on efficiency metrics such as TS% and PER, underscoring their overall value. Building a DFS lineup on proven track records creates a reliable core. Their consistency in both production and minute allocation minimizes risk while maximizing potential returns. An analytical approach to these performance indicators lays the groundwork for DFS success.

Matchup Analysis Grounded in Hard Data

By evaluating opponent defensive ratings, historical head-to-head data, and other advanced metrics, you can identify the most favorable matchups for DFS success. Using data to pinpoint which teams struggle defensively against the Raptors informs smarter player selections. Detailed statistical comparisons reveal opportunities that may be missed with traditional analysis. A focus on objective numbers ensures your DFS picks are both strategic and well-supported.

Optimizing DFS with Situational and Contextual Metrics

Situational factors such as home-court advantage, back-to-back games, and travel fatigue are quantifiable and greatly affect player performance. Adjust your DFS roster based on these contextual statistics to optimize overall lineup efficiency. Incorporating these variables ensures that your selections are attuned to real-time game conditions. A data-centric approach to situational analysis provides clear insights into potential performance shifts.

Toronto Raptors Rotations and Season-Long Fantasy Insights

In season-long fantasy basketball, consistent rotations and reliable minute distributions are essential for maintaining a competitive roster. Long-term trends and detailed statistical evaluations of player performance are crucial for drafting decisions and roster management. By closely monitoring minute averages alongside efficiency metrics, fantasy managers can anticipate fluctuations and adjust their teams strategically. Data-driven insights empower more informed, long-term fantasy decisions.

Assessing Rotational Stability Through Consistent Metrics

The Raptors’ core rotation is underpinned by consistent usage rates and reliable efficiency statistics from their key players. Regular tracking of performance metrics from players like Siakam and Anunoby provides a dependable baseline for fantasy success. These stable data points highlight the predictability of contributions throughout the season. Continuous statistical monitoring is crucial to understanding and forecasting rotational trends.

Evaluating Roster Depth with Advanced Bench Metrics

Beyond the starting lineup, detailed metrics such as bench scoring averages and plus-minus ratings reveal the overall depth of the roster. These numbers help identify undervalued role players who can boost fantasy performance when given increased minutes. Monitoring bench contributions is especially important during periods of injury or lineup changes. Detailed data analysis of roster depth offers a competitive edge in season-long fantasy play.

Proactive Roster Management with Real-Time Data

Staying competitive in fantasy basketball demands continuous monitoring of real-time statistics, including minute shifts and efficiency updates. Quick roster adjustments based on the latest data allow you to capitalize on emerging trends before they become widely recognized. A proactive, data-driven approach ensures your team remains optimized throughout the season. Regular updates and prompt changes based on current metrics are key to sustaining fantasy success.