Men's CBB- Player Projections
College Basketball Player Projections
Player | Team | PTS | REB | AST | 3PM | BLK | STL | TO | PRA | PR | PA | DFS | Matchup |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
M. Collins | USU | 18.5 | 3.4 | 2.2 | 2.4 | 0.2 | 0.5 | 2.1 | 24.1 | 21.9 | 20.7 | 29.6 | USU vs. USF |
M. Falslev | USU | 17.6 | 7.3 | 2.5 | 1.5 | 0.3 | 2.6 | 3.1 | 27.5 | 25.0 | 20.2 | 39.1 | USU vs. USF |
J. Omojafo | USF | 15.5 | 5.2 | 2.3 | 1.1 | 0.4 | 1.1 | 1.6 | 23.0 | 20.7 | 17.8 | 29.6 | USU vs. USF |
C. Brown | USF | USU vs. USF | |||||||||||
W. Enis | USF | USU vs. USF | |||||||||||
I. Nelson | USF | USU vs. USF | |||||||||||
S. Brown | DAV | CIT vs. DAV | |||||||||||
N. Chitikoudis | RMU | RMU vs. GB | |||||||||||
G. Clark | USU | USU vs. USF | |||||||||||
B. Williams | CIT | CIT vs. DAV | |||||||||||
J. Pinion | USF | USU vs. USF | |||||||||||
N. Coval | DAV | CIT vs. DAV | |||||||||||
C. Moore | CIT | CIT vs. DAV | |||||||||||
K. Templin | USU | USU vs. USF | |||||||||||
J. Scovens | DAV | CIT vs. DAV | |||||||||||
T. Dorset | MRMK | RID vs. MRMK | |||||||||||
D. Goode | RMU | RMU vs. GB | |||||||||||
D. Brown | DAV | CIT vs. DAV | |||||||||||
K. King | USU | USU vs. USF | |||||||||||
P. Friedrichsen | DAV | CIT vs. DAV |
Player projections may be limited due to college basketball data coverage.
How Our College Basketball Projections Work
Dimers’ projections for college basketball players give you a clear, data-backed edge for the 2025–26 season. Covering every major team and conference, our model updates throughout the day, factoring in form, opponent tendencies, and lineup changes to help you make informed fantasy and betting calls.
Our projections turn raw data into straightforward insights, helping you understand where value and opportunity exist before tip-off.
Data Sources & Model Factors
The model draws from box scores, advanced metrics, and team efficiency data. Each player’s historical output, pace of play, and opponent context are integrated into a machine-learning system designed specifically for college basketball. The result is a transparent projection built from accurate, up-to-date information across the NCAA landscape.
Position & Matchup Adjustments
Defensive schemes and talent levels vary widely in college hoops. Dimers’ model weighs defense-versus-position performance for each opponent, revealing when a player is primed to excel against weaker coverage or may face tougher conditions against elite defenses. These matchup layers add depth beyond surface-level stats.
Injury & Roster Changes
Lineups in college basketball can shift fast—injuries, suspensions, and eligibility updates can all reshape a team’s rotation. Dimers tracks verified sources to keep player minutes, usage rates, and projections current, so your decisions stay based on the latest, most reliable data.
What's Included in Our CBB Player Projections?
Our sortable projections table makes it easy to find actionable stats for any player, team, or conference:
- Points: Estimated scoring output based on efficiency, usage, and matchup.
- Rebounds: Projected totals influenced by pace and team rebound rates.
- Assists: Distribution potential informed by offensive structure and trends.
- Other Stats: Steals, blocks, and turnovers are vital for DFS and prop bettors.
Use Cases for College Basketball Projections
DFS and Fantasy
- Build Stronger Lineups: Identify undervalued players and high-ceiling matchups in daily fantasy contests.
- Long-Term Strategy: Use projections to guide NCAA fantasy roster moves across the season.
- Player Props and Parlays: Find edges when usage, pace, or matchup data point toward performance swings.
- Over/Under Efficiency: Analyze tempo and team style to anticipate statistical outcomes.
- Hidden Value: Uncover mid-major players poised to outperform expectations.
Research and Analysis
- Historical Trends: Access player data for advanced metrics or scouting projects.
- Matchup Breakdowns: Compare performance against ranked teams or specific defensive profiles.
Our Coverage and Updates
Dimers covers the major NCAA conferences—ACC, Big Ten, Big 12, SEC, Pac-12, and select mid-majors. Projections update multiple times daily, with a particular focus on pre-tip-off accuracy as new lineup information and results come in. Every update reflects the latest data so you can stay one step ahead.
Why Dimers’ CBB Player Projections Stand Out
Built In-House
Our projections are created from raw data using proprietary logic built for college basketball. No recycled or aggregated sources—just original insights you can trust.
Consistently Updated
The machine-learning engine recalibrates with new performances throughout the season, keeping projections aligned with team form and market trends. The more the season evolves, the sharper our data gets.
Get Started with College Basketball Player Projections
- Browse Projections: View projected points, rebounds, assists, and more.
- Customize the Table: Filter by team, conference, or date.
- Export Data: Download for offline analysis or integration with DFS and betting tools.
- Check Back Daily: Updates roll out across the day as news and data change.
Responsible Gambling
Dimers supports responsible and balanced betting habits. Set deposit and stake limits, manage your bankroll, and recognize when to take a break. If you or someone close to you needs help, visit our responsible gambling resources for confidential support. Enjoy the game, stay informed, and always bet within your means.
Do you have more questions about our CBB player projections? Our team is here to help -reach out today.
Which college basketball teams or conferences are covered?
We focus on all major NCAA conferences (ACC, Big Ten, Big 12, SEC, Pac-12) and select mid-major teams with robust data availability.
How often are player projections updated during the NCAA season?
We refresh the table multiple times a day, especially when new game data becomes available or breaking news affects a player’s status.
Can I download college basketball player data for my own analysis?
Absolutely. We offer a one-click export to CSV, so you can run custom analyses, build your own projections, or fine-tune DFS lineups.
Do you provide projections for smaller conferences or just major programs?
We mainly cover top conferences and key players in mid-major programs, but will expand coverage as data becomes available.