Coaching Portfolio
Demonstrating how data-informed thinking enhances player development and competitive preparation
Coaching Philosophy
My approach centers on data-informed development and systems thinking. I believe in building long-term growth through integrated film study, fundamental skill development, and statistical context.
Core Principles
Athletes learn best when they understand both the "what" and the "why"—combining technical coaching with analytical insights creates more autonomous, intelligent players who can adapt and problem-solve in competition.
Modern coaching requires balancing quantitative analysis with qualitative observation, using data to identify patterns and opportunities while maintaining focus on individual athlete development and team culture.
Applied Data Integration
- Video Analytics: Every practice and match is tagged and analyzed for pattern recognition
- Statistical Context: Player performance is evaluated against appropriate benchmarks and situational expectations
- Development Tracking: Long-term progression monitoring using objective metrics combined with qualitative assessment
- Competitive Preparation: Scouting reports blend statistical tendencies with qualitative observations from film study
The goal is creating athletes who are technically sound, strategically intelligent, and equipped with the analytical framework to continue their own development beyond our structured training environment.
Opponent Scouting Reports
Scouting Methodology
My scouting process combines statistical analysis, video breakdown, and pattern recognition to provide actionable intelligence for match preparation.
Statistical Foundation
- Rotation Analysis: Attack efficiency by rotation and setter position
- Serve Receive Patterns: Passing quality mapped to serve zones and types
- Out-of-System Tendencies: Second-ball attack distributions and success rates
- Key Player Metrics: Individual hitter tendencies by court zone and set type
Video Analysis Integration
Statistical data is cross-referenced with film study to identify:
- Shot Selection Patterns: Decision-making under pressure
- Defensive Systems: Blocking schemes and floor coverage
- Transition Efficiency: Quick attack and out-of-system options
- Situational Tendencies: Clutch performance and momentum shifts
Sample Scouting Structure
Pre-Scout: Data Collection
- Recent Matches: Last 5 matches vs similar competition
- Statistical Baselines: Season averages and conference comparisons
- Individual Tendencies: Player-by-player statistical profiles
Film Study Confirmation
- Pattern Verification: Confirm statistical trends in actual game footage
- Contextual Factors: Environmental and situational influences
- Intangible Factors: Body language, communication, team chemistry
Game Planning Application
- Strategic Objectives: Primary and secondary goals by rotation
- Specific Targets: Serving patterns, blocking schemes, defensive assignments
- Adjustment Triggers: In-match indicators for tactical changes
Deliverables
Each scouting report includes:
- Statistical Summary: 2-page quantitative overview
- Video Clips: Timestamped examples of key tendencies
- Game Plan: Specific strategies for each rotation
- Scouting Sheets: Reference guides for in-match coaching decisions
This comprehensive approach ensures our game planning is data-driven while maintaining flexibility for in-match adjustments.
Video & Recruiting Materials
Video Analysis Capabilities
My video analysis workflow combines traditional film study with modern analytical tools to provide comprehensive insights for player development and strategic planning.
Technical Setup
Equipment & Software Stack:
- Primary software: DataVolley for comprehensive scouting
- Video analysis: Hudl + custom Python scripts for pattern recognition
- Visualization: Tableau for statistical dashboards, Adobe Premiere for highlight reels
- Data integration: Custom APIs linking video timestamps with statistical databases
Video Analysis Process
1. Comprehensive Tagging System
# Video tagging framework
def tag_rally_actions(video_segment, rally_data):
"""Link video segments with statistical data"""
tags = {
'technical': ['serve_technique', 'approach_footwork', 'arm_swing'],
'tactical': ['shot_selection', 'court_positioning', 'transition'],
'physical': ['explosiveness', 'vertical_jump', 'recovery_time'],
'mental': ['decision_making', 'clutch_performance', 'communication']
}
for action in rally_data:
video_clip = extract_clip(video_segment, action.timeline)
annotate_clip(video_clip, action.analysis)
link_to_database(video_clip, action.metadata)
return tagged_library
2. Pattern Recognition
- Serve reception patterns: Passer movement tendencies and success rates by zone
- Attack distribution: Hitter shot selection vs block positioning
- Transition efficiency: Time from block touch to next attack initiation
- Defensive systems: Floor coverage patterns and dig success probabilities
Player Development Tracking
Before/After Analysis Framework
Each player development cycle includes:
Initial Assessment (Week 0)
## Player: Sarah Johnson (OH, Class of 2026)
### Technical Baseline
- **Approach**: Inconsistent footwork, 78% efficiency
- **Arm Swing**: Limited snap-through, 65% kill rate
- **Blocking**: Poor timing, 0.8 blocks/set
### Physical Metrics
- **Vertical**: 28 inches (below average for position)
- **Agility**: 4.8s pro agility (average)
- **Endurance**: 65% intensity maintenance through match
### Goals for Development Cycle
1. Improve approach consistency to 90%+ efficiency
2. Increase kill rate to 75%+
3. Develop 2-step blocking timing improvement
4. Add 3 inches to vertical jump
Progress Tracking (Week 6)
- Video comparison: Side-by-side technical analysis
- Statistical validation: Performance metrics improvement
- Qualitative assessment: Coach and player feedback integration
- Adjustment planning: Refinement of development strategy
Development Sample Compilation
Standard deliverable for each player:
## Development Package: 12-Week Cycle
### Technical Progress
- **Approach efficiency**: 78% → 91% (+13%)
- **Kill percentage**: 65% → 77% (+12%)
- **Blocking average**: 0.8 → 1.4 blocks/set (+75%)
### Physical Improvements
- **Vertical jump**: 28" → 31" (+3")
- **First-step quickness**: 0.2s improvement
- **Match endurance**: 85% intensity maintenance
### Video Evidence
- **Technical clips**: 15 before/after comparisons
- **Match application**: 8 in-game examples
- **Progressive training**: Weekly development snapshots
### Analytics Integration
- **Statistical validation**: 500+ rally analysis
- **Peer comparison**: Percentile rankings improvement
- **Scalability**: Projected DI performance metrics
Recruiting Video Production
Professional Highlight Reels
Standard Package Structure:
- Opening sequence: Player profile and key statistics
- Technical showcase: 15-20 quality touches by skill
- Competitive moments: High-pressure situations and clutch plays
- Athletic display: Physical capabilities and explosiveness
- Academic/character: Interview clips and academic achievements
Advanced Analytics Integration
# Recruiting video analytics
def generate_recruiting_metrics(player_highlights):
"""Extract objective metrics from recruiting footage"""
metrics = {
'attack_efficiency': calculate_attack_stats(highlights),
'blocking_reading': analyze_blocking_anticipation(highlights),
'serve_velocity': measure_serve_speed(highlights),
'defensive_range': calculate_cover_area(highlights),
'athletic_markers': extract_jump_and_speed_metrics(highlights)
}
return compare_to_d1_averages(metrics)
Sample Deliverables
Complete Recruiting Package
6-Video Series + Analytics Dashboard:
Skills Showcase (4 minutes)
- High-quality repetitions of all 6 skills
- Technical analysis with slow-motion breakdowns
- Statistical validation of effectiveness
Match Performance (5 minutes)
- High-pressure situations and clutch performances
- Strategic decision-making examples
- Team leadership and communication
Athletic Profile (3 minutes)
- Physical testing and measurements
- Explosiveness and agility demonstrations
- Comparative analysis against position averages
Development Journey (3 minutes)
- 12-month progress documentation
- Before/after technical improvements
- Training regimen and work ethic display
Academic Character (2 minutes)
- Academic achievements and classroom performance
- Leadership activities and community involvement
- Interview clips and communication skills
Reference Integration (1 minute)
- Coach testimonials and recommendations
- Teammate perspectives on work ethic
- Academic advisor endorsements
Data Integration Dashboard
Each video package includes:
- Interactive analytics: Clickable segments with detailed stats
- Performance tracking: Historical progression visualizations
- Comparative analysis: Positional rankings and percentile scores
- Predictive modeling: Projected collegiate performance
Quality Assurance Process
Technical Validation Steps:
- Shot selection verification: Ensure highlights represent typical performance
- Statistical accuracy: Cross-reference video with recorded statistics
- Contextual relevance: Include game situations, not just practice footage
- Professional production: Broadcast-quality video and audio
- Compliance verification: NCAA recruiting rule adherence
This comprehensive approach ensures recruiting videos provide authentic, data-validated insights into player capabilities and potential for collegiate success.