Software Engineering Meets AI Innovation

Challenge

Coaching staff relied on fragmented data from multiple vendors. No unified view of player performance, injury risk, or optimal lineups. Manual analysis took 20+ hours per week.

Solution

Built a real-time analytics dashboard that ingests data from GPS trackers, heart rate monitors, video feeds, and game stats. Implemented ML models for injury prediction and optimal substitution recommendations.

Results

• • 18% increase in team win rate
• • 31% reduction in player injuries
• • 20+ hours saved per week in data analysis
• • Real-time insights during games

Challenge

Teams used a mix of text messages, emails, and paper playbooks. Communication breakdowns led to confusion. No way to track if players reviewed assignments. Offline access was critical.

Solution

Developed an offline-first React Native app with secure team messaging, interactive playbook viewer, video breakdown tools, and read receipts. Built admin portal for coaches to manage content and track engagement.

Results

• • 12+ hours saved per week on communication
• • 100% playbook review compliance
• • Zero missed assignments due to communication errors
• • Used by 50+ professional teams

Challenge

Scouts manually reviewed hundreds of hours of game footage. Subjective evaluations led to inconsistent player ratings. No way to compare players across different leagues and competition levels.

Solution

Built a computer vision system that automatically tags plays, tracks player movements, and generates performance metrics. Implemented AI models to predict player development and fit within team systems.

Results

• • 90% reduction in video review time
• • Identified 14 draft prospects that outperformed their rank
• • Standardized evaluation across 200+ scouts
• • Improved draft success rate by 27%

Challenge

Coordinators spent 30+ hours per week studying film and creating game plans. Play-calling decisions were based on gut feel rather than data. No way to quickly adapt to in-game adjustments.

Solution

Developed a system that ingests game film, play-by-play data, and down-distance situations. Built LLM-based agent that suggests plays based on opponent weaknesses, personnel matchups, and historical success rates.

Results

• • 23% increase in offensive efficiency
• • 15+ hours saved per week in game planning
• • Real-time play recommendations during games
• • Higher conversion rate on 3rd downs

Challenge

Revenue data was siloed across multiple systems. No visibility into fan lifetime value or marketing ROI. Pricing decisions were based on intuition rather than data.

Solution

Built a data warehouse integrating CRM, ticketing, POS, and social media platforms. Developed ML models for attendance forecasting, dynamic pricing, and customer segmentation. Created executive dashboards with real-time revenue metrics.

Results

• • 41% increase in revenue per fan
• • Dynamic pricing increased ticket revenue by $2.3M
• • Identified top 10% of fans driving 60% of revenue
• • Optimized marketing spend with 5x ROI

Challenge

Fans had limited interaction beyond attending games. Low engagement during off-season. No direct communication channel with the fan base.

Solution

Developed a React Native app with live voting, behind-the-scenes content, augmented reality features, and rewards program. Integrated push notifications for personalized engagement based on fan preferences and behavior.

Results

• • 500K+ downloads in first 6 months
• • 35% increase in season ticket renewals
• • 3x growth in merchandise sales through in-app store
• • 4.7/5 app store rating

Challenge

Generic product recommendations led to low engagement. Average conversion rate was 1.8%, below industry benchmarks.

Solution

Built collaborative filtering and content-based recommendation engines with A/B testing framework. Implemented real-time personalization based on browsing behavior, purchase history, and user segments.

Results

• • 127% increase in click-through rate
• • Conversion rate improved to 4.2%
• • Average order value up 31%
• • $3.7M additional revenue in first quarter

Challenge

Accounting team manually processed 5,000+ documents monthly. Data entry errors caused reconciliation issues and audit findings.

Solution

Implemented document classification, table extraction, and entity recognition using fine-tuned vision and language models. Built validation rules and exception handling workflows.

Results

• • 92% automation rate for standard documents
• • Processing time reduced by 76%
• • Data accuracy improved to 98.7%
• • Audit findings eliminated