CricGuardian: Injury risk prediction system

Abstract: Cricket broke the calendar. Test matches stretching five days, ODIs cramming action into fifty overs, T20 exploding every few hours—same bodies, different torture. Players fly between continents, sleep in airports, recover in planes. Knees, backs, hamstrings—these don't care about broadcast schedules. Injuries happen. Teams lose stars, careers end early, fans wonder what could've been. Current fix? Wait until something hurts, then treat. Physio rubs where it aches, coach rests who limps. Reacti ve, late, often too late. We built something that sees trouble coming. Machine learning model—Random Forest, if you want the technical— trained on how workload actually breaks bodies. Recent bowling overs, sprint distances, gym hours, sleep quality, travel miles, age, history of tweaks. Feeds in, spits out percentage: 15% risk this week, 63% next month if you don't rest. Not replacing physios. Giving them numbers they never had. Coach sees bowler hitting 80% risk, rotates early. Player feels fine, model disagrees, scans deeper, finds stress fracture brewing. Caught before it breaks.

Keywords: Injury Prediction, Sports Analytics, Machine Learning, Random Forest, Workload Management, Cricket.