A 2025 study published in the International Journal of Sports Physical Therapy set out to quantify preseason throwing workload in nine collegiate pitchers using wearable IMU sensors strapped to their forearms. The researchers wanted to see if these athletes were following proper progressive overload principles during their six-week preseason training block. What they found was striking: the acute-to-chronic workload ratio exceeded 1.27 (the established injury risk threshold) during four of the six weeks. Week 4 was the only proper deload week, dropping to an ACWR of 0.79, significantly lower than Week 3's concerning 1.50 ratio. The pitchers averaged nearly 2,000 throws throughout the preseason, with weekly totals ranging wildly from 51 throws all the way up to over 700. On the surface, this looks like a textbook case of poor program design and excessive overload during a critical preparation period. But here's the thing: what if we're only seeing half the picture?

What The Study Found

The researchers tracked every throw these nine pitchers made during preseason training, using forearm-mounted inertial measurement units that captured angular velocity at 100Hz. Any movement exceeding 800 degrees per second was classified as a throw, which meant they captured everything from casual tosses to full-effort pitches from the mound. They calculated total workload by multiplying the median angular velocity for each day by the total number of throws, then used this to generate acute workload (seven-day average) and chronic workload (28-day rolling average). The acute-to-chronic workload ratio told them whether pitchers were ramping up too quickly compared to what their bodies had been exposed to over the previous month.

The results painted a concerning picture. Pitchers averaged 1,990 throws throughout the six weeks at an average angular velocity of 1,686 degrees per second. Acute workload was significantly reduced in Week 4 compared to both Week 2 and Week 3, with very large effect sizes. But here's the critical finding: ACWR exceeded the 1.27 danger threshold during weeks 1, 2, 3, and 5. Only Week 4, the single deload week, dropped below the injury risk zone with an ACWR of 0.79. The study concluded that preseason workload management needs serious improvement, suggesting that clinicians should monitor workload during preseason throwing to decrease the risk of chronic overuse injuries.

To be honest, this reminds me of looking at a car's speedometer and assuming you know everything about how the engine is performing. Sure, you can see how fast you're going, but you have no idea if the engine is running hot, if the oil pressure is dropping, or if the transmission is about to fail. The study measured external load beautifully but told us nothing about how these athletes' bodies actually responded to that stress on any given day. Were they recovering adequately? Were their tissues adapting? Was Week 4's deload actually sufficient for all nine pitchers, or did some need more recovery while others were ready to push harder? We simply don't know because the study only tracked what went into the system, not what the system did with it.

Why This Information Is Important

The fundamental issue with relying solely on ACWR or any external load metric is that it treats all athletes as if they respond identically to the same workload. But we know that's not true. A 2025 study examining pitch counts in adolescent pitchers found that shoulder strength and range of motion changes occurred completely independent of recorded pitch totals. Even after 120 pitches, there was no consistent link between pitch count and strength changes. The researchers concluded that pitch count alone is insufficient for connecting throwing volume to recovery and injury risk. This echoes exactly what we're seeing with ACWR: the external metric (how much you threw) doesn't reliably predict the internal response (how your body handled it).

Consider another piece of research that tracked heart rate variability in pitchers after starts. HRV, which reflects your autonomic nervous system's recovery state, remained depressed 24 hours after pitching. The study questioned why we're loading athletes the next day when their bodies are clearly still in a sympathetic, stress-dominant state. But here's what makes this finding even more important: HRV revealed massive individual variation. Some pitchers bounced back faster while others needed significantly more time. The authors noted that what makes HRV powerful is its individual specificity, something you can't capture by just counting throws or measuring velocity.

This is where the rubber meets the road. If you're using ACWR to manage preseason training, you're making educated guesses about injury risk based on group-level thresholds. You're assuming that because research shows an ACWR above 1.27 correlates with increased injury rates across populations, it must mean all your pitchers are at risk. But what if three of your nine pitchers are recovering beautifully and could handle more load, while two others are struggling to adapt and need immediate deload regardless of what the ACWR says? Without objective measures of internal response, you'll never know until someone breaks down.

A comprehensive analysis of return-to-throw programs found that most lack any system for objectively determining an athlete's readiness to throw or how their body is responding to increased workloads. The absence of these objective checkpoints was identified as perhaps the most critical flaw. Without individualized adjustment based on real-time feedback, athletes risk compounding physical damage, extending recovery timelines, and undermining long-term durability. The same criticism applies perfectly to this preseason workload study: measuring the stress you apply without measuring how athletes respond to that stress is fundamentally incomplete.

And here's another wrinkle that makes this even more complex. Research on in-game heart rates in professional pitchers found they averaged 85% of max heart rate during competition, far exceeding what was measured in controlled training environments. This tells us that the psychological and physiological demands of actual competition create internal stress that extends well beyond what we can predict from external workload alone. Two pitchers throwing the same number of pitches at the same velocity might experience vastly different levels of internal stress based on sleep quality, nutrition status, emotional state, previous injury history, or tissue quality. The external numbers look identical, but the internal reality is completely different.

How This Information Can Be Applied

The solution isn't to abandon ACWR or external load monitoring. These metrics provide valuable information about training structure and workload progression. The problem is treating them as complete answers rather than partial inputs. What we need is a system that tracks both external load and internal response simultaneously, then uses that combined information to make individualized training decisions.

This is exactly why tools like the ArmCare app exist. By collecting objective feedback on how an athlete's body responds to the stress of a given training day, you can accurately assess whether you've overloaded, maintained, or under-trained that specific athlete. When you compare this response score to their rolling seven-day and 28-day averages, you start to formulate a real measure of overload that's anchored in individual physiology rather than population-level assumptions. You're not just tracking how much stress you applied, you're tracking how much stress the athlete's system actually experienced.

Imagine if the researchers in this study had access to daily objective response data for all nine pitchers. They could have identified which athletes were truly at risk during those four high-ACWR weeks versus which ones were adapting successfully. They could have personalized the Week 4 deload, extending it for athletes who needed more recovery while potentially maintaining or even increasing load for those who were under-stimulated. They could have made real-time adjustments throughout the preseason instead of looking backward at population averages and making broad recommendations about reducing workload.

The application extends beyond preseason too. During the season, when workload fluctuates based on game demands and roster decisions, having objective internal response data becomes even more critical. A starting pitcher who throws 95 pitches on Monday might show excellent recovery markers by Wednesday, indicating he's ready for his between-start throwing program. His teammate who threw the same pitch count might still be showing signs of systemic stress, suggesting he needs another day before ramping up. Their ACWRs look identical, but their actual readiness states are completely different.

For coaches and practitioners, the takeaway is clear: measure everything you can about external load, absolutely track ACWR and workload ratios, but don't stop there. Pair those external metrics with consistent, objective measures of internal response. Use readiness assessments, track recovery markers, monitor tissue quality, and most importantly, individualize your training decisions based on how each athlete's body is actually handling the stress you're applying. Progressive overload isn't just about gradually increasing the numbers on a spreadsheet. It's about systematically exposing tissues to increasing demands while ensuring they're adapting successfully at each step.

Conclusion

This preseason workload study provides valuable data about how collegiate pitchers are currently being trained and reveals concerning patterns in ACWR management. Four out of six weeks above the injury risk threshold is legitimately problematic, and the recommendations to improve workload monitoring are well-founded. But measuring external load without internal response is like trying to navigate with only half a map. You know where you're trying to go, but you have no idea if you're actually making progress or just wandering in circles.

ACWR is a critical piece of the puzzle. It helps us understand workload structure, identify periods of rapid increase, and flag potential risk based on established thresholds. But without measuring how the body responds to that stress, it's literally just a slightly more educated guess. We can do better. We need to do better. The technology exists to track both external load and internal response simultaneously. The question is whether we're willing to invest in comprehensive monitoring or if we'll keep relying on partial information and hoping for the best. Because when you're operating at the edge of human performance, hoping isn't a strategy, it's a liability.

References

1. Tabaracci B, Sudhir S, Gauthier M, Hannigan L. Preseason Workload in Collegiate Baseball Pitchers. International Journal of Sports Physical Therapy. 2025;20(2):221-230.
2. Journal of Athletic Training. Pitch counts failed to predict shoulder strength or mobility changes in adolescent pitchers. 2025.
3. Heart Rate Variability and Post-Start Recovery in Pitchers. Daily HRV tracking may be essential for understanding workload and optimizing readiness between starts.
4. Analysis of return-to-throw programs and objective readiness measures.
5. Cornell DJ, Paxson JL, Caplinger RA, Seligman JR, Davis NA, Flees RJ, Ebersole KT. In-Game Heart Rate Responses Among Professional Baseball Starting Pitchers. The Journal of Strength and Conditioning. 2017.