What Data Couldn't Tell Me: Reflections on Applied Sports Science in Soccer

In this guest post, Sports Scientist and Strength Coach Jammie (Haochen) Hsueh shares five lessons from her time working in collegiate soccer so far.

Sitting at my desk, looking at all the data that had just been transferred after the morning session, the questions I always asked myself were: What should I include in the report? Would the coaches read it? Does it matter to them?

As a sports scientist with the Southern Methodist University (SMU) Women's Soccer team over the past two years, I faced that exact dilemma most days. Working at the Division I level in the Atlantic Coast Conference (ACC), with a high-performance team and various technologies and data sources, it was a constant challenge for me to decide what to share, what not to share, and how to share it.

I have recently been reflecting on my experience so far and have highlighted five key lessons that I will share in this article.

Stepping into SMU

When I first stepped nervously into my new surroundings, I faced a brand-new team, a new environment, a higher level of competition, new coaches, unfamiliar technology and software systems, all while managing English as my second language.

I had just graduated from Springfield College with a Master's degree in Strength and Conditioning and came with experience as a Strength and Conditioning Coach in a Division III setting.

Instead of hiding behind my desk and jumping into the data and dashboards, I knew connecting with the people around me was my main priority.

I needed to know the coaches, know the athletes, and know the other support staff. While it is always easier to stay behind a screen, I already appreciated that sports science isn’t just about the numbers; it’s the trust and buy-in you build that makes the data valuable.

Instead of hiding behind my desk and jumping into the data and dashboards, I knew connecting with the people around me was my main priority.

To understand what mattered to each coach and staff member, I started by listening and asking genuine questions. I wasn't trying to slam every dashboard, test result, or idea I had into their faces; I wanted to truly understand what they needed from me.

Every staff member has specific things they care about most and a unique preference for how they receive information.

I quickly learned that our head coach described training load using duration and a simple 1–10 intensity scale. Instead of dumping all the complex metrics on her, I adopted her language to plan and discuss load.

I learned that our strength coach didn't want overwhelming detail; he just needed to know if anything required an adjustment in the weight room, so I kept things brief and straight to the point.

Meanwhile, our athletic trainer wanted to dig deeper into what the data meant so we could grow together and use objective metrics to guide return-to-play progress.

I also realized this isn't a "one-and-done" process. I have to check in with them periodically to evaluate whether the reporting is working, asking directly whether it's too much, too little, or needs any adjustments. For example, through these ongoing check-ins, I discovered that while my head coach liked having all the detailed context available, what she valued most was a clear, highlighted key takeaway at a glance.

As my relationships with the staff grew, I realized that effective communication was only the beginning. Over my two years at SMU, my understanding of what sports science truly means continued to evolve.

Lesson 1: Sports science should never speak louder than soccer

Early on, I always hoped coaches would care more about sports science, the numbers, the reports, and the loading models, after all, that was my job and why I was there! At SMU, I was fortunate to work in an environment where our head coach genuinely valued sports science and welcomed my input into the decision-making process.

However, during off-season training in my second year, something in my head told me that something wasn't right. I realized I was spending way too much time having endless conversations with the coach about optimizing the load. That's when it hit me: the spotlight was supposed to be on soccer, not the data.

At the end of the day, the team is successful because they are able to score goals and win games, not necessarily because the team is using an "optimized" training plan on paper. Yes, sports science can, in theory, reduce injury risk and increase physical performance, but the sport itself must remain at the center of everything we do. Sports science is a supporting tool. We do what we can to help the team get a little closer to winning, but sports science itself is not the goal.

Lesson 2: Not every demanding session looks demanding on GPS

GPS is a great tool for capturing external load metrics, with the most reliable metrics such as total distance and high-speed distance. However, I learned that just because a session doesn't look demanding on the GPS report doesn't mean it wasn't demanding for the players.

During one small-sided session, I was standing next to one of the assistant coaches, who had previously been a player on the team. As we watched the drill, she turned to me and said,

"Jammie, this kind of drill was one of the hardest drills I did when I was a player. You might see that the players are not covering a ton of distance on your iPad, but their feet are definitely burning right now. It is really exhausting."

That was another moment when I thought to myself: today, I learned something.

This taught me not to let a single data source tell the entire story. Sometimes, simply asking the players how the session felt provides information that the GPS unit can not capture. This is where RPE and direct conversations with players became especially valuable.

Numbers are still valuable, but numbers without context are not enough. GPS tells us what it can measure, but sometimes, it is more important for us to understand what it cannot.

Lesson 3: RTP is more than physical progression

While supporting return-to-play (RTP) and tracking players’ progress, it is easy to get hyper-focused on GPS metrics when players get back on the field. Distance, in particular, as it is also one of the easiest metrics for everyone to understand without a long explanation, and also the first metric the player is going to see progress in. However, during the RTP process, the focus and goals vary by stage.

Additionally, there are factors such as psychological readiness and cognitive stress that we cannot capture with the GPS unit.

For example, an athlete may be physically capable of progressing but still lack confidence in the injured area or be hesitant to perform movements similar to those they performed when they tore their ACL. We need to recognize that progression is not only about whether an athlete can physically do it, but also whether they feel ready and confident enough to do it.

As an athlete progresses into high-intensity exposure, the volume is not necessarily going to increase at the same time. The progression of running load itself is multidimensional; the Control-Chaos Continuum considers not only total running volume, but also running speed, high-speed running, accelerations and decelerations, technical actions, and, eventually, increasingly unpredictable “chaotic” movements.

It might require more effort than you expect to help the people around you understand why the distance is dropping, why it is so much lower than the game-distance demand, and why that is okay at that moment.

Cognitive load is also easy to overlook, especially in the final stage of return to play, when players begin participating in group settings after months of individual rehab and training.

I found that the Control-Chaos Continuum model (Taberner et al. (2020) helped me better understand the importance of progressively exposing athletes to increasing perceptual and neurocognitive demands. If we do not consider cognitive load as part of that progression, moving from a controlled individual setting into a chaotic team environment can create a sudden jump in demands that we overlooked.

The Visual Cognitive Control-Chaos Continuum (VC-CCC) applied to on-pitch rehabilitation (Taberner et al., 2025)

This becomes even more important in the final stage, when there may be increasing time pressure to get the player back to competition. If we continue progressing on what we can measure while overlooking the demands we cannot easily quantify, we might be setting players up for failure.

Lessons 4: The academic stress we didn't account for

We all know that stress can accumulate from many sources, not just training. Student-athletes, especially, experience academic stress from exams and assignments, which can lead to a lack of sleep and significantly affect their readiness on the field.

During my first season, the team usually had two-game weeks. Therefore, when we had a one-game week, coach and I discussed how we wanted our training plan to look. We saw it as an opportunity to train harder because we had more days to prepare and recover. However, when game day came around, the players looked fatigued.

Afterward, during my post-season sport science review, I realized we had mainly been focusing on the stress we were creating on the field. We hadn't fully accounted for what was happening outside of it.

Players were preparing for exams, completing assignments, studying late into the night, and getting less sleep. Even though they had more physical recovery time between games, they didn't necessarily have more recovery. Jo refers to this as part of the Training Adaptability Prediction Problem.

The following year, we treated exam week and the week prior, as a significant stressor in our training planning. We became more proactive by considering what was happening in the players' lives outside of soccer and determining whether they needed more recovery or could tolerate more training during that valuable one-game week.

Lesson 5: Not only review the past, but also forecast the future

When I first started at SMU in a new sports science role with the women's soccer team, every day was new to me. I then learned to build season reviews for future reference, knowing what we did well and what we would like to improve. It was definitely valuable to have those reviews during my second year when planning training load, as we could identify patterns, challenge our assumptions, and make better decisions.

However, I found that one area I could improve was my ability to forecast different scenarios and different training load plans, for example, when the load might peak, when it might drop, how it would affect high-minute players and low-minute players, and how I could visualize those scenarios for coaches to better understand where each decision might take us. I learned not only to look back on the past but also to look ahead and forecast the future.

Final Thoughts

Before becoming a sports scientist, I thought there would be more certainty in decision-making with the support of sports science. However, through my time in the field, I discovered that sports science is actually about learning to navigate and embrace uncertainty.

I know I will still ask myself what to include in the report and whether it matters to the coaches the next time I sit at the desk with all the data staring at me. I will still make mistakes, but I now see things from more angles, understand the limitations of each data source, and try to make the best decision we can with the information we have at that moment.

More importantly, I will always remind myself that sports science is a tool to support the team, not the goal itself. Ultimately, our role is to help create an environment that gives the team the best opportunity to perform and win.

I also want to take this opportunity to express my gratitude. I am beyond grateful for the mentorship and guidance Jo has provided throughout my career, as well as the opportunity to write this guest blog and share my experiences and reflections with more people.

These are just a few lessons I learned so far, with many more still to learn. I would love to hear from you. What one lesson has changed the way you approach sports science?

I discovered that sports science is actually about learning to navigate and embrace uncertainty.

References

Taberner, M., Allen, T., & Cohen, D. D. (2020). Adapting the high chaos phase of the ‘control-chaos continuum’: A bridge to team training. Sports Performance and Scientific Reports, 109(1), 1-6.

Taberner, M., Allen, T., Constantine, E., & Cohen, D. (2020). From control to chaos to competition: building a pathway to return to performance following ACL reconstruction. Aspetar Sports Med J, 9, 84-94.

Taberner, M., Allen, T., O’keefe, J., Chaput, M., Grooms, D., & Cohen, D. D. (2025). Evolving the control-chaos continuum: part 1–translating knowledge to enhance on-pitch rehabilitation. Journal of Orthopaedic & Sports Physical Therapy, 55(2), 78-88. https://www.jospt.org/doi/10.2519/jospt.2025.13158