Spreadsheet or software for load monitoring?
There is no published evidence that software performs better than a spreadsheet, or the other way round: spreadsheets are a widely used solution in professional football (Dello Iacono et al., 2025). The useful question is where your workflow starts to fall short, and this guide gives you the published surveys of elite football, five checkpoints and a self-audit for your coaching staff.
What elite football does in practice
Akenhead and Nassis (2016) invited 82 high-level clubs from Europe, the United States and Australia; 41 responded. All of them used GPS and heart-rate monitors in every training session and 28 used RPE. Players’ responses to training were monitored with questionnaires in 68% of clubs and with submaximal protocols in 41%.
Dello Iacono et al. (2025) surveyed 206 practitioners in senior football from all six FIFA confederations (73% performance, 18% data and 9% medical). They found heterogeneity in metrics and methods across departments, a mix of solutions for storing, analysing and reporting data, and spreadsheets cited as a popular solution for data wrangling and reporting tasks. This is prevalence data: it shows what is used, not that it is better or worse.
What monitoring is for and where it falls short
In the survey by Akenhead and Nassis (2016), practitioners rated the actual effectiveness of monitoring below the expected effectiveness: a difference of 23% for injury prevention and 20% for performance enhancement. These are perceptions from a small sample, not measured outcomes. Among the barriers, limited human resources scored highest, followed by coach buy-in. The authors attribute the gap to suboptimal integration with coaches, insufficient human resources and concerns over the reliability of assessment tools.
Five checkpoints
| Checkpoint | What the literature documents | Source |
|---|---|---|
| Integrating GPS, RPE and wellness | In an Australian football club (45 players), GPS, sRPE and a five-item wellness questionnaire formed separate components: external load, internal load and perceived wellness; the authors aimed to address data overload | Ryan et al., 2021 |
| Data quality | 60% of 276 studies on acceleration and deceleration did not report how the data was derived and cleaned; custom single-item questionnaires were used ubiquitously and may affect validity | Ellens et al., 2022; Neupert et al., 2022 |
| Staff time | Limited human resources was the highest-scoring barrier. None of the sources consulted quantifies time | Akenhead and Nassis, 2016 |
| Access | An organisational question: who enters, who corrects and who sees each piece of data? | — |
| Communication | 44% of the 25 UK practitioners with a monitoring system (11) said athletes did not get enough feedback; some said the data was never discussed with athletes or coaches | Neupert et al., 2022 |
Two clarifications. Neupert et al. (2022) surveyed 30 practitioners from UK Olympic sports, not football. And Thornton et al. (2019) hold that underpinning a successful monitoring system is the ability of practitioners to communicate important information to coaches; they do not compare spreadsheets with software.
What a dedicated system can and cannot do
The evidence does not compare spreadsheets and software on outcomes. What Robertson et al. (2017) do describe is that traffic-light systems are a particularly common form of decision support in team sports, but that there is still a lack of standardisation in how they are operationalised. A system stores and presents data; it does not by itself fix a badly defined metric or cleaning without criteria, which are the problems the studies above point to. And none of the cited sources shows that changing tools reduces injuries or improves performance. So the honest question is not “which is better?” but “which part of our process depends on copying and reconciling data by hand, and how much staff time does it take?”
A self-audit for your staff
Answer yes or no. The more “no” answers, the more that point deserves a review, whether with your current spreadsheet or with another tool.
- Are the GPS, RPE and wellness data of the same player and the same session read together without copying data by hand?
- Is it written down how each GPS file is cleaned, so another staff member reaches the same result?
- Are the questionnaires players use always the same, with the same questions?
- Is there enough staff time to enter, review and report without leaving data unseen?
- Do you know who can enter, correct and view each piece of data?
- Do players and the coaching staff receive what they need, and do they discuss it?
Starting small
Ryan et al. (2021) worked precisely on data overload: reducing redundant measures is a reasonable step before adding tools. Thornton et al. (2019) ask that monitoring enable the rapid reporting of simple and scientifically valid feedback. In practice: choose few measures, write down the cleaning rules and report simply.
In practice
With a spreadsheet or another tool, the key is being able to answer the six questions above. In Athlo, you upload the CSV your GPS exports and review how columns and players were interpreted before confirming, without relying on a direct integration with the provider ; and in load control, wellness and availability can be consulted next to the physical indicators . More in GPS load and in wellbeing and sRPE.
Sources
- Akenhead R, Nassis GP (2016) “Training load and player monitoring in high-level football: current practice and perceptions” International Journal of Sports Physiology and Performance 11(5):587–593. https://doi.org/10.1123/ijspp.2015-0331
- Dello Iacono A, Datson N, Clubb J, et al. (2025) “Data analytics practices and reporting strategies in senior football: insights into athlete health and performance from over 200 practitioners worldwide” Science and Medicine in Football 10(1):80–95. https://doi.org/10.1080/24733938.2025.2476478
- Neupert E, Gupta L, Holder T, Jobson SA (2022) “Athlete monitoring practices in elite sport in the United Kingdom” Journal of Sports Sciences 40(13):1450–1457. https://doi.org/10.1080/02640414.2022.2085435
- Thornton HR, Delaney JA, Duthie GM, Dascombe BJ (2019) “Developing athlete monitoring systems in team sports: data analysis and visualization” International Journal of Sports Physiology and Performance 14(6):698–705. https://doi.org/10.1123/ijspp.2018-0169
- Robertson S, Bartlett JD, Gastin PB (2017) “Red, amber, or green? Athlete monitoring in team sport: the need for decision-support systems” International Journal of Sports Physiology and Performance 12(Suppl 2):S2-73–S2-79. https://doi.org/10.1123/ijspp.2016-0541
- Ryan S, Kempton T, Coutts AJ (2021) “Data reduction approaches to athlete monitoring in professional Australian football” International Journal of Sports Physiology and Performance 16(1):59–65. https://doi.org/10.1123/ijspp.2020-0083
- Ellens S, Middleton KJ, Gastin PB, et al. (2022) “Techniques to derive and clean acceleration and deceleration data of athlete tracking technologies in team sports: a scoping review” Journal of Sports Sciences 40(16):1772–1800. https://doi.org/10.1080/02640414.2022.2054535