If you had no budget for technology, how would you monitor training load?

We asked this question to six experts in this field. These were their responses:

Harry Routledge

First Team Sports Scientist, Brighton & Hove Albion FC

In elite sports, expensive GPS and heart rate monitoring are considered the industry standard. However, when resources are limited, monitoring should shift from technology-led external loads to internal physiological response.

Session RPE (sRPE), athlete wellness surveys, strategic drill design, and effective work time help staff quantify load effectively without high cost technology.

The primary tool for monitoring load is sRPE. Following each grass session, players record their perceived intensity on a 0–10 scale. Multiplying their RPE by training duration (in minutes) gives us a measure of training load in arbitrary units (AU).

Additionally, a daily questionnaire assessing sleep, fatigue, muscle soreness, and mood provides a cumulative wellness score. Tracking this over time allows staff to identify flags in player readiness and recovery.

Without GPS, area per player (ApP) is a way to control physical output. By manipulating dimensions and the number of players, staff can dictate training intensity.

Small-sided games (SSGs) are 3v3 or 4v4 on a 20×25 m pitch, allotting ~80 m² per player. These drive high explosive distance, frequent accelerations and decelerations, and high metabolic demand. Large-sided games are 8v8 to 10v10 on a 70×50 m pitch, providing >200 m² per player. These allow players to accumulate high speed running and maximal velocities.

Effective working time (EWT) distinguishes actual drill time from total pitch time. Isolating EWT allows for more accurate periodisation of work to rest ratios, ensuring player exposure aligns with specific physical objectives.

Standardised drills allow for tracking internal efficiency. If a player performs the same drill on consecutive days but reports a significant increase in sRPE, it indicates a fatigue marker, potentially requiring load adjustment.

Comparing the total weekly acute load against the rolling average (chronic load) helps identify workload spikes.

Additionally, incorporating a “coaches’ RPE” provides vital context. A potential discrepancy between the coaches’ intended intensity and the players’ perceived exertion can be a tool for altering session intensity. Furthermore, musculoskeletal assessments, such as ankle dorsiflexion and sit and reach tests, provide a baseline of physical function that can flag when accumulated fatigue is due to mechanical restriction or increased injury risk.

Brendan Fahrner

Head of Sport Science, South Sydney Rabbitohs

Training load is the simple equation of training intensity and volume, representing the overall stress the athlete experiences. While technology can add valuable context in quantifying internal and external loads, a meaningful and valid picture of overall training load doesn’t require big budgets or large datasets.

Rating of perceived exertion (RPE) for the session and individual drills is the obvious starting point for data collection. When recorded correctly, RPE is a highly valid and reliable tool that even well-resourced teams use alongside GPS, accelerometry, heart rate, and other technologies.

The benefit of using RPE as a measure of intensity is the ability to use a uniform measure across all training modalities: field-based training, gym work, or cross-training, something technology often struggles with.

Combining RPE with duration gives a valid snapshot of training load trends, including strain and monotony.

Training duration alone can be a valuable measure of training load. Many commonly used GPS variables, such as total distance and running distance, are strongly related to activity duration, providing meaningful estimates of training volume.

Further, classifying time spent in subjectively defined intensity zones or training activities can provide insights into overall training loads and support  planning progressions. Finding quantifiable tasks that are relevant to the athlete group or activity can highlight progressions across training load patterns.

For example, categorizing time spent across small-sided games, technical skills, conditioning, and other training components can show how the emphasis of a training program shifts over time.

Quantifying sport specific activities can also provide important information for monitoring training load when technology isn’t available. Two common, low tech metrics include pitch count in baseball and overs bowled in cricket. Similarly, some sports have intrinsic measures that can be quantified without technology, such as swimming distance in an Olympic pool, sprint distances on a track, or sets, reps, and weights lifted in the gym.

Finally, without technology, it becomes important to monitor the adaptive responses of the athletes to ensure your training load measures are valid. Internal load is harder to track without technology. Subjective wellness ratings, coaches’ observations, and conversations with athletes remain valuable to get a good overall picture of the training progressions and validate other measures of training load.

Marc Lewis

Director of Applied Sports Science, Houston Texans

If I had no budget for technology, I would monitor training load by tracking session duration and the rating of perceived exertion for each player from each session, while documenting the context of that session. I’d collect the data with Microsoft forms, and feed that into Power BI for data analysis and visualization. This would allow for quick and convenient data collection using easily accessible, low- or no-cost tools.

Training load reflects the combination of both volume and intensity. Session duration is simply the total time of the session in minutes, while players provide their RPE in response to “How hard or intense was your session?” A basic scale is: 0 = rest, 1 = very, very easy, 2 = easy, 3 = moderate, 4 = somewhat hard, 5-6 = hard, 7-9 = very hard, and 10 = maximal.

Session RPE, expressed as arbitrary units (AU), is a crude measure of training load and is tracked over time.

An advantage of using such a simple measure is that it can easily be compared across different types of training sessions, including weight room or field-based sessions occurring indoors or outdoors. This makes it easy to quantify daily training stress across a multitude of activities in one unit of measurement.

Practitioners can also analyze session RPE using concepts such as training monotony and strain, where accounting for all training stress imposed upon an athlete is vital in mitigating the risk of illness or injury.

In addition to tracking session RPE, I would also ask a coach or staff member to fill out a “context form.” The context form would capture important information regarding the environment and equipment. This includes whether the session was indoors or outdoors, and what specific equipment the players wore (e.g., pads, spiders, S&C gear).

If the session occurred outdoors, additional information would be the temperature, humidity, and wet bulb globe temperature.

These contextual factors play a significant role in the relative stress a session places on the athlete. They allow practitioners to better understand the training load on that given day, as well as better interpret athlete response to the training load.

Matt Kan

Head of Performance Science, Data, and Technology, Rugby Australia & Wallabies

Training load monitoring does not disappear in the absence of budget. Instead, it shifts from direct measurement toward interpretation.

Without devices to quantify external load, there is greater emphasis on session design, athlete response, and the ongoing sense-making that occurs through coaching observation and human interaction. The focus moves away from precise quantification and toward understanding what was planned, why it was planned, and how athletes responded to it.

In this context, the training session itself becomes the primary expression of load. Session duration, structure, drill density, constraints, and intent define the demands imposed on the athlete. When sessions are well designed and standardised (to an extent), they provide a consistent reference point from which practitioners can interpret responses over time.

Internal load remains central. Session RPE, collected consistently and with intent, provides a low cost yet robust indicator of how athletes perceive and tolerate training demands. Its value lies less in the absolute score and more in how it relates to the planned session, the athlete’s typical responses, and recent training history.

Where greater nuance is required, differential RPE—such as breathlessness, leg freshness, or mental effort—can help identify the dominant stressor of a given session without increasing athlete burden.

The coaching eye becomes critical without technological input. Coaches and practitioners continually observe movement quality, intent, engagement, and behaviour, often identifying subtle changes before they appear as measurable performance decrements. Shifts in movement patterns, decision making, communication, or drill execution are interpreted relative to session demands and to each individual, providing valuable insight into fatigue and readiness.

Emerging practice also supports the use of simple sub-maximal tests to infer fitness and readiness without advanced equipment.

Repeated, standardised efforts performed at a fixed intensity, such as a set running pace or workload, allow practitioners to track changes in physiological response over time. Measures such as heart rate during or immediately after these efforts, which can be assessed through manual palpation, offer insight into aerobic fitness, recovery status, and accumulated fatigue.

As with other low resource approaches, the emphasis is on consistency and longitudinal change rather than absolute values.

Human interaction remains central throughout this process. Informal conversations and day-to-day interactions provide insight into mood, emotional presence, and cognitive engagement, all of which meaningfully influence how athletes perceive and tolerate load. Mood reflects an athlete’s underlying emotional state, while emotional presence relates more to how engaged and responsive they are within the training environment.

These elements are difficult to capture through technology, yet they are often critical in understanding an athlete’s response to training.

Ultimately, effective load monitoring without technology relies on alignment between training intent, athlete feedback, observation, and context. While technology can support this process, it cannot replace the interpretive skill of the practitioner or the importance of human connection in understanding training response.

Adam Hoffman

Performance Scientist, Charlotte FC

The first step is to define long term monitoring goals and work back to the team’s current position in the season at each competitive level. This reverse engineering approach ensures that daily and weekly training decisions align with performance objectives across the entire year.

A Major League Soccer development structure generally includes three levels: the MLS (first team), the MLS NEXT Pro team (second team), and the academy, which contains multiple age groups developing toward professional soccer. Monitoring training load across these levels requires a collaborative approach in which each member of the performance, coaching, and medical staffs contributes to the process.

Effective monitoring supports the larger objectives of building a winning environment while maintaining athletes who are physically resilient and capable of consistently performing at an optimal level.

Without expensive technology, the two practical and free metrics for internal and external load are RPE and session duration, respectively

RPE can be collected from both coaches and athletes to provide insight into how demanding each training session was compared with what was planned.

The process begins with consistent communication. Daily performance meetings help align staff members on the goals and expectations of each training session. The Director of High Performance and the Head of Performance Science work closely with coaches to ensure that training activities support the broader team objectives. The planned load of drill design and timing will provide a daily estimate of cumulative load.

Organizing the season’s calendar into clear training phases across daily, weekly, and monthly time frames is crucial. This helps determine whether performance goals are being achieved at the drill level.

Simple wellness questionnaires collected before training provide insight into fatigue and stress that may influence how athletes respond to training.

Session duration and RPE can be analyzed deeper to include monotony, strain, average load, and total load, along with comparisons between projected and actual daily load using Excel sheets. These variables provide a practical overview of acute and chronic workload trends and help guide decision making throughout the season, all the way down to the drill level.

Success is meaningful outcomes, such as minimizing injury risk from overtraining, strong player performance during demanding phases of the season, and overall player development on the field. While there is no single solution for monitoring load, a clear structure and strong collaboration can produce effective results even without advanced technology.

Perry Blanchette

Head of Sports Science, Millwall FC

If I had no budget for technology, my approach to monitoring training load would be targeted around relationships, trust, and consistent communication. With no incoming data, the players themselves become the primary source of insight and information. That makes it imperative to create an environment where they feel comfortable sharing how they feel, providing honest feedback.

Practitioners should prioritise building strong, individual relationships with each player, taking time to understand their character, behaviours, and how they respond to stress.

Over time, the practitioner will be able to recognise changes with each player, noticing any changes in mood, how they engage with us, our colleagues, or their teammates. These subtle changes may provide clues into potential fatigue.

To help form the relationships with the players, actively seek regular conversations, and daily check-ins before and after training. Ask open-ended questions around how the player is feeling both physically and mentally, how they are coping with the demands of training and matches, and if there is anything they wish to change with their recovery strategies.

Trust is paramount: players need to feel they can be honest and that their input will be acted upon.

Creating psychological safety, where players feel comfortable saying they are fatigued or struggling without fear of negative consequences enhances the quality of feedback. From here, our challenge is to decipher the most important pieces of feedback and act upon them accordingly.

Over time, this leads to more accurate decision making around training adjustments.

Overall, lacking technology should shift practitioners to a human centred process that provides depth, context, and individualisation.