Examine the tools and methods used to monitor, record and evaluate training load and performance, and explain how the resulting data informs program decisions

What this sub-topic is asking

NESA wants you to identify the subjective and objective tools used to monitor training load and athlete response, describe how training is recorded over time, and explain how coaches evaluate that data (trends, periodised testing, comparison against pre-set targets) to make informed decisions about progression, deload or program change.

The answer

Monitoring is the ongoing collection of training and athlete data. Recording is the systematic storage of that data. Evaluation is the interpretation that drives the next coaching decision. Done well, the three steps close the loop on the principles of training.

Subjective measures (athlete-reported)

Rating of Perceived Exertion (RPE)

Athletes report effort on a 1-10 (Borg CR-10) or 6-20 (Borg) scale. Session RPE (sRPE) multiplied by session duration gives an arbitrary-unit training load (e.g. RPE 7 x 60 min = 420 AU). Cheap, simple, well-validated against heart-rate-based load measures across many sports.

Wellness questionnaires

Daily 1-5 ratings on sleep quality, fatigue, muscle soreness, stress and mood. A sustained drop across multiple items can signal accumulating fatigue or under-recovery before performance declines.

Training logbooks / diaries

The athlete records what was actually completed (sets, reps, distances, times), how it felt, and contextual factors (sleep, illness, life stress). Indispensable for retrospective analysis when results change.

Objective measures (instrument-based)

Heart-rate monitors

Track average and peak HR per session, time in zones, and resting / morning HR. A rising resting HR or suppressed HR response to a standard workload can indicate fatigue or illness.

GPS units

Wearable GPS (worn between the shoulder blades in a vest) records distance, speed, accelerations, decelerations and high-intensity efforts. Standard in field-sport (rugby, AFL, football, hockey) and increasingly in court sports via local positioning systems.

Force plates and jump mats

Measure vertical jump height, peak force, rate of force development. A drop in countermovement jump performance is a sensitive early indicator of neuromuscular fatigue.

Wearable sleep / HR-variability devices

Estimate sleep duration and quality, and HR variability as a proxy for autonomic recovery state. Useful as a trend tool; single-day readings vary too much to act on alone.

Performance testing batteries

Periodised tests run pre-block, mid-block and post-block. Common items:

• Yo-Yo Intermittent Recovery test (intermittent aerobic capacity for team sports).
• Multi-stage fitness test (beep / shuttle run) as a general aerobic capacity field test.
• 20m sprint with split times at 5m and 10m (acceleration vs top speed).
• Vertical jump (countermovement or squat jump) for lower-body power.
• 1RM (one-repetition maximum) or predicted 1RM for strength.
• Sit-and-reach and goniometric measures for flexibility.

Reading the data: trends, not single sessions

A single day's RPE, HR or jump score is noisy. Coaches look for trends across 7-28 days. Two widely used constructs:

• Acute:Chronic Workload Ratio (ACWR). The 7-day rolling load divided by the 28-day rolling load. Ratios persistently above ~1.5 are associated with elevated injury risk in some sports; ratios well below 1.0 reflect detraining. The exact thresholds are debated in the sports-science literature, but the concept of comparing acute spike against chronic build is widely used.
• Monotony and strain. Weekly load divided by weekly standard deviation (monotony); monotony multiplied by weekly load (strain). High monotony with high load is a risk pattern.

A wellness drop of one or two points on its own may be noise. A sustained drop across several items over a week, combined with rising sRPE and falling jump height, is a coherent signal.

Periodised testing

Tests are not run every week (too disruptive, too fatiguing). A typical periodised approach:

• Pre-block baseline testing in the first week of a new macrocycle.
• Mid-block retest of one or two key markers after 4-6 weeks.
• Post-block full retest after 8-12 weeks, used to evaluate the block and plan the next.

The choice of test must match the sport (specificity). A marathon runner is tested with a treadmill VO2max or field time trial, not with a vertical jump.

Subjective vs objective: use both

Subjective measures are sensitive (athletes often "know" before the numbers move) but vulnerable to bias and motivation effects. Objective measures are reproducible but expensive and sometimes lag behind subjective change. Best practice is to triangulate: a coherent signal from both is the cue to adjust.

Athlete-management systems

Many programs use software platforms to aggregate sRPE, wellness, HR, GPS and test data into per-athlete dashboards. The platform is a tool, not a decision. The coach still interprets, and the program still has to apply the principles of training.

Examples in context

Example 1. AFL pre-season GPS load monitoring. AFL clubs use wearable GPS in every training session and match. Weekly total distance, high-speed running distance and number of accelerations are tracked per player. The strength and conditioning staff use rolling 7-day and 28-day loads to plan the next week; a player returning from injury is progressively reintroduced to high-speed running over several weeks rather than being thrown straight back into full training. This is the monitoring framework operationalised at professional level.

Example 2. A school 1500m runner using a free training-log app and a heart-rate monitor. The student records every session (distance, time, RPE 1-10) and HR data. Over a 12-week build the coach reviews weekly: total mileage, time at threshold pace, and any sessions with abnormally high HR for a given pace (a possible early sign of illness or under-recovery). A pre-block, mid-block and post-block 3km time trial measures aerobic fitness change. The setup is low-cost, but applies the same logic as elite monitoring: track trends, test periodically, act on coherent signals.

Try this

Q1. Identify three subjective and three objective measures used to monitor training load and athlete response. [3 marks]

• Cue. Subjective: RPE / session RPE, wellness questionnaire, training logbook. Objective: heart-rate monitor, GPS, vertical jump (countermovement jump), 1RM or 20m sprint test.

Q2. Explain why coaches interpret training-monitoring data as trends rather than single data points. [4 marks]

• Cue. Day-to-day variability (sleep, stress, hydration) creates noise. A 7-28 day rolling view (e.g. acute:chronic workload ratio) gives a more reliable signal of accumulating fatigue or training adaptation; convergence of multiple subjective and objective markers is the cue to act.

Q3. Justify a monitoring and testing plan for a named athlete over a 12-week training block. [8 marks]

• Cue. Pick a specific athlete (a 400m runner, an AFL midfielder, a school 1500m runner). Specify daily monitoring (RPE, wellness), session monitoring (HR or GPS), and periodised testing (pre / mid / post). Match each test to the sport demand. State what change in the data triggers a deload or program change. Show the link between monitoring data and the principles of training (progressive overload, recovery, specificity).