Triathlon Cycling

CTL, ATL and TSB Explained: Fitness, Fatigue and Form for Triathletes

What CTL, ATL and TSB actually measure, how they are calculated, what a “good” CTL means in weekly hours, and how to use form before a race. Includes a modelled 70.3 build and a free CTL simulator.

Triathlete riding a time-trial bike in an aero position during an urban race
In this article

    CTL, ATL and TSB are the three lines on the Performance Management Chart in TrainingPeaks and similar platforms. They look like a verdict on your fitness. In reality they are three running averages of one number—your daily training stress—and once you see the arithmetic, the chart becomes far more useful and far less mysterious.

    Quick answer

    CTL (“fitness”) is a slow, roughly six-week weighted average of your daily training stress. ATL (“fatigue”) is a fast, roughly one-week weighted average of the same numbers. TSB (“form”) is yesterday’s CTL minus yesterday’s ATL. A negative TSB means recent training is above your usual load; a positive TSB means you have been training less than usual.

    CTL Chronic Training Load
    42-day time constant. Over weeks, it settles at your average daily TSS.
    ATL Acute Training Load
    7-day time constant. Reacts within days to hard weeks and rest.
    TSB Training Stress Balance
    CTL − ATL, using yesterday’s values. Describes balance, not readiness.

    Everything on the chart starts with a daily load score. In most triathlon software that is Training Stress Score (TSS), where one hour at threshold equals 100. If the TSS going in is wrong—because of an outdated FTP, a guessed swim threshold or a heart-rate estimate—every line built from it inherits the error. Keep that in mind throughout.

    What the Performance Management Chart actually shows

    The chart is a practical version of the fitness–fatigue (impulse–response) model proposed by Eric Banister and colleagues in the 1970s. The idea is simple: every workout produces a small, long-lasting positive effect and a larger, short-lived negative effect. Performance at any moment reflects the balance between the two. Andrew Coggan adapted the idea to power-based TSS, and TrainingPeaks popularised it as the Performance Management Chart (PMC).

    Metric TrainingPeaks label What it really is Moves
    CTL Fitness Exponentially weighted average of daily TSS, 42-day time constant Slowly: usually a few points a week
    ATL Fatigue Exponentially weighted average of daily TSS, 7-day time constant Quickly: one big day can lift it 10+ points
    TSB Form Yesterday’s CTL minus yesterday’s ATL Mirrors ATL in the opposite direction

    Strava shows a similar model as “Fitness & Freshness”. Other platforms may use different load inputs, time constants and names, so numbers are rarely comparable between apps.

    How CTL, ATL and TSB are calculated

    TrainingPeaks documents the same update rule for both averages. Each day, the line moves a fixed fraction of the way towards that day’s TSS:

    CTLtoday = CTLyesterday + (TSStoday − CTLyesterday) × 1/42ATLtoday = ATLyesterday + (TSStoday − ATLyesterday) × 1/7TSBtoday = CTLyesterday − ATLyesterday

    42 and 7 are the default time constants. Some platforms let you change them, which changes every number on the chart.

    Because each day only moves the line a fraction of the gap, older workouts never fully disappear—their influence just shrinks. That is why TrainingPeaks notes that CTL in effect reflects about three months of training, even though its time constant is six weeks.

    What one workout does to the chart

    Take a single 100-TSS session for an athlete starting at zero. CTL rises by 100 × 1/42 = 2.4. ATL rises by 100 × 1/7 = 14.3. The next morning, TSB is 2.4 − 14.3 = −11.9. One hard day can make form look poor, but it barely changes fitness.

    How long changes take to show up

    If you change your training and then hold the new load steady, the lines close the gap at very different speeds:

    Days at the new load 7 14 28 42 90
    Share reflected in CTL 16% 29% 49% 64% 89%
    Share reflected in ATL 66% 88% 99% 100% 100%

    Calculated from the default 42- and 7-day constants (1 − (1 − 1/k)days). ATL at 42 and 90 days is above 99.8% and rounds to 100%.

    Practical consequence: a good training block needs four to six weeks before CTL fully reflects it, while one bad week shows up in ATL and TSB almost immediately. Judge CTL by its trend across a block, and TSB by its pattern across a week.

    The most useful rule: CTL ≈ your average daily TSS

    If you trained with exactly the same daily TSS for long enough, CTL would settle at that number. In other words, CTL is a smoothed estimate of how much TSS you produce per day. Multiply it by seven and you get the weekly load it represents. That single fact answers most “is my CTL good?” questions better than any league table.

    To translate weekly TSS into hours, you need to know how much TSS each hour produces. For power-based cycling, TSS per hour equals 100 × IF². Steady endurance riding at IF 0.71 gives about 50 TSS per hour, mixed training at IF 0.77 about 60, and harder sessions at IF 0.84 about 70.

    Stable CTL Weekly TSS Hours at 50 TSS/h Hours at 60 TSS/h Hours at 70 TSS/h
    30 210 4.2 3.5 3.0
    40 280 5.6 4.7 4.0
    50 350 7.0 5.8 5.0
    60 420 8.4 7.0 6.0
    70 490 9.8 8.2 7.0
    80 560 11.2 9.3 8.0
    100 700 14.0 11.7 10.0
    120 840 16.8 14.0 12.0

    Arithmetic conversion, not a population benchmark. Running and swimming scores per hour can differ from cycling, so real triathlon weeks will not match a single column exactly.

    So what is a good CTL?

    There is no universal good number. A CTL of 60 simply says that you have recently sustained something like 420 TSS a week—around six to eight hours of typical training. Whether that is enough depends on your race distance, your history and, above all, whether you can repeat it without breaking down. A better question is: what weekly hours can I sustain, and what CTL does that produce? Our guide to how many hours a week to train for a triathlon is a sensible starting point; CTL then becomes a way to check that you are actually delivering that volume.

    Be wary of CTL “targets” for each race distance. Numbers quoted online come from different athletes, platforms and threshold settings, and they are not validated standards. Two athletes with the same CTL can be very differently prepared.

    A 70.3 build, modelled day by day

    To show how the lines behave in a real plan, we modelled a self-coached half-distance athlete. The assumptions are deliberately ordinary:

    • Starting CTL and ATL of 45 (about 315 TSS a week).
    • First week at 330 TSS, adding 30 TSS each build week, with every fourth week a recovery week at 65% of the previous week.
    • 15 weeks of building, peaking at 660 TSS—roughly 11 hours at 60 TSS per hour.
    • A two-week taper at 70% and then 45% of peak load, with race day on the final Sunday.
    • A fixed weekly pattern: rest Monday, key sessions Tuesday and Thursday, the long ride on Saturday and the long run on Sunday.
    Modelled CTL, ATL and TSB across a training build and taper CTL rises from 45 to a peak of 73.8, ATL rises and falls with each week, and race-morning TSB is 8.6.020406080100120−30−20−100+10+20W1W4W7W10W13W16RaceCTL & ATLTSB
    Modelled with the default 42/7-day constants. Green shading marks recovery weeks; rust shading marks the taper. These are model outputs from an illustrative plan, not measured athlete data.

    Four things stand out:

    1. CTL climbs slowly. Fifteen weeks of progressive training move CTL from 45 to a peak of 73.8. The biggest weekly increase is about 4 points.
    2. TSB is negative for almost the entire build. At the end of the biggest week it reaches −27. That is what training looks like in this model, not a warning by itself.
    3. Recovery weeks reset TSB, not CTL. Each one pulls TSB back near zero while costing only about 1.5 points of CTL.
    4. The taper trades a little CTL for a lot of form. CTL drops 5.3 points from its peak, but TSB swings from −27 to +8.6 on race morning.
    Show the week-by-week numbers
    Week Phase Weekly TSS CTL ATL TSB CTL change
    1 Build 330 45.5 49.7 −4.2 +0.5
    2 Build 360 46.5 54.4 −7.9 +1.1
    3 Build 390 48.1 59.1 −11.0 +1.6
    4 Recovery 254 46.4 46.5 −0.2 −1.7
    5 Build 420 48.6 59.6 −10.9 +2.3
    6 Build 450 51.2 67.1 −15.9 +2.6
    7 Build 480 54.1 72.8 −18.7 +2.9
    8 Recovery 312 52.8 57.2 −4.5 −1.4
    9 Build 510 56.1 72.6 −16.5 +3.3
    10 Build 540 59.5 80.9 −21.4 +3.5
    11 Build 570 63.2 86.9 −23.7 +3.6
    12 Recovery 371 61.7 68.2 −6.5 −1.4
    13 Build 600 65.7 85.7 −20.0 +4.0
    14 Build 630 69.7 94.7 −25.0 +4.0
    15 Build 660 73.8 101.0 −27.2 +4.1
    16 Taper 462 72.7 82.4 −9.7 −1.0
    17 Taper 297 (6 days) 68.5 59.9 +8.6 −4.2
    Race morning — — 68.5 59.9 +8.6 —

    CTL, ATL and TSB at the end of each Sunday. Race-morning TSB uses the end-of-day values from the day before the race, as TrainingPeaks does.

    Try it with your own numbers

    Change the inputs to see how starting load, progression, recovery weeks and taper length shape the chart. The simulator uses exactly the same model and weekly pattern as the example above.

    How to read TSB (form)

    TSB is the line athletes most often misread. TrainingPeaks itself describes it as a measure of how adapted you are to your current load, not as a predictor of performance. A useful way to read it is by context:

    Situation Typical TSB pattern In our 70.3 model What to check
    Build week Negative, lowest after the weekend −4 to −27 at week end Are key sessions still good? Sleep, mood, soreness?
    Recovery week Rises towards zero −0.2 to −6.5 Do you feel fresher by the end of the week?
    Taper Rises above zero +8.6 on race morning Is CTL falling more than you intended?
    Weeks off / illness Strongly positive while CTL falls — Positive form without fitness underneath is detraining.

    Notice how much TSB moves within a single week. A Monday morning after a big weekend will always look worse than a Saturday morning. Compare like with like—for example, every Monday—rather than reacting to daily swings.

    Why doesn’t TSB equal CTL − ATL on your screen? TrainingPeaks calculates today’s form from yesterday’s CTL and ATL, so a hard workout today changes tomorrow’s TSB. Rounding of the displayed values can also make the subtraction look a point off.

    Ramp rate: how fast should CTL rise?

    Ramp rate is the weekly change in CTL. You can predict it with one line of arithmetic. Over seven days at a steady load, CTL closes about 15.5% of the gap between its current value and your average daily TSS:

    Weekly CTL change ≈ 0.155 × (weekly TSS ÷ 7 − current CTL)
    Starting CTL 60, next week’s TSS 420 490 560 630 700
    CTL change after 7 days 0.0 +1.6 +3.1 +4.7 +6.2
    Increase vs. current load 0% +17% +33% +50% +67%

    Daily-step calculation with the default 42-day constant and evenly spread load. Uneven weeks change the result by a few tenths.

    The table makes a point that is easy to miss: a ramp of 5 CTL points in one week requires a weekly load roughly 50% above what your CTL represents. Sustaining that for several weeks in a row is a very large progression for most age-group triathletes.

    Coaching rules of thumb commonly quote something like 3–7 CTL points per week. Treat these as conventions rather than safety limits. Research on load ratios has not shown that any particular threshold protects you: a widely cited critique of the acute:chronic workload ratio concluded there was no evidence supporting its use to reduce injury risk. Progress load gradually, but let your response—not a target ramp—decide the next step.

    Tapering with TSB

    The chart is most useful before a race because it shows the trade-off a taper creates. The table below starts from an athlete holding a steady CTL and ATL of 80 (TSB 0) and applies different tapers:

    Taper (from steady CTL 80) Race CTL Race ATL Race TSB CTL lost
    7 days at −40% load 75.0 58.9 +16.2 6%
    10 days at −50% 71.4 48.6 +22.9 11%
    14 days at −50% 68.5 44.6 +23.9 14%
    21 days at −60% 60.9 33.9 +27.1 24%
    7 days complete rest 67.6 27.2 +40.4 16%

    Model outputs with default constants. Real athletes rarely hold perfectly steady load, so their starting TSB will differ.

    The model always rewards more rest with a higher TSB—complete rest produces the biggest number of all. It has no way to tell you when freshness becomes staleness, or how much CTL you can afford to lose. That judgement has to come from evidence and experience. A 2023 meta-analysis of endurance athletes found that tapers which cut training volume by roughly 41–60% while keeping intensity and frequency improved time-trial performance. Our triathlon taper guide turns that into practical taper lengths by race distance.

    Use TSB to check a taper, not to design it. Plan the taper from the evidence and your own history, then use the chart to confirm that fatigue is falling and fitness is not collapsing. If you record how you raced at different race-morning TSB values, your own data will eventually be more useful than any generic target.

    CTL, ATL and TSB in triathlon: three sports, one number

    Most platforms add swim, bike and run stress into one combined CTL. That is useful for total workload, but it hides several problems that are specific to triathlon:

    • Different scores are calibrated differently. Power-based cycling TSS, pace-based running scores and swim scores use different thresholds and assumptions. A running score depends on an accurate threshold pace; a swim score on a realistic critical swim speed.
    • Equal scores are not equal stress. Running is weight-bearing and usually costs more musculoskeletal recovery than the same score on the bike or in the pool.
    • Some work is invisible. Strength sessions, unrecorded swims and heart-rate estimates on sessions without power or pace can make the chart overstate or understate your real load.
    • Thresholds drift. An FTP that is too low inflates every cycling score. Retest with a consistent FTP test when sessions repeatedly stop matching the numbers.

    Check the per-sport lines as well as the combined one. A combined CTL that keeps rising because of extra cycling can hide a run CTL that has stalled—or a run load that is climbing faster than your legs can handle. Our triathlon training zones guide explains how to set consistent thresholds across all three sports.

    What the model cannot tell you

    The fitness–fatigue model is elegant, but it is a simplification. Research on it points to a few important limits:

    • The constants are not personal. When researchers fitted the Banister model to elite swimmers, the individually estimated time constants had very wide confidence intervals, and some parameters were so strongly correlated that they could not be interpreted on their own. The default 42 and 7 days are convenient conventions, not measured properties of your body.
    • Different load inputs give different answers. A study comparing training-load quantification methods found that the fitness–fatigue model’s results depended on how training load was quantified.
    • It knows only what you upload. Sleep, illness, heat, travel, nutrition and life stress all change how you absorb the same TSS.
    • “Fitness” is a label. CTL measures sustained training load. Fitness—your FTP, threshold pace, durability or race result—has to be measured separately.

    A 2022 review of fitness–fatigue models in sport also highlighted conceptual issues with how these models represent fitness and fatigue. Our practical reading: the chart is a useful framework for thinking about load, not a precise forecast of how you will perform on a given day.

    A five-minute weekly PMC check

    1. Check the inputs first. Were all sessions recorded, and are FTP, threshold pace and swim threshold still current?
    2. Look at the CTL trend over four to six weeks. Is it rising, flat or falling, and is that what the plan intended?
    3. Compare this week’s TSB with the same day last week. Ignore day-to-day swings; look for a pattern of deepening fatigue across several weeks.
    4. Look at the per-sport lines. Make sure one discipline is not driving the total while another quietly falls away.
    5. Compare the chart with how you feel and perform. If key sessions, sleep and motivation are all deteriorating, reduce load—whatever the chart says.

    Frequently asked questions

    What is a good CTL for a half Ironman or Ironman?

    There is no validated target. CTL reflects the weekly load you sustain, so a better approach is to choose the hours you can repeat consistently and let CTL describe them. In our modelled beginner 70.3 build, peak weeks of about 11 hours produced a peak CTL of about 74. Full-distance training usually requires more volume and therefore a higher CTL, but the right number depends on the athlete.

    Is a negative TSB bad?

    No. During a build, TSB is normally negative because you are training above your recent average. It becomes a concern when it stays deeply negative for weeks and your sessions, sleep or mood are deteriorating as well.

    What TSB should I race at?

    The model cannot prescribe one. In our examples, sensible tapers produced a race-morning TSB between about +9 and +27, while complete rest produced +40 with a larger loss of CTL. Plan your taper from the evidence and your experience, then note your TSB before each race to learn what works for you.

    How much CTL do I lose in a week off?

    From a steady CTL of 80, seven days with no training lowers CTL to about 67.6 (−15%) and lifts TSB to about +40. That drop is the model’s arithmetic, not a measured loss of fitness. A short break after a race or during illness is often worth it.

    Does CTL measure fitness?

    Not directly. CTL measures how much training you have sustained recently. Fitness gains show up in performance markers such as FTP, threshold pace, swim pace or race results—which you need to test or race to see.

    Why are my numbers different on Strava, Garmin or TrainingPeaks?

    Each platform calculates daily load in its own way, may use different time constants and may estimate load from heart rate when power or pace is missing. Pick one platform for trend analysis and avoid comparing numbers between apps.

    Should triathletes use one combined CTL or separate CTL for each sport?

    Both. The combined line shows total workload and fatigue. The sport-specific lines show whether swim, bike and run are each progressing—and whether running load in particular is rising too quickly.

    From chart to plan

    Need a progression to put on the chart?

    Our beginner half-distance plan builds to about 11–12 hours in peak weeks with structured recovery and an automatic race-date schedule—the kind of gradual progression the model above rewards.

    Sources and methodology

    All CTL, ATL and TSB values in this guide were calculated by TriathlonLoop with the default TrainingPeaks update rules (time constants of 42 and 7 days, TSB from the previous day’s values) and checked independently in two implementations. The 70.3 build is an illustrative model, not data from a real athlete. TSS® is a registered trademark of Peaksware; TriathlonLoop is not affiliated with TrainingPeaks.

    1. TrainingPeaks Help Center: Fitness (CTL) and Form (TSB). Definitions, update formula and calculation of TSB from yesterday’s values.
    2. Calvert TW, Banister EW, Savage MV, Bach T (1976). A systems model of the effects of training on physical performance. IEEE Transactions on Systems, Man, and Cybernetics 6(2):94–102. Origin of the fitness–fatigue model.
    3. Hellard P, et al. (2006). Assessing the limitations of the Banister model in monitoring training. Journal of Sports Sciences 24(5):509–520.
    4. Vermeire KM, et al. (2021). The influence of different training load quantification methods on the fitness-fatigue model. International Journal of Sports Physiology and Performance 16(9):1261–1269.
    5. Imbach F, et al. (2022). The use of fitness-fatigue models for sport performance modelling: conceptual issues and contributions from machine-learning. Sports Medicine – Open.
    6. Impellizzeri FM, et al. (2020). Acute:chronic workload ratio: conceptual issues and fundamental pitfalls. International Journal of Sports Physiology and Performance 15(6):907–913.
    7. Wang Z, et al. (2023). Effects of tapering on performance in endurance athletes: a systematic review and meta-analysis.

    Featured photograph by Omar Magdy Tri via Pexels (Pexels License).

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