Pull Efficiency Calculator
The formula
What the pull slip tells you
The fraction of the hand’s backward sweep that actually moves the body — DPS against hand-path length, plus the pull-vs-kick speed split.
Calculation: Slip fraction = 1 − DPS/hand-path; propulsive share from pull-vs-kick speed. Enter your inputs and every substitution is shown below the result.
Reading the result
A short hand path with low slip beats a long sweep with the anchor slipping — catch first, range later.
Rules of thumb: Slip 15–40% is the club range; scullers below that
Limitations and best practice
Hand path is measured per cycle; feeding a single-arm number doubles the slip estimate.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Why measure kick speed?
Why is pull-only often faster?
Source & methodology
Scholz & de Groot propulsive analyses.
Pull Efficiency explained: formula, worked example and honest limits
You are here because you need a specific number, and you want to see how it was produced before you rely on it. Searchers land on a Pull Efficiency page for three reasons — to plan, to compare options, and to check that somebody else’s arithmetic is honest. This tool serves all three, and everything after the calculator explains the model instead of hiding it.
In Fitness & Sports the same quantity is often quoted under two or three different conventions. The formula printed above fixes one convention and applies it consistently, which is what makes results from this page comparable with each other.
Training math in Fitness & Sports converts effort into load, and load into adaptation. Pull Efficiency does the conversion: Slip fraction = 1 − DPS/hand-path; propulsive share from pull-vs-kick speed. Athletes who understand their numbers progress faster because they can separate programming from recovery — and the 15.0 % result above is exactly that separator.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here pull slip fraction = 15.0 %, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Hand path per cycle first, at ≈63.0 % of the headline for a ten-percent error either way in that input — which is the thread the rest of this guide pulls on.
Every input in Pull Efficiency, and what it does to the answer
The engine implements a single stated model: Slip fraction = 1 − DPS/hand-path; propulsive share from pull-vs-kick speed. There is no hidden coefficient and no login-gated precision — the formula printed is the formula executed, which is also what makes the result citable.
Speed with pull (m/s) (example value 1) is a quantity rather than a category — precision here is cheap and worth having. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Speed with kick only (m/s) (example value 1) is a plain measured quantity — the unit shown in the label is the unit the formula expects. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
Hand path per cycle (m) (example value 2) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
DPS with pull (m) (example value 2) is a quantity rather than a category — precision here is cheap and worth having. Replace the example with the figure from your own records — the tool recomputes instantly and the printed steps follow your numbers.
The default Pull Efficiency calculation, written out in full
Abstract formulas are hard to trust, so here is the complete substitution using the default inputs, written the way an examiner would want it. Starting figures: Speed with pull (m/s), Speed with kick only (m/s), Hand path per cycle (m), DPS with pull (m). Run to the end, the pull slip fraction resolves to 15.0 % — 15% of the hand’s path is lost to slip — the usual club band: the hand pushes water backward; pull generates ~60% of combined speed share on the bands this tool uses.
- Slip = 1 − DPS/hand-path = 1 − 1.70/2.00 = 0.15
- Efficiency = 85% of hand travel converted to body travel
- Sculling drills and high-elbow catch reduce the gap
Catch efficiency — 85.0 %. This is the number experienced users quote when the headline alone would mislead.
Pull vs kick speed ratio — 1.50. Compare it against the main result of 15.0 % before drawing conclusions.
Slip m per stroke — 0.30. Read next to the headline, this is the figure that shows the shape of the trade-off.
Paddles test — big paddle gain = slip problem. Read next to the headline, this is the figure that shows the shape of the trade-off.
Re-running with your own figures is instant; re-running by hand once is the best way to know the tool is telling you the truth.
How far Pull Efficiency can reasonably move
Read this table as the practical error bar on the headline figure. It answers the question people actually have after seeing a single number: how wrong could this be if the main input is off by ten or twenty percent?
| Hand path per cycle setting | Pull slip fraction |
|---|---|
| 80 % of the example value | -6.3 % |
| 90 % of the example value | 5.6 % |
| example inputs | 15.0 % |
| 110 % of the example value | 22.7 % |
| 120 % of the example value | 29.2 % |
The corridor runs from -6.3 % to 29.2 % across that band — which is the range worth planning inside rather than the single 15.0 % point estimate. Reproduce it in the form above by editing Hand path per cycle alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change Pull Efficiency the most
This list was computed for this specific engine just now: each numeric input was nudged ±10 % while every other field held its example value, and the pull slip fraction was recalculated from scratch. For Pull Efficiency the ranking is measured rather than guessed, and it belongs to these defaults: shift the starting point and the order can shift with it.
- Hand path per cycle: ten percent up gives 22.7 %, ten percent down gives 5.6 % — ≈63.0 % of the pull slip fraction either way
- Nudge DPS with pull by ±10 % and Pull Efficiency lands between 6.5 % and 23.5 % (sensitivity ≈56.7 %)
Hand path per cycle is the dominant lever here: ten percent either way moves the result by about 63.0 %, from 5.6 % to 22.7 %. Spend your verification effort there first, and treat DPS with pull as the second priority (≈56.7 % per ten percent). Everything below that can stay approximate, which is a licence to stop chasing data that would not change the decision.
Is your Pull Efficiency good — reading the result bands
A number on its own is trivia; a number against a range is intelligence. The verdict attached to the default calculation — “15% of the hand’s path is lost to slip — the usual club band: the hand pushes water backward; pull generates ~60% of combined speed share” — is one band on a ladder your own figure may sit somewhere else on. How much of that band is luck? On Hand path per cycle alone ten percent either way covers 5.6 % to 22.7 %. The practical reading rules: ask what would have to change to move you one band. If the answer is “a small, plausible input difference”, the band itself is not the finding — the uncertainty is.
In Fitness & Sports, Pull Efficiency is one instrument in an orchestra: on its own it is a number, next to Catch efficiency and Pull vs kick speed ratio it becomes a diagnosis. The tools linked above exist so the headline never has to carry that weight alone.
How people get Pull Efficiency wrong
Hand path is measured per cycle; feeding a single-arm number doubles the slip estimate. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Reporting the headline and quietly discarding Catch efficiency. The companions are where the shape of the trade-off survives the rounding.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: Hand path per cycle first, everything else second.
Another is comparing across contexts: a Pull Efficiency computed with one set of conventions should never be lined up against a figure computed with another. Check the inputs behind both before ranking them.
Before you trust your Pull Efficiency: a short checklist
- Verify each input against its original source document, not memory.
- Compare the result with one independent method or published benchmark.
- Re-verify Hand path per cycle against a source document — ten percent of error there moves the headline by ≈63.0 %.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Confirm the example values are plausible for your own situation before replacing them.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
A routine for decision-grade Pull Efficiency
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — gather before you type. Pull Efficiency depends on speed with pull (m/s), speed with kick only (m/s), hand path per cycle (m), dps with pull (m). Collect them from a source document — a statement, a report, an invoice, a log — rather than from memory, because recalled inputs are the single largest cause of wrong results. If the answer changes your behaviour, it deserves a second run with different assumptions.
Step 2 — enter the conservative case first. Resist the flattering scenario. Type the inputs you would defend in front of a sceptical reader, read the Pull slip fraction (15.0 % for the example values), and note the verdict band. Rounding early is the quietest way to introduce a permanent error.
Step 3 — measure what deserves measuring. The ranked levers above tell you where a careful figure pays off. Everything else can stay approximate, which is a licence to stop hunting for data you do not need. When in doubt, prefer the boring input: the interesting one is usually the one you misread.
Step 4 — run the scenario trio. Expected, pessimistic, optimistic. The gap between pessimistic and expected is the number to plan against; the optimistic result is useful only as a ceiling. The inputs are the part of the work that nobody else can do for you.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the 15.0 % output. Six months from now the context is what turns this figure into a trend. Half of a good calculation is knowing which input you would hate to be wrong about.
The real-world conversations Pull Efficiency settles
Numbers earn their keep in conversations, and Pull Efficiency is no exception. In Fitness & Sports discussions around Swimming, this figure decides whether an option stays on the table: it converts an opinionated debate into an arithmetic one, and arithmetic is the only referee both sides accept. Numbers are cheap to produce and expensive to retract; the extra minute is the cheapest insurance available.
The audience for this page is people who need one trustworthy number before their next decision. In professional Swimming practice the pattern is always the same — screen with Pull Efficiency, then invest slow analysis only in whatever survives the screen. Repeating a calculation with the same numbers proves only that the arithmetic is reliable — which is worth knowing.
Re-running this page costs nothing and catches the slow drifts that never announce themselves. In Fitness & Sports the expensive mistakes are rarely sudden; they are small changes in Speed with pull (m/s) that nobody recalculated for a year. Comparisons are cheap: run the identical calculation for the alternative and look at the gap.
Pull Efficiency — frequently asked questions
What affects Pull Efficiency the most?
The short answer: Hand path per cycle. The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the pull slip fraction recalculated — Hand path per cycle moved it furthest, by roughly 63.0 % (5.6 % to 22.7 %).
Which matters more: dps with pull or hand path per cycle?
Hand path per cycle, by a factor of about 1.1. Concretely: ten percent on Hand path per cycle is worth ≈63.0 % of Pull Efficiency, the same nudge on DPS with pull only ≈56.7 %. That ranking is re-computed for each page from that page’s own defaults.
What is a typical Pull Efficiency?
There is no honest universal average for Pull Efficiency, but there is a reference point: the defaults on this page produce 15.0 % (15% of the hand’s path is lost to slip — the usual club band: the hand pushes water backward; pull generates ~60% of combined speed share). Replace the inputs with your own and compare — that comparison is the useful meaning of “typical”.
How do I calculate Pull Efficiency by hand?
Three steps: write the formula (Slip fraction = 1 − DPS/hand-path; propulsive share from pull-vs-kick speed), insert your values, and simplify. The worked example section shows exactly that chain for the default inputs; replicating it once on paper teaches you more about Pull Efficiency than any number of calculator runs.
What happens to Pull Efficiency if hand path per cycle changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the pull slip fraction goes across 5.6 % to 22.7 %, a swing of roughly 63.0 % around the 15.0 % baseline. That ratio is the practical definition of how much this input matters.
Is the Pull Efficiency result of 15.0 % good or bad?
Neither, on its own — the label “15% of the hand’s path is lost to slip — the usual club band: the hand pushes water backward; pull generates ~60% of combined speed share” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives, and remember that a ten-percent error in Hand path per cycle alone moves it by ≈63.0 %.
How do I calculate Pull Efficiency manually?
Write down the inputs, then follow the printed steps in order — Slip fraction = 1 − DPS/hand-path; propulsive share from pull-vs-kick speed. A spreadsheet replicates it with two or three cells. The manual route is worth doing once to build intuition; after that the calculator saves time and eliminates transcription slips.
Is Pull Efficiency individualized?
Partly — the tool is mechanical on the inputs you provide (Speed with pull (m/s), Speed with kick only (m/s)); what varies person-to-person is the response. Start at the computed 15.0 %, adjust by results within a few sessions.
Why measure kick speed?
It isolates the pull contribution — paddled-pull minus kick-only is the propulsive split.
Why is pull-only often faster?
The kick sinks the hips and adds drag, so pull-only isolates upper-body propulsion cleanly.
Can this tool see the numbers I type?
It cannot. There is no submission step: the calculation happens in your browser and the result disappears when you close the page. Treat the fields above as a scratchpad rather than a form.
What the labels on this page mean
- Catch efficiency
- 85.0 % for the Pull Efficiency worked case; it sits next to the main result because it carries context the headline leaves out.
- Pull vs kick speed ratio
- 1.50 on the example inputs — a companion figure printed beside the headline of Pull Efficiency so that no result is read in isolation.
- Slip m per stroke
- 0.30 on the example inputs — a companion figure printed beside the headline of Pull Efficiency so that no result is read in isolation.
- Pull slip fraction
- The primary output of this tool: 15.0 % for the default inputs, computed exactly from Slip fraction = 1 − DPS/hand-path; propulsive share from pull-vs-kick speed.
- Worked example
- The step-by-step substitution printed above, so the arithmetic can be re-derived by hand or in a spreadsheet.
- Verdict band
- The plain-language label — here “15% of the hand’s path is lost to slip — the usual club band: the hand pushes water backward; pull generates ~60% of combined speed share” — mapping the computed figure onto experience-based ranges for Fitness & Sports.
- Sensitivity (±10 %)
- How far the Pull Efficiency moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
The provenance of this Pull Efficiency calculation
Everything above runs on one stated formula, applied without hidden coefficients: Slip fraction = 1 − DPS/hand-path; propulsive share from pull-vs-kick speed. Source of record: Scholz & de Groot propulsive analyses. Specialist software layers extra coefficients on top of the same algebra; none are hidden here, and that transparency is what makes a disagreement traceable to a specific input instead of a black box.
Treat the output as a precise answer to the question you typed: exact arithmetic, transparent formula, published source, no hidden rounding. The promise to the reader is narrow and testable: same inputs, same output, no silent rounding, and no figure presented without the formula that produced it.
After the number: what to do with it
Save the number together with its inputs and today’s date; a Pull Efficiency figure without context is unusable the moment an input changes.
Whoever you are (people who need one trustworthy number before their next decision), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Fitness & Sports, a dated figure is a trend, and an undated one is a rumour.