Reading the Ride Log Overlay on a Calibration Map
Every calibration map in MotoTunePro USA has a Ride Log tab that lays your actual logged riding over the same RPM × throttle grid as the tune. What the colors mean, why some cells are blank, what the nine overlay modes each measure, and how to turn any of it into a real fuel-map correction instead of a guess.
What the Overlay Is
Open any map in the Map Editor and switch to its Ride log tab and you get a second grid, drawn at exactly the same cell size as the tuning grid above it. That alignment is not cosmetic — the overlay shares the map's own row and column breakpoints, so overlay cell (row 4, column 9) describes precisely the same RPM × throttle (or RPM × TP%) window as tuning cell (row 4, column 9). Whatever the overlay tells you about a cell, that is the cell you would edit to act on it.
The data behind the overlay comes from one of two places, chosen with the Ride selector above the grid: the live session — whatever telemetry has streamed in since you connected this time — or any saved ride recorded and kept on the device. A saved ride overlays identically to a live one; recording a ride, closing the app, and reviewing it the next day loses nothing.
Every sample the app logs — RPM, throttle, lambda, fuel trim, acceleration, engine temperature, whatever the connected ECM and sensors provide — gets binned into the map cell whose RPM and throttle breakpoints it's nearest to. A ride with ten thousand samples becomes, at most, one number per cell: an average, a count, or a total, depending on which overlay mode you have selected.
One grid, nine questions. The overlay grid never changes shape. What changes is which question you're asking it — how often you were here, how long you stayed, how far off target the mixture ran. That question is the mode dropdown next to the ride selector.
The Nine Overlay Modes
They are kept as nine separate readouts rather than one blended “tune quality” score on purpose. A blended number has no unit and nothing to check it against; nine honest ones do.
| Mode | What it answers | Unit |
|---|---|---|
| Cell visits | Raw count of logged samples in this cell | samples |
| Dwell time | Total seconds spent in this cell, weighted by real sample spacing | seconds |
| Share of ride | What fraction of the whole ride's time landed in this cell | % |
| Lambda error | Measured lambda minus your target lambda. Positive is leaner than target, negative is richer | λ |
| Fuel correction | Average closed-loop / adaptive fuel trim the ECM applied | % |
| Throttle | Average throttle position logged in this cell | % |
| Acceleration | Average forward acceleration while in this cell | ft/s² |
| Engine temperature | Average engine temperature logged in this cell | °F |
| Data coverage | Same count as Cell visits, meant to be checked first — how well-sampled the ride was here at all | samples |
Lambda error needs a wideband sensor connected during the ride — the overlay says so directly if you select it without one. Its target isn't fixed: a field above the grid lets you type a target lambda (the app defaults to 0.90, and accepts anything a spark engine could plausibly run, roughly 0.5 to 1.5) so the same overlay works whether you're checking a cruise cell against a near-stoichiometric target or a wide-open-throttle cell against a richer one.
Reading the Colors
The overlay uses two different color systems, and which one applies depends entirely on whether the mode you picked has a meaningful zero.
One-Way Modes: Visits, Dwell, Share of Ride, Throttle, Engine Temperature, Data Coverage
These six have no natural zero-point to center on — more samples, more dwell time, higher throttle, and higher temperature are just “more.” They render on a single heat ramp, scaled to whatever range actually appears on this map: blue at the low end, through teal and amber, to orange-red at the high end. In Cell visits, for example, a red cell is one you hammered on this ride; a blue cell is one you barely touched. The ramp is always relative to this ride's own min/max, not to some fixed scale — a “red” cell on a 20-minute commute and a “red” cell on a two-hour canyon run do not mean the same absolute sample count.
Diverging Modes: Lambda Error, Fuel Correction, Acceleration
These three are centered on zero on purpose, because the sign is the whole point — lean versus rich, adding fuel versus removing it, speeding up versus slowing down. Zero renders as a neutral gray. Moving away from zero in one direction shifts toward blue; moving the other way shifts toward orange-red. For Lambda error specifically: red cells ran leaner than your target, blue cells ran richer. The scale is symmetric around zero across the whole map, so a red cell and a blue cell of the same intensity are equally far off target in opposite directions — one is not exaggerated relative to the other.
Red in Lambda error is the cell to look at first. A lean cell under load is where detonation risk and engine heat live. Community consensus for an air-cooled V-twin at full throttle is roughly 12.5–13.2:1 AFR — if a high-load cell shows solid red against that target, that is the correction to make before anything cosmetic.
Blank Cells, Thin Cells, and the Dash
The overlay draws three different “something is missing here” states, and they mean three different things. Mixing them up is how a rider ends up trusting a cell that was never actually measured.
- A blank cell (no color, no number) means the engine never visited that RPM/throttle combination on the selected ride — zero samples. It is left empty on purpose rather than painted as a zero: a colored zero on the same ramp as real readings would look identical to “tested and measured zero,” and that is exactly how an untested region of a map gets assumed safe.
- A dark cell showing a dash (—) means the engine did visit, but the specific mode you have selected has no reading there — most often Lambda error selected on a ride where no wideband was connected, so visits and dwell can still show real numbers for that same cell while Lambda error shows a dash.
- A colored cell with a light gray outline has a real reading, but fewer than 30 samples backing it up. It is still colored and labeled — the outline is a warning, not a blank. Treat it as directional, not settled: a single outlier sample can still move a thin cell's average noticeably.
Hover (or tap, on a touch screen) any cell for its tooltip, which spells out the exact value, the sample count and coverage tier behind it, and the dominant operating regime the ECM was in while those samples were collected — steady state, accelerating, decelerating, or wide-open throttle. A cell whose dominant regime is “Accelerating” is telling you the average partly reflects a transient sweep through the cell, not time spent settled there — useful context before you trust an AFR reading enough to change fuel.
The Sample-Count Tiers
Underneath the colors, every cell is scored by how much log data actually stands behind it. This is deliberately a plain sample-count rule, not a statistical confidence number — inventing a percentage confidence out of a raw count would be exactly the kind of false precision a tuner should distrust.
| Tier | Samples | What you can do with it |
|---|---|---|
| No data | 0 | Nothing — the cell is blank |
| Insufficient | 1–4 | The count itself is a fact; do not draw an AFR or trim conclusion yet |
| Moderate | 5–29 | Directional reading — the thin-outlined cells. One outlier still moves the average |
| Strong | 30+ | Stable average, no outline — safe to act on |
Visits, dwell, share of ride, and Data coverage are exempt from the “don't draw a conclusion” rule — a count of three really is an exact fact about the log even when three samples cannot characterize an AFR average. It is the value-bearing modes (Lambda error, Fuel correction, Throttle, Acceleration, Engine temperature) where the tier decides whether the number is a conclusion or just a data point.
From Overlay to Map Changes
The overlay is a read-only diagnostic — it never edits the map itself. Turning it into an actual fuel-map change is a short, repeatable loop.
- 1.Switch to Data coverage first. Confirm the cells you actually care about tuning — cruise, roll-on, or wide-open throttle, depending on what you're chasing — have real samples in them before you trust anything else about them.
- 2.Set your target lambda correctly for the region you're reviewing, then switch to Lambda error. Red cells need fuel added, blue cells need fuel removed, gray cells are already on target.
- 3.Cross-check with Throttle and each cell's tooltip regime. A red Lambda-error cell whose dominant regime is “Accelerating” is telling you something different than one that's solidly “Steady state” — a transient sweep and a settled cruise point deserve different amounts of trust.
- 4.Skip the thin-outlined cells for now. Note them, then go get more miles there before making a real fuel change on 6 samples.
- 5.Edit the corresponding cell in the Map Editor, flash, and log a new ride to confirm the correction landed where you intended before moving to the next region.
A red wide-open-throttle cell is the one that matters most. A lean reading at part-throttle cruise is a rideability annoyance; a lean reading at full load is a heat and detonation risk on an air-cooled engine. If the overlay shows a strongly-supported lean cell anywhere near wide-open throttle, that is the correction to make first — not the cosmetic cruise-region smoothing.
Glossary
Overlay cell
One RPM × throttle (or TP%) bin, sharing the exact grid geometry of the tuning map it sits on. Same row/column, same breakpoints.
Blank cell
Zero logged samples landed here — deliberately left uncolored rather than shown as zero, so an untested region can never be mistaken for a measured one.
Dash (—)
The cell was visited, but the selected overlay mode has no reading for it (most commonly Lambda error with no wideband connected).
Thin-outlined cell
A real reading backed by 5–29 samples (the Moderate coverage tier). Directional, not yet a stable average.
Diverging mode
An overlay mode centered on zero — Lambda error, Fuel correction, Acceleration — where the sign of the number is the meaning, not just its size.
Lambda (λ)
Measured air/fuel ratio expressed as a fraction of stoichiometric. Lambda error is measured lambda minus a target you set; positive is leaner, negative is richer.
Target lambda
The lambda you are checking a cell against in Lambda error mode. Editable per review, defaulting to 0.90.
Operating regime
What the engine was doing during the samples in a cell — Steady state, Accelerating, Decelerating, or Wide open throttle — shown in every cell’s tooltip.
Data coverage
Both the name of one overlay mode and the general concept: how much real log data backs a cell, from No data through Strong.
Provenance
A short tag (Logged, Calculated) shown with every value, naming whether it came straight from the log or was derived from it — never presented as a bare, unqualified number.
Check coverage before conclusions, red means lean, blank means untested — then ride more before you trust the thin cells.
MotoTunePro USA is not affiliated with Buell Motorcycle Company or any third-party tuning-tool vendor. All trademarks belong to their respective owners. This guide is for education — modifying engine calibration can affect reliability, emissions compliance, and warranty.