In Excel: give FORECAST.LINEAR only the two bracketing points — =FORECAST.LINEAR(x,{y1;y2},{x1;x2}) — and it returns the straight-line value between them.
Sort the table by the x column ascending; everything below depends on that order.
Locate the row below the target with =MATCH(E2,$A$2:$A$13,1), which returns the position of the largest x not greater than the target.
Use INDEX with that position and the one after it to build the two-point ranges for FORECAST.LINEAR.
Or compute it arithmetically: y1 + (x - x1) * (y2 - y1) / (x2 - x1), which makes each term visible on the sheet.
Guard the edges with IF so a target outside the table returns a message rather than a silent extrapolation.
Need it as an auditable file?
Ships inside the linked template — formula-driven, unlocked, audit-ready.
What this does
Interpolation estimates a value at an input that lies between two measurements, on the assumption that the relationship is straight between them. Passing FORECAST.LINEAR the whole table instead of the bracketing pair does something quite different: it fits a least-squares line through every point and returns a value from that fit, which is a regression estimate rather than an interpolation. Most people learn this as a sequence of clicks and forget it by next week; learning it as a pattern instead is what lets you apply it to the next, slightly different version of the problem without starting from scratch. That is the difference this page is trying to make. The difference between a quick fix and a sheet you can trust is the extra minute you spend validating “excel function interpolate”. Start on a copy or a tiny sample, keep the affected formula visible, and compare the result with the tool above before you touch the real workbook. When a formula is involved, keep the inputs labelled beside it, reference cells instead of typing values, and apply number formatting only after the result checks out. The point is a calculation you can defend to a CFO or an auditor, but the practical win is that someone else can open the file and understand what happened without asking you.
A worked example
Viscosity is 4.2 at 20 °C and 3.1 at 30 °C. At 24 °C the interpolated value is 4.2 + (24-20) × (3.1-4.2) / (30-20) = 3.76, and =FORECAST.LINEAR(24,{4.2;3.1},{20;30}) returns the same 3.76. Handing the function all twelve rows of the table would return 3.68 — a different number answering a different question. Rate tables, calibration curves and price breaks are all published at intervals, and reading the nearest row instead of interpolating is a rounding error nobody documents. A practical tip before you scale it up: build it once on a small block of test data, confirm the number against the tool on this page, and only then point it at your real sheet. That one habit catches almost every mistake while it is still cheap to fix, long before a wrong figure reaches a report or a colleague.
In Google Sheets
Everything above works in Google Sheets too. Excel and Sheets share the formula syntax used here; only the surrounding menus are arranged differently. That portability is deliberate — learn it once and it follows you between the two tools and across Windows and Mac. Nothing on this page is behind a login: the tool runs entirely in your browser, the formula is shown in full with one-click copy, and the steps work the same on Windows and Mac. That is the whole promise here — the exact answer, a way to prove it on your own numbers, and just enough context to make it stick. Treat “excel function interpolate” as a small building block rather than a chore. Once the inputs sit in their own cells and the formula reads from them, the same setup answers a dozen related questions with a tweak, and Excel keeps every dependent figure current as the data changes. The tool above is there so you can rehearse and verify before committing anything to a real workbook; the steps and worked example are there so the logic sticks. Get it right once and it stops costing you time — it starts saving it, every time the question comes back around.
Common mistakes
- Passing the entire dataset to FORECAST.LINEAR and calling the result an interpolation.
- Leaving the x column unsorted, which makes
MATCHwith match type 1 return the wrong bracketing row without any error. - Extrapolating past the ends of the table, where a straight-line assumption has nothing supporting it.
- Interpolating a curved relationship over a wide gap — fit a curve, or interpolate between closer points.
Frequently asked questions
Is FORECAST.LINEAR the same as TREND?
For a single new x they return the same value. TREND accepts an array of new x values and returns an array of results.
How do I find the two rows to interpolate between?
MATCH with match type 1 on a sorted x column gives the row below; the row after it is the upper bracket.
What about non-linear data?
Add a trendline, tick Display Equation on chart, and evaluate that equation — or interpolate between points close enough together for a line to be reasonable.
Can I interpolate a date?
Yes. Dates are numbers, so a date x column works directly, as long as the cells are real dates rather than text.