How to Answer “What is a football field valuation, and how would you build one?” in Investment Banking Interviews
In football field valuation interview prep, this is a go-to Investment Banking analyst question because it combines valuation knowledge with pitchbook-style communication.
When an interviewer asks, “What is a football field valuation, and how would you build one?”, they want you to define the output (a chart of ranges), name the core investment banking valuation techniques that feed it, and walk through a clean, repeatable build process with consistent assumptions.
What Interviewers Test: Valuation Analysis Under Time Pressure
Interviewers are primarily checking that you understand the football field is a presentation of valuation analysis—not a separate valuation method. You should be able to explain what the bars represent (low-to-high implied value ranges) and why bankers use this format in pitchbooks to compare methods quickly.
They also test technical judgement across valuation methods in investment banking: which methods make sense for the situation (trading comps, precedent transactions, DCF, sometimes LBO/SOTP), and how you keep the ranges conceptually consistent (enterprise value vs equity value, LTM vs NTM denominators, adjustments to EBITDA, treatment of leases, pensions, minorities, and other claims).
Finally, this is about analyst execution and clarity. Strong candidates outline a step-by-step workflow, mention how ranges are constructed (percentiles, low/median/high, DCF sensitivities), and add quick sanity checks that prevent a chart that “looks right” but is inconsistent or misleading.
Football Field Valuation Explained: A Step-by-Step Build Framework
- 1
Step 1: Define the football field valuation and the unit of value
A football field valuation is a chart that summarises multiple implied valuation ranges side-by-side, usually as horizontal bars from “low” to “high.” Each bar corresponds to one method (for example, trading comps EV/EBITDA), helping the team and the client see where methods overlap and where they diverge.
In interviews, explicitly state what the chart is measured in. Many pitchbooks start with enterprise value (EV) because it’s capital-structure neutral, and then optionally show an implied equity value per share by applying the same EV→equity bridge (subtract net debt and other claims; divide by diluted shares).
Also clarify what “range” means: it could be a percentile band of observed multiples, low/median/high, or a sensitivity band (for DCF). This framing is the difference between “football field valuation explained” conceptually and described in a way you could actually build as an analyst.
- 2
Step 2: Select the methods and set consistency rules upfront
Choose 3–6 methods you can support with data and that fit the company and context. Common investment banking valuation techniques include:
- Trading comparables (e.g., EV/EBITDA, EV/Revenue, P/E depending on sector)
- Precedent transactions (often higher due to control and synergies)
- DCF (intrinsic value via discounted free cash flows)
- Sometimes LBO (sponsor “floor”), SOTP, or sector-specific frameworks
Before calculating anything, set consistency rules that keep the football field auditable:
- EV vs equity value: pick one basis for the chart and stick to it.
- Time period: align LTM vs NTM; don’t apply NTM multiples to LTM metrics.
- Metric definitions: ensure EBITDA (or EBIT, revenue, EPS) uses the same adjustments across methods.
- Conversion bridge: if showing equity value per share, apply the same treatment of net debt, preferreds, minorities, pensions/leases (as applicable) and share count.
This is a core part of investment banking interview strategies: showing you can avoid apples-to-oranges ranges.
- 3
Step 3: Build low-to-high ranges for each method with defensible drivers
For each methodology, compute a low and high implied value (and often a midpoint) and be ready to explain what drives the spread.
Trading comps: build the peer set, calculate relevant multiples, then choose a range (e.g., 25th–75th percentile, or low/median/high after removing clear outliers). Apply that multiple range to the company’s corresponding metric (LTM or NTM) to get an implied EV (or equity) range.
Precedent transactions: collect deal multiples, normalise for deal context where appropriate, then apply a chosen multiple band to the company’s metric. Be explicit that precedents can screen higher due to control premiums and expected synergies.
DCF: create a range via a sensitivity table (commonly WACC × terminal growth, or WACC × exit multiple). Use a reasonable band rather than extreme corners.
If the question pushes for “how to create a football field valuation for interviews,” emphasise that the range should be explainable—not just mechanically wide.
- 4
Step 4: Build the chart in Excel and label it like a pitchbook output
Mechanically, a football field is typically a horizontal stacked bar chart. You store “Low” and “High” (or “Low” and “Spread = High−Low”). In the chart, the first series (Low) is formatted as invisible to offset the bar, and the second series (Spread) is the visible coloured bar.
To make it pitchbook-ready:
- Group and order methods logically (market-based vs intrinsic; or by relevance).
- Clearly label the axis and units (e.g., “Implied Enterprise Value ($mm)” or “Implied Price Per Share ($)”).
- Add the multiple or assumption ranges next to each bar (e.g., “8.0x–10.0x NTM EBITDA”) so the work is traceable.
- Keep formatting consistent: rounding, currency, colours, and axis scale.
This is where “football field valuation examples for investment banking” tend to differ: the best ones are easy to audit and easy to narrate in a client conversation.
- 5
Step 5: Sanity-check, reconcile differences, and prepare the talk track
Before sending it up the chain, do quick checks that mirror real review comments:
- Relative ordering: do precedents generally sit above trading comps (control/synergies), and does the DCF sit in a reasonable place given growth and margins?
- Current reference point: if the company is public, do implied equity values relate sensibly to the current share price (and can you explain gaps)?
- Outliers: confirm that one extreme multiple or an edge-case DCF sensitivity isn’t driving the story.
- Consistency: confirm the same metric timing/definitions and the same EV→equity bridge for every bar.
Then prepare a 30–60 second explanation: what each bar is, why the ranges differ, and where the overlap suggests a reasonable valuation discussion. That’s the “step-by-step guide to football field valuation” interviewers are really looking for: correct mechanics plus clear interpretation.
Model Answer Using Investment Banking Valuation Techniques
A football field valuation is a chart that summarises the implied valuation ranges from several methods—like trading comparables, precedent transactions, and a DCF—shown side-by-side as horizontal bars. It isn’t a standalone valuation method; it’s a way to compare outputs quickly and see where they overlap.
To build one, I’d first decide the basis, typically enterprise value, and set consistency rules upfront—same LTM vs NTM metrics, consistent EBITDA adjustments, and a consistent EV-to-equity bridge if I’m showing price per share. Then I’d build the ranges for each method. For trading comps, I’d choose a peer set, take a defensible multiple band like 25th to 75th percentile EV/EBITDA, and apply it to the company’s EBITDA to get an implied EV range. For precedent transactions, I’d do the same using deal multiples, recognising those often screen higher because of control premiums and expected synergies. For the DCF, I’d create a valuation range using a sensitivity around WACC and terminal assumptions rather than relying on a single point estimate.
Finally, I’d lay the outputs into a horizontal bar chart in Excel, label each bar with the underlying multiple or assumption range, and sanity-check the results for consistency and reasonableness versus current trading and versus each other.
- Open by defining it as an output chart of ranges (not a separate method).
- Name 3 core methods and how each produces a “range” (percentiles vs deal multiples vs DCF sensitivities).
- Show analyst judgement: consistency on EV vs equity value, timing (LTM/NTM), and metric adjustments.
- Add one real-world driver to explain differences (control premium, synergies, growth/cyclicality).
- Keep the first 2 sentences crisp so they can stand alone if the interviewer cuts you off.
Common Mistakes in Football Field Valuation and Range Building
- Describing the football field as a valuation methodology rather than a way to present multiple valuation ranges.
- Mixing enterprise value and equity value on the same chart (or converting only some bars to per-share).
- Applying mismatched multiples and denominators (e.g., NTM multiple applied to LTM EBITDA) or inconsistent EBITDA adjustments.
- Using extreme DCF sensitivity corners or one-off transaction outliers that artificially widen the range without explanation.
- Omitting labels/assumptions behind each bar, making the chart hard to audit and easy to challenge.
- Focusing only on chart mechanics and not explaining what drives differences and where the overlap suggests value.
Follow-Ups on Valuation Methods in Investment Banking
Which valuation methods belong on a football field for a loss-making, high-growth company?
You’d typically emphasise revenue-based trading comps and precedents, and use a DCF only if cash flows become meaningful; EBITDA multiples may be less relevant if EBITDA is negative.
How do you pick the multiple range for trading comps?
Use a consistent rule like 25th–75th percentile or low/median/high after removing clear outliers, and sanity-check peers for similar growth, margins, and risk.
Why do precedent transactions often imply higher values than trading comps?
Precedents usually include a control premium and may reflect expected synergies, plus deal markets at the time of signing rather than today’s spot trading.
If the chart is in equity value per share, what do you adjust for when converting from EV?
Subtract net debt and other non-common claims (e.g., preferreds, minorities, pensions/leases as relevant), then divide by diluted shares using a consistent share count across methods.
What quick checks would you do before sending the football field to an associate?
Confirm consistent timing/definitions, verify the EV→equity bridge, check for outlier-driven ranges, and ensure the ordering makes sense (precedents vs comps vs DCF).
Practice Plan: Investment Banking Interview Strategies for Analysts
- Practise a 60–90 second answer that hits: definition → methods → how ranges are built → consistency checks.
- Build a simple Excel template once (low/high inputs + stacked bar chart) so you can explain the mechanics without getting lost.
- Drill the “consistency rules” aloud (EV vs equity, LTM vs NTM, adjustments) since that’s where many candidates slip.
- Do a timed mock on AceTheRound focused on comps + precedents + DCF outputs, and ask for feedback on whether your ranges and talk track sound coherent.
Ready to practice with AceTheRound?
Create an account to unlock AI mock interviews, feedback, and the full prep library.