Football Field Valuation Chart in Excel: Banker's Guide (2026)

May 28, 2026 · VeloraAI Team
Data Analysis Financial Modeling Excel

Every M&A pitch book and fairness opinion lives or dies on one slide: the football field valuation chart. It is the single page where a managing director points and says, "here is the range." Get the bars right and the room nods. Get them wrong — wrong methodology, mis-flexed assumptions, axis cut at the wrong number — and the entire deck loses credibility.

This guide walks through how to build a football field valuation chart in Excel from scratch: the methodologies that belong on it, the stacked-bar trick that makes the bars "float," the reference markers that frame the conversation, and the formatting choices that separate an analyst draft from a pitch-ready exhibit. By the end you will be able to build one in under twenty minutes and defend every bar in it.

What Is a Football Field Valuation Chart?

A football field valuation chart is a horizontal floating-bar chart that displays the implied price-per-share or enterprise-value range from several independent valuation methodologies on a single axis. Each methodology gets one bar showing its low-to-high range, plus reference markers for the current trading price and any offer price.

The chart is the visual synthesis of an entire valuation workstream. Rather than presenting a table of numbers across five tabs of a model, the football field collapses everything onto one slide so a board, committee, or counterparty can immediately see where the methodologies converge, where they diverge, and where the proposed deal price sits relative to the range.

Why bankers and PE deal teams rely on it

  • Triangulation. No single methodology is right. A DCF is sensitive to WACC and terminal growth, trading comps depend on peer selection, and precedent transactions reflect a different market cycle. The football field forces the reader to weigh the evidence.
  • Defensibility. Fairness opinions, board decks, and Delaware litigation all assume the advisor considered multiple methods. The chart is the proof.
  • Negotiation framing. Buyers point to the bottom of the range; sellers point to the top. The picture sets the goalposts for the discussion.

ℹ️ Note: The name comes from the visual resemblance to a football field viewed from the sideline — parallel horizontal bars stacked like yard lines. It has nothing to do with sports statistics.

Which Valuation Methodologies Belong on a Football Field?

The football field should include three to seven methodologies. Too few and the chart looks thin; too many and the reader cannot process the differences. The selection depends on the company, the sector, and the purpose of the analysis.

Standard methodologies

Methodology What it shows Typical range driver
52-week trading range Market's recent view of the standalone company Daily high/low over trailing year
Equity research price targets Sell-side analyst consensus Min/max of covering analysts
Trading comparables (EV/EBITDA, EV/Revenue, P/E) Market multiples applied to target metrics 25th–75th percentile of peer set
Precedent transactions Multiples paid in recent deals 25th–75th percentile of comparable deals
Discounted cash flow (DCF) Intrinsic value from projected free cash flows WACC ± 100 bps, perpetuity growth ± 50 bps
Leveraged buyout (LBO) floor Maximum a financial sponsor could pay for a target IRR 20%–25% sponsor IRR sensitivity
Premiums paid analysis Implied price from typical control premiums 25th/75th percentile of one-day premiums

Situation-specific methodologies

  • Sum-of-the-parts (SOTP) for conglomerates or companies with distinct business lines that warrant different multiples.
  • Liquidation or NAV for asset-heavy or distressed companies (real estate, financials, holdings).
  • Replacement cost for infrastructure, energy, and industrial assets.
  • Dividend discount model (DDM) for banks, insurance, and mature dividend-payers where free cash flow is hard to define.

💡 Pro Tip: Order the bars from most market-based at the top (52-week range, analyst targets) to most intrinsic at the bottom (DCF, LBO). The eye reads top-to-bottom, and that order tells a story: "here is what the market thinks, and here is what the cash flows are worth."

How Do You Build a Football Field Chart in Excel?

To build a football field chart in Excel, lay out a table with each methodology's low and high values, add a helper column equal to (High − Low), insert a 2D stacked bar chart from the Low and Difference columns, set the Low series fill to "No Fill," and reverse the category axis so the first methodology appears at the top.

That is the 60-second version. The full build has eight steps.

Step 1: Lay out the source data

Create a table with one row per methodology. The first column is the label, the next two are the low and high implied prices (or enterprise values), and the fourth is a calculated helper.

A                          B          C           D
Methodology                Low        High        Difference
52-Week Range              42.10      58.75       =C2-B2
Analyst Price Targets      48.00      65.00       =C3-B3
Trading Comps (EV/EBITDA)  51.20      63.40       =C4-B4
Precedent Transactions     55.80      71.20       =C5-B5
DCF (WACC 8.5%–10.5%)      53.40      68.90       =C6-B6
LBO (20%–25% IRR)          47.50      58.00       =C7-B7

The Difference column is the trick. Excel cannot draw a free-floating bar, so we use a stacked bar where the first segment is invisible (the Low value) and the second segment is the visible range (High minus Low).

Step 2: Insert a 2D stacked bar chart

  1. Select the range covering Methodology, Low, and Difference (skip the High column — it is reference only).
  2. Insert → Charts → 2D Bar → Stacked Bar.
  3. Excel will produce a chart with two segments per row: a colored Low segment and a colored Difference segment.

Step 3: Make the Low series invisible

Click the Low series in the chart. Format Data Series → Fill → No Fill. Border → No Line. The Low segments disappear, leaving only the Difference bars floating at the correct positions on the axis.

⚠️ Warning: Do not delete the Low series — you only hide it. If you delete it, every bar collapses back to starting at zero and the chart breaks.

Step 4: Reverse the category axis

By default, Excel plots the first row at the bottom. Click the vertical (category) axis → Format Axis → Categories in reverse order. Also check Horizontal axis crosses at maximum category so the value axis stays at the bottom. Now your methodology order reads top-to-bottom as written in the table.

Step 5: Set the value axis range manually

Auto-scaled axes lie. If your range is $40–$72 and Excel auto-scales to 0–80, the bars look short and the differences shrink visually. Right-click the value axis → Format Axis → set Minimum to a round number just below your lowest Low (e.g., 40) and Maximum just above your highest High (e.g., 75).

Step 6: Add value labels at the ends of each bar

Click the Difference series → Add Data Labels → Format Data Labels. Check Value From Cells and select the High column for the high-end label, then add a second set of labels positioned at the Inside Base showing the Low column. The result: each bar is annotated with its low and high values, exactly as it would appear in a pitch deck.

Step 7: Add reference markers (current price, offer price)

This is what elevates the chart from generic to pitchable. Add two vertical lines:

  • Current share price — what the stock trades at today.
  • Offer price — the proposed deal price (if applicable).

The cleanest way is to add a scatter series:

Reference Series                X         Y
Current Price (low)            56.40      0
Current Price (high)           56.40      7
Offer Price (low)              62.00      0
Offer Price (high)             62.00      7

Add these as a new scatter series on the secondary axis, set the line style to a thin dashed line, hide the markers, and align the secondary Y-axis range to (0, number of methodologies). Add a label at the top of each line ("Current: $56.40", "Offer: $62.00").

Step 8: Format for pitch-deck quality

  • Remove gridlines.
  • Set bar gap width to 50%–75% so bars are thick but not touching.
  • Color all Difference bars the firm's primary brand color, except the LBO bar (often a lighter or accent color since it is a "floor," not an offer).
  • Remove the legend if the labels are self-explanatory.
  • Title: "Implied Equity Value per Share."
  • Axis title: "$ per share" with a note "Source: Company filings, Capital IQ, [Firm] estimates."

Example: For a target trading at $56.40 with a $62.00 offer, the football field shows that the offer falls within the DCF and trading comps ranges but above the LBO floor — a defensible "fair" deal that the board can support.

What Does the Underlying Data Flow Look Like?

Every bar on the chart is the output of a separate model or analysis. Understanding the upstream flow makes the chart easier to audit and update.

graph TD
    A[Trading Comps Model] --> H[Football Field Data Table]
    B[Precedent Transactions Model] --> H
    C[DCF Model with WACC Sensitivity] --> H
    D[LBO Model with IRR Sensitivity] --> H
    E[52-Week Price Data Pull] --> H
    F[Analyst Consensus Pull] --> H
    G[Premiums Paid Study] --> H
    H --> I[Low / High / Difference Columns]
    I --> J[Stacked Bar Chart with No-Fill Low Series]
    J --> K[Add Current Price and Offer Markers]
    K --> L[Pitch-Ready Football Field Exhibit]

The football field chart is downstream of every other valuation tab in your workbook. Build it last, after each methodology has been independently sanity-checked. If you wire it up early, every change to your DCF re-flows through the chart and you will spend more time formatting than analyzing.

How Do You Define the Range for Each Methodology?

Each methodology needs a defensible low and high. Picking a single number from a DCF or a comp set and calling it a "range" is the rookie mistake reviewers catch first.

DCF range

Flex two assumptions in a two-way data table:

  • WACC ± 100 basis points around the base case — see our WACC calculation guide in Excel for the cost of equity, cost of debt, and capital structure mechanics that produce the base case.
  • Terminal growth rate ± 50 basis points (or terminal multiple ± 1.0x).

Take the 25th and 75th percentile of the resulting grid, not the absolute min and max. The corner cells of a sensitivity table (low WACC + high growth, or vice versa) are extreme and not credible.

Trading and precedent transactions

Build a peer set, calculate each peer's multiple (EV/EBITDA, EV/Revenue, P/E), then:

  • Low: 25th percentile multiple × target's metric.
  • High: 75th percentile multiple × target's metric.

Using min/max widens the bar artificially because outlier peers dominate. The interquartile range is the standard.

LBO range

The LBO sets a financial sponsor floor — the highest price a buyer could pay and still hit a target IRR. Solve for the entry equity value at:

  • Low: 25% sponsor IRR over a 5-year hold (premium price).
  • High: 20% sponsor IRR over a 5-year hold (more aggressive price).

Counterintuitively, the higher IRR requirement produces the lower valuation, because a sponsor demanding more return will pay less for the same cash flows.

💡 Pro Tip: Always show the IRR or WACC assumptions in the methodology label itself: "DCF (WACC 8.5%–10.5%)" rather than just "DCF." Reviewers will ask. Putting it in the label saves you ten footnotes.

52-week range and analyst targets

These are direct data pulls — no modeling required.

  • 52-week: trailing 52-week intraday high and low from your market data vendor.
  • Analyst targets: the min and max price target across all covering sell-side analysts (Bloomberg BEST_TARGET_PRICE, Capital IQ Estimates_Target_Price).

Common Mistakes That Get Caught in Diligence

The football field looks simple, which makes the mistakes embarrassing.

1. Inconsistent metrics across bars

Mixing equity value, enterprise value, and price-per-share in the same chart. Pick one (usually price-per-share for public targets, enterprise value for private) and convert every methodology to that metric using the target's diluted share count and net debt.

2. Stale or inconsistent dates

The 52-week range uses today's date. The trading comps use multiples as of today's close. The precedent transactions use deals from the last 24–36 months. Document the valuation date in a footnote and make sure every input ties to it.

3. Ranges that are too narrow

If every bar is one dollar wide, the chart looks fake. Realistic bars span 10%–25% of the midpoint. If your DCF range is too tight, widen the WACC sensitivity. If your comps range is too tight, your peer set is too small — add more comps or use a wider percentile band.

4. Ranges that are too wide

If a bar spans 60% of the chart, the methodology is not telling you anything. Tighten the sensitivity or drop the methodology entirely.

5. The axis starts at zero

A bar chart of values between $50 and $70 with an axis starting at zero crushes the bars into the right side of the chart. Always manually set the axis minimum to a round number just below the lowest Low.

⚠️ Warning: Conversely, do not start the axis so close to the lowest Low that small differences look enormous. A target trading at $56 with an offer at $58 on an axis from $55 to $60 makes a 3% premium look like a windfall. Be honest with the axis.

6. No source attribution

Every football field needs a footer naming the data sources (Capital IQ, Bloomberg, company filings, firm estimates) and the valuation date. Without it, the chart cannot be defended in a board meeting or a fairness opinion.

How Do You Update a Football Field Chart Without Breaking It?

Football field charts are notoriously fragile. A single broken link in an upstream model or a renamed range and the chart silently misreports.

The right pattern is to decouple the chart from the upstream models with a dedicated summary table:

  1. Each valuation tab (Trading Comps, Precedent Transactions, DCF, LBO) exposes two cells: a Low and High named range.
  2. A single "Football Field Data" sheet pulls those named ranges into the layout shown in Step 1 above.
  3. The chart sources only from the Football Field Data sheet.

When a model changes, the named cells update, the summary table refreshes, and the chart redraws. No chart series re-linking, no broken references.

Audit checklist before sending the deck

  • Every Low is less than its corresponding High.
  • The midpoints are reasonable relative to the current trading price.
  • The 52-week range is current as of the valuation date.
  • WACC, growth, multiple, and IRR assumptions appear in either the labels or a footnote.
  • Reference markers (current price, offer price) tie to the source files cited in the deck.
  • Axis minimum and maximum are round numbers, not auto-scaled.

Automating Football Field Updates with AI

A typical pitch involves rebuilding the football field three to ten times as new comps are added, the DCF is re-flexed, or an updated offer comes in. Each rebuild used to mean an analyst manually copying low and high values, refreshing labels, and re-aligning reference markers.

Modern AI Excel assistants — including VeloraAI — can read the upstream sensitivity tables, identify the 25th/75th percentile of each methodology, write the values into the football field data sheet, and refresh the chart references in seconds. The analyst's role shifts from data plumbing to judgment: deciding which methodologies belong in the deck, whether the LBO floor is too generous, and how to frame the range in the cover narrative.

That is the right division of labor. The mechanical work of pulling low/high values across five sensitivity tables is the kind of task an LLM with a structured Excel interface handles reliably; the question of which methodologies to weight in the cover memo is not.

Frequently Asked Questions

What is the difference between a football field chart and a valuation summary table?

A valuation summary table lists each methodology's range in rows of numbers. A football field chart visualizes the same data as horizontal floating bars on a single axis. The chart makes convergence and outliers immediately visible, while the table preserves precision. Most pitch decks include both — the table on one slide for detail, the football field on the facing slide for synthesis.

How many methodologies should I include?

Three to seven. Fewer than three and the triangulation argument falls apart. More than seven and the chart becomes hard to read, with bars so thin that the reader cannot distinguish them. For most public-company sell-sides, five is the sweet spot: 52-week range, analyst targets, trading comps, precedent transactions, and DCF.

Should I show price per share or enterprise value?

Use price per share when the target is public, the buyer is paying for shares, and the board is voting on a per-share price. Use enterprise value when the target is private, the deal is structured as an asset purchase, or the audience is comparing the company against EV-denominated peer multiples. Never mix the two in the same chart.

How do I add a current price line in Excel?

Add a scatter series with two points at (current_price, 0) and (current_price, n) where n is the number of methodologies. Plot the scatter on the secondary axis, connect the two points with a thin dashed line, hide the markers, and label the top point with the price. The result is a vertical reference line spanning the chart without overlapping the bars.

Why is the LBO range usually lower than the other methodologies?

The LBO range represents a floor — the maximum price a financial sponsor would pay while still earning a 20%–25% IRR. Strategic buyers can pay more because they capture synergies, and intrinsic methodologies like DCF assume no IRR hurdle. If the LBO bar is higher than the DCF, either the LBO assumptions are too generous or the DCF is too conservative — both worth re-checking before the deck goes out.

Closing

A great football field chart looks effortless on the page but represents the entire valuation workstream behind it. Master the no-fill stacked-bar trick, defend every range with the right sensitivity, and frame the deal price with reference markers, and you have the single most-discussed slide in any M&A pitch handled.

Next step: open your current sell-side or fairness opinion model, build the Football Field Data sheet using named ranges from each methodology tab, and chart it once. From that point on, every model update flows through automatically — and you spend your time on the cover narrative, not the chart formatting.