Author: Alessandro Radice · M.Sc. Economics and Business Law (Finance), Università Cattolica del Sacro Cuore, Milan
PIF, Silver Lake and Affinity Partners took Electronic Arts private at $210 per share, about $55 billion. Could a buyout fund have paid that price? A private equity case study on the largest leveraged buyout in history, closed on 4 August 2026. It rebuilds the deal from EA's FY2026 results and the actual $18 billion debt package: sources and uses, six debt tranches, a five-year operating plan with cost savings, a debt schedule with cash sweep, sponsor returns in three scenarios and the maximum price a fund could pay at a 20% IRR. It comes with a Colab notebook, an Excel model with live formulas and a scenario switch, an investment memo and a presentation deck.
Every buyout starts from the same question: at this price, with this debt, does the equity earn the fund's hurdle? EA is an unusual test case, a $55bn take-private led by a sovereign wealth fund that already owned about 10% of the company.
This project has three goals:
- Model a real LBO end to end. The closing debt package tranche by tranche, a bookings-based operating model, mandatory amortisation and a cash sweep, exit and returns.
- Measure the ability to pay. The highest price per share a sponsor could pay at a 20% IRR, and the exit multiple it would need at $210.
- Deliver it in deal-team format. An auditable Excel model with a scenario switch, reconciled with the Python engine, plus a memo and a deck.
| Downside | Base | Upside | |
|---|---|---|---|
| Net bookings growth / cost savings / exit multiple | 2% / $200m / 14× | 5% / $400m / 16× | 8% / $700m / 19× |
| FY2031 adj. EBITDA | $3.11bn | $3.76bn | $4.57bn |
| Net debt / EBITDA, close → FY2031 | 6.4× → 3.9× | 6.4× → 2.7× | 6.4× → 1.8× |
| Sponsor IRR / MoM at $210 | –1.9% / 0.91× | 7.5% / 1.43× | 17.7% / 2.26× |
| Maximum price at a 20% IRR | $122 | $151 | $197 |
| Exit multiple needed for 20% at $210 | 31.7× | 25.8× | 20.7× |
- Entry: $54.8bn of uses and an entry enterprise value of $51.2bn, 19.4× FY2026 adjusted EBITDA, funded with $34.8bn of equity (63.5%), $18.0bn of new debt (6.8×) and $2.0bn of EA's cash.
- Credit: the business carries the debt comfortably: the Base case repays $6.7bn and cover rises from 2.4× to 4.0×.
- Conclusion: no scenario reaches a 20% IRR at $210. In the Base case a 20%-IRR buyer could pay $151, below the $168 unaffected price. The price fits a long-term owner with a lower cost of capital, and PIF funds most of the equity.
| Step | Module | What it produces |
|---|---|---|
| 1 | Data | FY2025–FY2026 financials from the earnings release and 10-K, share count, deal terms, closing debt package |
| 2 | Sources & uses | Equity purchase, refinancing of the old notes, fees and OID vs new debt, balance-sheet cash and sponsor equity |
| 3 | Operating model | Net bookings, adjusted EBITDA with cost savings, cash compensation replacing stock awards, capex, cash taxes |
| 4 | Debt schedule | TLA, USD and EUR term loan B, USD and EUR secured notes, unsecured notes: interest, amortisation, cash sweep |
| 5 | Returns | Exit value, sponsor IRR and MoM by scenario |
| 6 | Ability to pay | Maximum price per share at the target IRR; exit multiple needed at the offer price |
| 7 | Sensitivity | IRR by entry price and exit multiple |
| 8 | Exports | Excel model with live formulas and a scenario switch, and a chart |
Cover · Inputs · Sources & Uses · Operating Model · Debt Schedule · Returns · Sensitivity
- Scenario switch: one cell on
Inputs(1 = Downside, 2 = Base, 3 = Upside) drives the whole model. - Banker colour code: blue = hard-coded input, black = formula, green = link to another sheet.
- 353 formulas, a sources = uses check, and every output reconciled with the Python engine in all three scenarios.
- Adjusted EBITDA on a net bookings basis: operating income + change in deferred net revenue + D&A + stock-based compensation ($2,636m in FY2026). $18.0bn / $2,636m = 6.8×, the gross leverage reported for the financing.
- Operating case: bookings growth by scenario, a constant 32.8% margin on bookings plus cost savings (half in FY2027), 50% of former stock-based pay moved to cash, capex and D&A at FY2026 ratios, cash taxes at 21%.
- Debt: interest on opening balances, so there is no circularity. Mandatory amortisation first (5% TLA, 1% term loan B), then 100% of cash above a $1.0bn minimum sweeps the TLA and the term loan Bs; the notes are bullets.
- Returns: five full fiscal years (FY2027–FY2031) after the August 2026 close, exit at an EV/EBITDA multiple, sponsor equity treated as one cheque including PIF's rollover at $210.
- Ability to pay: because the debt package is fixed at $18bn, the entry price changes only the equity cheque, so the maximum price and the sensitivity grid are exact closed-form results.
- The TLA spread and amortisation, SOFR (3.75%), Euribor (2.25%), fees, minimum cash and the share of stock-based pay moved to cash are assumptions.
- Annual model over five full fiscal years; measured from the August 2026 close (about 4.7 years), the Base IRR would be about 8% instead of 7.5%. Euro tranches are held at the exchange rate implied at signing.
- Taxes ignore the US limit on interest deductibility, which is material here: FY2027 interest exceeds 30% of tax EBITDA.
- Only half of former stock-based pay is charged as a cash cost; the other half is neither a cash cost nor dilution at exit, which flatters returns.
- No dividend recap, IPO or strategic exit is modelled, and the strategic value to PIF is outside the model.
This project is for educational purposes and is not investment advice.
| Requirement | Details |
|---|---|
| Environment | A Google account to run the notebook in Google Colab, free tier is enough. It also runs in any local Jupyter with Python 3.10+. |
| Python libraries | pandas, numpy, matplotlib, xlsxwriter. The first cell installs what is missing. |
| To open the outputs | Microsoft Excel or Google Sheets; any PDF reader. |
| Background knowledge | LBO mechanics, debt tranches and cash sweeps, IRR and MoM. |
- Open
EA_LBO_Analysis.ipynbin Google Colab. - Change the assumptions in the Configuration and Data cells if you want: scenario drivers, base rates, fees, target IRR.
Runtime → Run all. The Excel model and the chart download automatically.- In Excel, set
Inputs!C5to 1, 2 or 3 to switch scenario, or edit any blue cell.
├── EA_LBO_Analysis.ipynb # the notebook (run this)
├── ea_lbo.py # same code as a plain Python script
├── EA_LBO_Model.xlsx # Excel model with live formulas and a scenario switch
├── EA_LBO_Memo.pdf # investment memo
├── EA_LBO_Deck.pdf # seven-slide presentation
├── returns.png # slide used in this README
├── deleveraging.png # chart used in this README
└── README.md
- Electronic Arts, Q4 and FY2026 earnings release and 10-K, SEC EDGAR (May 2026)
- Electronic Arts closing 8-K, via Stock Titan (August 2026)
- EA bonds land tight of price talk, Octus (March 2026)
- Electronic Arts launches leveraged loan, PitchBook (March 2026)
- Leveraged buyout of Electronic Arts, Wikipedia
- PIF, Silver Lake and Affinity's $55bn acquisition of EA, MergerSight
Python · pandas · numpy · matplotlib · xlsxwriter · Google Colab · Excel