This free Google Sheets earnings season tracker is built for options and stock traders who want a personal historical record of their accuracy on earnings plays — not just a calendar of upcoming reports. Download it, log your trades across one full earnings season, and the dashboard will show you whether your strategy has real edge or is costing you money you haven’t noticed yet.
What’s Included
- Trade Log sheet — Records ticker, report date, trade type (long call, short strangle, stock, etc.), entry price, exit price, and net P&L in one continuous log across all earnings seasons
- EPS & Revenue columns — Side-by-side expected vs actual EPS and revenue, with a beat/miss flag and percentage surprise calculated automatically
- IV Tracker columns — Pre-earnings IV rank on a 0–100 scale and the IV the morning after earnings, with a formula that computes the exact crush percentage for each trade
- Expected Move column — Uses the formula (ATM call price + ATM put price) / stock price to calculate what the options market implied before the announcement; actual move is logged alongside it for direct comparison
- Post-Earnings Price columns — Separate columns for 1-day, 5-day, and 30-day closing prices, with percentage changes calculated automatically from the pre-earnings close
- Dashboard tab — Aggregates win rate by strategy type, average IV crush percentage, average actual vs expected move accuracy, and total P&L segmented by earnings season
- Strategy filter — A dropdown on the Dashboard tab lets you isolate results for directional plays (long calls/puts) versus premium-selling strategies (short strangles, iron condors) separately
How to Use
Step 1: Set Up Your Trade Log
Enter the ticker, report date, and trade type in columns A–C. In column D, record your pre-earnings IV rank from your broker’s options chain (scale 0–100). Column E auto-formats as a beat/miss flag once you enter expected and actual EPS in columns F and G.
Step 2: Record Expected and Actual Fundamentals
Before the announcement, log expected EPS and expected revenue from consensus estimates. After the report, fill in the actual figures. The template calculates the beat/miss percentage automatically — this matters because roughly 72% of S&P 500 companies beat EPS estimates in a typical quarter (FactSet Earnings Insight), which means “beat” alone tells you almost nothing about price direction.
Step 3: Log the Expected Move and IV Crush
In column J, enter the sum of the ATM call and ATM put price from the options chain before earnings. The formula in column K divides this by the stock price to give the implied move percentage. The morning after earnings, enter the new IV in column L — the template calculates crush percentage as (pre-IV minus post-IV) / pre-IV. On a stock trading at 120 IV into earnings that falls to 50 IV after, that’s a 58% crush — enough to turn a winning directional call into a near-breakeven trade.
Step 4: Fill in Post-Earnings Price Changes
Record the closing price 1 day, 5 days, and 30 days after earnings in columns N through P. Columns Q–S calculate percentage moves from the pre-earnings close automatically. The average post-earnings 1-day move for S&P 500 stocks is approximately 4–5% in absolute value — use your actual column Q data to see whether the names you trade move more or less than that benchmark.
Step 5: Review the Dashboard Tab
After 10 or more trades, open the Dashboard tab. It shows win rate by strategy type, your average actual-vs-expected move accuracy, and net P&L by season. Filter by strategy using the dropdown in cell B2. Most traders find that their directional and premium-selling strategies have meaningfully different win rates — the dashboard makes that split visible without manual sorting.
Key Benefits
- Exposes IV crush — Shows exactly how much post-earnings volatility collapse reduced your options P&L on each trade, not just in aggregate
- Measures expected-move accuracy — Over 20+ trades, compares what the options market implied against what actually happened, broken out by sector or ticker group
- Season-over-season tracking — Accumulates results across all four earnings seasons to surface patterns that a single season’s data would obscure
- Strategy segmentation — Separates win rates for directional plays versus premium-selling strategies, which often diverge sharply on the same underlying stocks
Template vs JournalPlus App
| Feature | This Template | JournalPlus App |
|---|---|---|
| Trade Entry | Manual entry per position | Auto-import from 50+ brokers |
| IV Crush Tracking | Manual IV entry, formula calculates crush % | Automatic with real-time options data |
| Expected Move Calculation | Manual formula using ATM call + put prices | Calculated automatically per position |
| Post-Earnings Price Tracking | Manual entry at 1, 5, and 30 days | Pulled automatically from market data |
| Dashboard Analytics | Pre-built charts, limited to template columns | 30+ metrics with custom filters |
| Customization | Full — modify any column or formula | Fixed schema, broader data coverage |
| Price | Free | $159 one-time |
This template is a complete, functional solution for traders who want to understand their earnings history. When you’re trading earnings regularly across multiple seasons and want automatic data population and deeper analytics, JournalPlus picks up where the spreadsheet leaves off.
Download
Download the free Earnings Season Tracker and start building your personal earnings history today. No account required — make a copy in Google Sheets and begin logging with your next earnings play.
Frequently Asked Questions
What should I track during earnings season as an options trader?
Beyond win/loss, track pre-earnings IV rank, the IV the morning after (to calculate crush percentage), the options market’s implied move, and the actual 1-day price change. These four data points reveal whether your edge comes from direction, volatility forecasting, or both — and which one is costing you money.
How do I calculate expected move from options prices?
Add the at-the-money call price and the at-the-money put price for the nearest expiration after earnings, then divide by the stock price. For example, on a $200 stock with a $5 ATM call and $4.50 ATM put, the expected move is ($5 + $4.50) / $200 = 4.75%. The straddle break-even rule applies here: the stock must move more than the combined option cost to generate a profit on a long straddle. The template’s column K includes this formula pre-built.
How much does IV typically drop after earnings?
Implied volatility typically drops 30–60% the morning after an earnings announcement. A stock trading at 120 IV into earnings will often fall to 40–60 IV after the report — regardless of whether the result was a beat or miss. This IV crush is the central mechanic that the tracker makes visible. Consider the NVDA example: stock at $850, ATM call at $28 with an IV rank of 88. NVDA beats EPS by 12% and gaps up $35. IV crushes from 88 to 32, and the call — $35 in the money — is worth only $31. Net gain: $3 on a $28 investment (10.7%). The tracker would show this as expected move $28, actual move $35, IV crush 64%, P&L $300 on 1 contract. After 15 similar trades, the dashboard reveals the average crush ate 60% of directional gains — a clear signal to shift toward selling premium instead of buying it.
Is beating EPS estimates a reliable signal for which way a stock moves?
Not reliably. Roughly 72% of S&P 500 companies beat EPS estimates in a typical quarter (FactSet Earnings Insight), yet stocks frequently drop on beats or rally on misses. The price reaction depends on the gap between actual results and what the market had already priced in. The tracker captures this by logging the beat percentage alongside the 1-day price reaction — over 20+ trades on the same sector, you’ll see whether beats in that group consistently produce positive or muted reactions.
How many earnings trades do I need to log before the data is useful?
Patterns typically become meaningful around 20–30 trades in the same strategy category. With fewer than 15 trades, a single outsized win or loss can distort the win rate significantly. The dashboard flags sample sizes below 15 to help you avoid drawing conclusions from thin data. If your accuracy on a specific strategy reaches 55% or above over 40 trades, that represents a measurable edge worth sizing into; if it sits at 48% or below, the data is telling you to stop trading that setup on those names.
