Event Contract Trading Journal: P&L Templates & Metrics

Why a Trading Journal Is the Missing Edge in Event Contract Speculation

Most event contract traders rely on memory to evaluate their decisions. After a winning week, the tendency is to assume the approach is working; after a losing one, to blame variance. Neither reaction is informed by data. A structured trading journal converts anecdotal recollection into measurable performance patterns.

Without a systematic record, you cannot separate genuine edge from statistical noise. A trader who closes 60% of positions profitably over twenty trades may have caught favorable market conditions — or may be consistently pricing delay probability better than the market implies. Only a journal with consistent field definitions and calculated metrics can tell the difference.

Recording every event contract trade — route, cost basis, position size, settlement outcome, realized P&L — creates the data substrate for all analytical steps that follow. For a broader framework on approaching speculative event contract trading, see How to Profit Trading Flight Delay Event Contracts.

The Core Fields Every Event Contract Trade Entry Needs

A minimal viable trade log covers the following eight fields. These columns enable every downstream metric calculation.

1. Route / Asset — the specific route and flight number (e.g., JFK–LHR BA 175). For maritime contracts, record vessel name and port pair.

2. Entry Date & Time — the exact timestamp when you opened the position. This lets you correlate entry timing with available data: ATFM restrictions, weather alerts, aircraft rotation status.

3. Cost Basis per Unit — the price paid per contract unit in USD-cents. This is the acquisition cost of a financial position on an outcome — not a wager amount.

4. Position Size — the number of contract units held. Combined with cost basis per unit, this gives total capital deployed: position size × cost basis per unit.

5. Your Delay Probability Estimate — your assessed probability of the delay outcome at entry, expressed as a percentage. This field is the raw input for EV Accuracy tracking.

6. Contract Threshold — the delay threshold defined in the specific contract (e.g., the 15-minute delay threshold). Essential for cross-contract comparisons.

7. Settlement Outcome — the factual result at settlement: Delayed, Not Delayed, or Cancelled where applicable.

8. Realized P&L — the net result in USDT: (settlement value − cost basis per unit) × position size. Record positive for winning positions, negative for losing ones.

Treat every field as mandatory — missing values degrade the integrity of every downstream metric.

Context Fields That Make Your Journal Actionable

Core fields tell you what happened. Context fields tell you why, enabling slice-and-dice analysis across delay causes.

Weather Flag at Entry (Y/N) — was significant adverse weather present at the origin, destination, or hub when you opened the position? This flag, combined with settlement IATA codes, reveals whether weather-driven positions outperform your baseline.

ATFM Slot Restrictions (Y/N) — were EUROCONTROL Air Traffic Flow Management restrictions in effect on the route at entry? EUROCONTROL publishes ATFM delay data that you can cross-reference against your positions. If ATFM-flagged trades consistently outperform, that data source is generating real edge.

Aircraft Rotation Risk (Y/N) — is the inbound aircraft arriving from a route with a known delay history? Reactionary delay from aircraft rotation is a primary driver of actual delay outcomes. For multi-position scenarios involving cascade dynamics, see Cascade Delay Trading: Multiple Event Contract Positions.

IATA Delay Code at Settlement — the actual IATA delay code reported at settlement (code 11 for airline-controlled delay, code 81 for ATC-related, code 91 for weather). Cross-referencing your pre-entry flags against actual IATA codes reveals which signals are genuinely predictive.

Trade Notes — free-text field for unusual circumstances: crew shortages, equipment swap announcements, gate changes, or other information that influenced the trade.

With 50–100 trades logged, these context fields let you answer questions such as: Do ATFM-flagged positions win more often than non-flagged ones on the same route? For guidance on which data signals to check before opening a position, see Pre-Trade Research: 5 Data Signals Before Buying a Flight Delay Event Contract.

Google Sheets Template: Layout and Formulas

A three-tab Google Sheets structure handles most event contract tracking needs without programming knowledge.

Tab 1 — Trade Log: the row-by-row record with fixed column headers in this order:

Keep column order consistent. Every new trade is a new row. Avoid merging cells or using color-coding as a substitute for structured data — colors do not survive formula references.

Tab 2 — Performance Dashboard: auto-calculated from Tab 1:

Win Rate: =COUNTIF(TradeLog[Outcome],"Delayed")/COUNTA(TradeLog[Outcome])
Average P&L: =AVERAGE(TradeLog[Realized P&L])
EV Accuracy gap: =AVERAGE(TradeLog[My Prob Estimate])-COUNTIF(TradeLog[Outcome],"Delayed")/COUNTA(TradeLog[Outcome])
Max Drawdown: derived from a running cumulative P&L column; find the deepest trough from any prior peak
Sharpe-like Ratio: =AVERAGE(TradeLog[Realized P&L])/STDEV(TradeLog[Realized P&L])

Tab 3 — Asset Roster: a summary table aggregated by route. Use SUMIF for total P&L per route and COUNTIF for trade count per route. This view shows which routes generate positive realized results and which are underperforming.

The same template applies to maritime event contracts (substitute Route with Port Pair) and rail delay contracts (substitute with train service code). Only the asset description changes; the field logic is identical.

Performance Metrics That Tell You Whether You Have an Edge

Five metrics derived from your trade log are sufficient to assess whether your approach is systematically profitable or variance-driven.

Win Rate — the percentage of trades settling in your favor. Win rate must be interpreted relative to your average cost basis. At a cost basis of 0.30 per unit (30% implied probability), a 35% win rate generates positive expected value. At 0.50, you need above 50% to break even.

EV Accuracy — the gap between your average probability estimate at entry and your actual win rate. An EV Accuracy near zero means your calibration is sound. A consistent positive gap means you systematically overestimate delay frequency; a negative gap means you underestimate it.

Sharpe-like Ratio — average realized P&L divided by its standard deviation. This is analogous to the Sharpe ratio used in portfolio management and measures return per unit of P&L volatility. Higher values indicate more consistent performance relative to outcome fluctuation.

Max Drawdown — the largest cumulative loss from a peak P&L value to a subsequent trough, expressed in USDT or as a percentage of deployed capital. BTS On-Time Performance data can help establish baseline delay frequency by route for benchmarking your win rate against historical norms.

ROI by Asset — total realized P&L divided by total cost basis deployed, per route. This metric identifies your best-performing markets and flags underperforming routes for removal from your active roster.

No metric is meaningful from a small sample. Aim for at least 30 closed positions before drawing conclusions from any single figure.

EV Accuracy: The Calibration Metric Most Traders Skip

Win rate is the metric most traders track. EV Accuracy reveals whether your win rate makes sense given the probabilities you estimated at entry.

Consider this example: over 20 trades, your average probability estimate at entry was 62%. Your actual win rate was 45%. The EV Accuracy gap is +17 percentage points — you consistently believed delay was more likely than it turned out to be. At that level of miscalibration, you will underperform even in conditions where a well-calibrated trader would generate positive results.

EV Accuracy gaps have specific diagnostic implications:

Positive gap (overestimating win frequency): your data sources may report higher on-time performance than the actual routing produces, or you are not accounting adequately for favorable weather windows.
Negative gap (underestimating win frequency): you may be entering positions too conservatively, passing on contracts where the implied probability significantly underprices actual delay frequency.

The correction is not to adjust estimates arbitrarily but to identify which routes or contexts drive the gap. Filter your journal by Weather Flag = Y or ATFM Flag = Y and compare EV Accuracy within those subsets.

For foundational EV calculation methodology, see Expected Value (EV) for Event Contract Traders. For identifying where market pricing diverges from historical delay frequency, Finding Mispriced Flight Delay Contracts covers the screening process in detail.

Drawdown Analysis and Sizing Discipline

Max drawdown data from your journal should directly govern your position size rules through three steps.

Step 1 — Define a drawdown threshold. Set a maximum acceptable loss over a rolling 7-day period, expressed as a percentage of deployed capital. A common starting point is −15%.

Step 2 — Automate the alert. In the Performance Dashboard, use conditional formatting to flag the rolling 7-day P&L column when it breaches the threshold. This removes the need for daily manual review.

Step 3 — Apply a sizing reduction rule. When the threshold is breached, reduce position size on new entries by 50% until the running P&L returns to the pre-drawdown peak. This is a temporary brake on capital at risk during losing sequences, not a permanent constraint.

The mathematical principle underlying this approach is covered in Risk of Ruin in Event Contract Speculation: How Much to Risk Per Trade. A trader who ignores drawdown rules exposes their full capital to sequential losses that compound faster than gains recover them.

Sizing optimization based on win rate requires a stable estimate from at least 50–100 journal trades before the inputs are reliable enough to inform decisions. Applying a sizing formula to 10 trades produces recommendations that carry more noise than signal.

The Weekly Review Ritual: From Data to Better Decisions

Maintaining a journal creates no value without a consistent review cadence. A weekly review converts data accumulation into behavioral adjustment.

Per losing trade:

Did my pre-entry ATFM or weather flag match the actual IATA code at settlement?
Was the loss attributable to a factor I had not flagged, or was it a correctly estimated low-probability outcome?
Would I take the same position again with the same pre-entry information?

Across the full week:

Has win rate on key routes shifted by more than 5 percentage points from the prior 30-trade average?
Is the EV Accuracy gap widening or narrowing?

Asset Roster review (monthly): Remove any route with negative cumulative P&L across 30 or more closed positions and replace with alternatives from delay-frequency data. Best Flight Routes to Trade on GADUIN provides a structured framework for identifying routes with persistent delay edges.

Basis risk check: Routes where your position outcome and the underlying delay do not correspond cleanly — due to threshold mismatches or data lag — should be flagged separately. Basis Risk in Event Contract Hedging explains how to identify and quantify this type of discrepancy within your journal data.

A weekly review need not be lengthy — 20 minutes of structured analysis against your Performance Dashboard is sufficient if the dashboard is kept current.

Notion Alternative: A Database View for Event Contract Tracking

Traders who prefer Notion can replicate the Google Sheets structure as a relational database. The core fields translate directly to Notion property types:

Route (Text)
Entry Date (Date)
Cost Basis / Unit (Number)
Position Size (Number)
My Prob Estimate (Number, percentage display)
Contract Threshold (Text: the threshold defined in the specific contract, e.g., 15 min)
Outcome (Select: Delayed / Not Delayed / Cancelled)
Realized P&L (Formula field linked to cost basis and position size)
Weather Flag (Checkbox)
ATFM Flag (Checkbox)
IATA Code (Text)

Rollup for Asset Roster: Create a linked Route database, then rollup Realized P&L by route using Sum aggregation. This produces the route-level P&L view equivalent to the Asset Roster tab in Google Sheets.

Recommended filtered views: “Open Positions,” “Closed — Positive P&L,” “Closed — Negative P&L,” “Last 30 Days.”

Notion’s primary limitation for this use case is formula complexity. Standard deviation and Sharpe-like ratio calculations are difficult to implement in Notion’s formula environment. For those calculations, export the Notion database to CSV monthly and process the metrics in a spreadsheet. The two tools can coexist: use Notion for mobile data entry and quick position review; use Google Sheets for the analytic layer.

Risk Disclosure: Event contracts on Gaduin are financial instruments, not gambling products. All trading involves risk of loss, including loss of the full amount allocated to a position. This article is for educational purposes only and does not constitute investment advice. US persons should consult applicable regulations, including CFTC guidance, before accessing any event contract platform. Past performance data recorded in a personal trading journal does not guarantee future returns.