How a near coin flip resolves: average implied probability by checkpoint, split by outcome
Answered against 22 years of US equities and 12 years of US options data and published with the query that produced it. This result is stored as of 2026-08-03, from Event Contract Prices as Probabilities.
| checkpoint | eventual_yes_pct | eventual_no_pct | contract_days |
|---|---|---|---|
| 30 days out | 52.6 | 47.8 | 5650 |
| 21 days out | 61.3 | 41.9 | 3871 |
| 14 days out | 66.3 | 36.8 | 3666 |
| 7 days out | 73.3 | 29.2 | 2177 |
| 3 days out | 76.8 | 27.2 | 1779 |
| 1 day out | 79.8 | 14.4 | 785 |
- Rows × columns
- 6 × 4
- Computed
- Completeness
- No missing values
- Source
- US exchange, SIP and OPRA market data
- Licence
- Strasmore terms · free, no signup
What each column holds
| Column | Type | Range | Notes |
|---|---|---|---|
checkpoint |
text | 6 distinct values (1 day out, 14 days out, 21 days out…) | |
eventual_yes_pct |
number | 52.6 to 79.8 | percent |
eventual_no_pct |
number | 14.4 to 47.8 | percent |
contract_days |
number | 785 to 5,650 |
Computed from Strasmore's warehouse of US exchange, SIP and OPRA market data. Equity prices are delayed; options greeks and implied volatility are end-of-day. This result is stored, not recomputed on load — it is exactly the numbers that were returned on , and the query below is what returned them.
the exact SQL behind every number
WITH px AS (
SELECT toDate(toTimeZone(window_start, 'America/New_York')) AS session,
argMax(toFloat64(close), window_start) AS close_px
FROM global_markets.delayed_stocks_minute_aggs
WHERE ticker = 'SPY'
AND toDate(toTimeZone(window_start, 'America/New_York')) >= toDate('2025-06-01')
AND toDate(toTimeZone(window_start, 'America/New_York')) <= toDate('2026-06-30')
AND (toHour(toTimeZone(window_start, 'America/New_York')) * 60
+ toMinute(toTimeZone(window_start, 'America/New_York'))) BETWEEN 570 AND 959
GROUP BY session
),
coin_flips AS (
SELECT ticker AS contract
FROM global_markets.options_greeks
WHERE underlying_symbol = 'SPY'
AND date >= toDate('2025-06-01')
AND expiration_date <= toDate('2026-06-30')
AND days_to_expiry BETWEEN 28 AND 32
AND iv_converged = 1
AND volume > 0
AND delta > 0
GROUP BY contract
HAVING avg(delta) BETWEEN 0.35 AND 0.65
),
obs AS (
SELECT g.days_to_expiry AS dte,
g.delta AS implied_prob,
if(px.close_px > toFloat64(g.strike_price), 1, 0) AS finished_above
FROM global_markets.options_greeks AS g
INNER JOIN coin_flips AS c ON g.ticker = c.contract
INNER JOIN px ON px.session = g.expiration_date
WHERE g.underlying_symbol = 'SPY'
AND g.date >= toDate('2025-06-01')
AND g.expiration_date <= toDate('2026-06-30')
AND g.iv_converged = 1
AND g.volume > 0
AND g.delta > 0
AND (g.days_to_expiry BETWEEN 28 AND 32
OR g.days_to_expiry BETWEEN 19 AND 23
OR g.days_to_expiry BETWEEN 12 AND 16
OR g.days_to_expiry BETWEEN 6 AND 8
OR g.days_to_expiry BETWEEN 3 AND 4
OR g.days_to_expiry <= 1)
)
SELECT multiIf(dte >= 28, '30 days out',
dte >= 19, '21 days out',
dte >= 12, '14 days out',
dte >= 6, '7 days out',
dte >= 3, '3 days out',
'1 day out') AS checkpoint,
round(100 * avgIf(implied_prob, finished_above = 1), 1) AS eventual_yes_pct,
round(100 * avgIf(implied_prob, finished_above = 0), 1) AS eventual_no_pct,
count() AS contract_days
FROM obs
GROUP BY checkpoint
HAVING countIf(finished_above = 1) > 0 AND countIf(finished_above = 0) > 0
ORDER BY avg(dte) DESC
Run your own version of this
The same 22 years of US equities and 12 years of options data are queryable in SQL or plain English. A free account runs 100 queries a day and takes no card.
More from this analysisEvent Contract Prices as Probabilities
Implied probability vs what happened: SPY calls 30 days from expiry, 2022 through June 2026
ranking 10×4
→
Contracts priced near a coin flip: implied vs realized outcome by name, 2023 through June 2026
ranking 6×4
→
Yes and No probabilities across one SPY chain: call side, put side, and the pair total
table 8×5
→
Implied probability by quote format, illustrative quotes
ranking 5×2
→
De-vig methods on one lopsided market, -750 against +475
ranking 4×3
→
Book sum and overround on four illustrative markets
ranking 4×3
→
See all 2,170 queries →