The Kalshi market for "When will the first touchdown be scored in Super Bowl LX?" has 14 time buckets spanning Q1 through overtime. The Q4 buckets are priced at 1c bid / 2c ask on the YES side -- implying a 2% chance per bucket that the first TD of the game comes in the 4th quarter. That's too high. Each individual Q4 window covers just 5 minutes of game time in a scenario that requires 45+ minutes of scoreless-touchdown football first. For makers, buying NO at 98c in these buckets is one of the better risk/reward setups on the Super Bowl board.
The Market
Seattle Seahawks vs. New England Patriots, Super Bowl LX, February 8, 2026. Kickoff 6:30 PM ET.
Bucket | Time Window | Yes Bid | Yes Ask | Volume |
|---|---|---|---|---|
Q1: 15:00-10:01 | First 5 min of game | 26c | 27c | 25,620 |
Q1: 9:59-5:00 | ~5-10 min in | 30c | 31c | 8,972 |
Q1: 4:59-0:00 | ~10-15 min in | 20c | 21c | 9,794 |
Q2: 15:00-10:01 | ~15-20 min in | 9c | 10c | 614 |
Q2: 9:59-5:00 | ~20-25 min in | 4c | 7c | 512 |
Q2: 4:59-0:00 | ~25-30 min in | 3c | 5c | 1,224 |
Q3: 15:00-10:01 | ~30-35 min in | 1c | 2c | 4,316 |
Q3: 9:59-5:00 | ~35-40 min in | 1c | 2c | 858 |
Q3: 4:59-0:00 | ~40-45 min in | 1c | 2c | 460 |
Q4: 15:00-10:01 | ~45-50 min in | 1c | 2c | 1,460 |
Q4: 9:59-5:00 | ~50-55 min in | 1c | 2c | 1,914 |
Q4: 4:59-0:00 | ~55-60 min in | 1c | 2c | 2,686 |
OT | Overtime | 0c | 1c | 15,056 |
No TD | No touchdown scored | 0c | 1c | 13,128 |
The Q1 buckets combine for ~77c of implied probability. Q2 adds another ~16c. That leaves ~7c spread across nine remaining buckets. The Q4 buckets alone account for ~6c of that (3 buckets x 2c ask each).
The trade: Buy NO in the three Q4 buckets at 98c. You're paying 98c to win 100c -- a 2c profit per contract -- and you win as long as the first touchdown doesn't fall in that specific 5-minute window. The math says you should win this bet well over 99% of the time per bucket.
The Methodology
There's no clean "average first TD time" stat tracked by major sports sites, so we're working from multiple angles:
NFL-wide scoring timing data (2002-2020 play-by-play studies)
Super Bowl-specific historical data (59 games)
This specific matchup context (two elite defenses)
The goal: figure out the true probability that the first TD of the game lands in any given 5-minute Q4 window, and see if 2% per bucket is too generous.
The Full Breakdown
What Historical Data Tells Us
NFL Regular Season (general pattern):
Average time to first score in an NFL game: ~8 minutes (per play-by-play analysis of 2002-2012 data)
The vast majority of first TDs come in Q1 or early Q2
Only ~2-3 NFL games per full season have zero touchdowns entirely
Games where the first TD comes in Q4 are extremely rare in the regular season -- well under 1%
Super Bowls Are Different -- But Not In a Way That Helps Q4 YES:
10 out of 59 Super Bowls (~17%) had a completely scoreless first quarter -- but nearly all of those still had a first-half TD
Super Bowl XXXVIII (2004): Scoreless for a record 26 minutes and 55 seconds, but the first TD still came in Q2 (Deion Branch catch with 3:05 left in the half)
Super Bowl LIII (2019): The one true outlier -- first TD came with 7:00 left in Q4. This is the only Super Bowl in 59 games where the first TD came in the fourth quarter
Super Bowl LVIII (2024): Scoreless first quarter, but first TD came in Q2
Super Bowl XLIX (2015): Scoreless first quarter (SEA vs NE), but first TD came in Q2
The critical stat: In 59 Super Bowls, the first TD came in Q4 exactly once. That's a 1.7% base rate for the entire quarter -- split across three 5-minute buckets, that's roughly 0.5-0.6% per bucket.
Probability Estimation Per Q4 Bucket
Let's be rigorous about this.
P(First TD in all of Q4 combined):
Super Bowl base rate: 1/59 = 1.7%
NFL regular season base rate: almost certainly lower (Super Bowls skew more defensive early)
Generous estimate accounting for this matchup's elite defenses: ~2-3%
P(First TD in a specific Q4 5-minute window):
If Q4 overall is ~2-3%, split across three windows: ~0.7-1.0% per bucket
Not evenly distributed either -- SB LIII's TD came in the first window (15:00-10:01), so the later windows are arguably even less likely
What the market implies vs. reality:
Q4 Bucket | Market YES Ask | Implied Prob | True Estimate | NO Edge |
|---|---|---|---|---|
15:00-10:01 | 2c | 2.0% | ~0.8-1.0% | ~1.0c |
9:59-5:00 | 2c | 2.0% | ~0.5-0.7% | ~1.3c |
4:59-0:00 | 2c | 2.0% | ~0.3-0.5% | ~1.5c |
At 98c for NO, you're getting roughly 1-1.5c of edge per contract. That's a 1-1.5% return on a bet that resolves in a single evening. On an annualized basis that's absurd, but more practically: the math favors NO in every Q4 bucket, and it favors it more in the later windows.
The Highlights
1. The Per-Bucket Math Strongly Favors NO
The market is treating each Q4 bucket as a 2% event. But for the first TD to land in, say, the Q4 4:59-0:00 window, you need:
Zero touchdowns in Q1 (15 minutes)
Zero touchdowns in Q2 (15 minutes)
Zero touchdowns in Q3 (15 minutes)
Zero touchdowns in Q4 15:00-10:01 (5 minutes)
Zero touchdowns in Q4 9:59-5:00 (5 minutes)
A touchdown in Q4 4:59-0:00 specifically
That's 55 minutes of touchdown-free football followed by a TD in a specific 5-minute window. In 59 Super Bowls, nothing like this has ever happened. Even SB LIII's legendary defensive battle had its first TD at 7:00 remaining in Q4 (the first Q4 window, not the last). The 2c ask on the latest Q4 bucket is pricing an event that has literally never occurred in Super Bowl history.
2. The Orderbook Depth Is Maker-Friendly
The NO side of Q4 buckets has serious depth:
Q4 15:00-10:01 (NO side):
Thousands of contracts resting at 96-98c
Q4 9:59-5:00 (NO side):
Similar depth, large blocks at 96-98c
Q4 4:59-0:00 (NO side):
Tens of thousands of contracts stacked at 96-99c
This matters for makers. You're not trying to push into a thin book -- there's already deep resting NO liquidity, which means the market broadly agrees these are high-probability NO outcomes. You can join the queue at 98c and expect fills as YES buyers trickle in looking for lottery tickets. The volume numbers (1,460 to 2,686 contracts per Q4 bucket) show there ARE counterparties actively buying YES at these levels -- those are your fills.
3. Even the "Worst Case" Historical Scenario Only Hits One Bucket
Super Bowl LIII is the bear case for NO holders. Let's walk through what happens if we get an identical game:
Score after Q1: 0-0
Score after Q2: 3-0
Score after Q3: 3-3
First touchdown: Sony Michel 2-yard run with 7:00 left in Q4
If you bought NO in all three Q4 buckets:
Q4 15:00-10:01 NO: LOSES (first TD landed here)
Q4 9:59-5:00 NO: WINS (+2c)
Q4 4:59-0:00 NO: WINS (+2c)
Even in the single worst Super Bowl in history for this trade, you go 2-for-3 on the Q4 buckets. Your net P&L across the three: +4c revenue, -98c loss, = -94c. That's the worst case, and it's happened once in 59 games.
In the other 58 Super Bowls, you go 3-for-3 and collect +6c across the three buckets. Expected value per 3-bucket set:
EV = (58/59 * 6c) + (1/59 * -94c)
EV = 5.90c + (-1.59c)
EV = +4.31c per cycle
That's a ~4.3c expected profit on 294c of capital deployed (3 x 98c), or about 1.5% return on a single-game bet using the most conservative historical base rate. And that base rate is inflated by a single outlier game that featured the Patriots.
4. This Matchup Doesn't Change the Q4 Math Much
Yes, this is a game with two elite defenses:
Seahawks: #1 scoring defense (16.4 PPG allowed), elite third-down defense
Patriots: #4 scoring defense, gave up 1 or fewer TDs in each of their last 5 games
O/U: 45.5 -- solid, not a shootout
This matchup context might push the probability of a scoreless first quarter higher than the typical Super Bowl. The Patriots alone have been in 5 of the 10 scoreless-Q1 Super Bowls (XXXVIII, XXXIX, XLIX, LI, LIII). Their last meeting with Seattle (XLIX, 2015) had a scoreless Q1.
But here's the thing: a slow start doesn't mean a Q4 first touchdown. Even in the 10 scoreless-Q1 Super Bowls, 9 out of 10 had their first TD in Q1 or Q2 anyway (just later in Q1 or in Q2). The only exception was SB LIII. A defensive game makes it more likely the first TD drifts into Q2 -- it doesn't meaningfully increase the probability it drifts all the way to Q4.
Both teams also averaged 28+ PPG this season (Seattle 28.4, New England 28.8). These aren't the 2018 Rams or Bears. The offense is there on both sides. Kenneth Walker III scored 4 TDs in Seattle's two playoff games. Drake Maye leads the league in completion percentage and yards per attempt.
The 45.5 O/U implies roughly 6-7 combined TDs. The probability that ALL of them come after the 15:00 mark in Q4 is vanishingly small.
Look at who's on the other side of this trade. The Q4 YES buyers are people paying 2c for a shot at 98c -- a 49:1 lottery ticket. Super Bowl prop markets attract a flood of recreational bettors looking for exactly this kind of long-shot action. The volume in Q4 buckets (1,460-2,686 contracts) confirms there's retail flow buying these at 2c.
As a NO maker, you're the house. You're selling insurance against an event that happens roughly 0.5-1% of the time per bucket, and you're collecting a 2c premium that implies 2%. The edge is structural -- recreational bettors systematically overpay for long shots, and you're on the right side of that dynamic.
Risks
The SB LIII scenario
It happened once. If we get another historically low-scoring defensive battle, one of your three Q4 NO positions loses 98c. As shown above, even this worst case nets -94c across the three-bucket portfolio, and it occurs with ~1.7% probability.
Floor pricing limits your edge per contract
At 2c YES / 98c NO, the per-contract edge is small in absolute terms (1-1.5c). You need volume to make this worthwhile. If Kalshi fees eat significantly into that 2c spread, the trade gets worse, so limit orders are the way to go, but then you have to get fills too.
If you buy NO in all three Q4 buckets, you're NOT making three independent bets. They're highly correlated -- if the game is scoreless through Q3, all three positions are suddenly at risk simultaneously. Size accordingly.
Small sample size
59 Super Bowls. One Q4-first-TD occurrence. The true rate could be anywhere from 0.5% to 5% with reasonable confidence intervals. The edge is real but not enormous.
Liquidity for getting OUT
If you want to exit before settlement (e.g., the game is 0-0 at halftime and you want to cut risk), the orderbook may not be liquid enough to exit at a reasonable price mid-game. Plan to hold through settlement.
Bottom Line
Buying NO in the Q4 first-touchdown buckets at 98c is a solid maker play. The market implies 2% per bucket; history says it's closer to 0.5-1%. You're collecting premium from recreational bettors who love lottery tickets, and even the worst Super Bowl ever played for this trade (SB LIII) only hits one of the three buckets.
The play:
Buy NO in all three Q4 buckets (15Q4, 10Q4, 5Q4) at 98c
Each contract risks 98c to profit 2c
Win rate: ~99%+ per bucket historically
Even in the SB LIII disaster scenario, you go 2-for-3
Expected value: ~+1.5% per cycle on capital deployed
The later Q4 windows are even better. The Q4 4:59-0:00 bucket requires 55 minutes of TD-free football -- something that has never happened in Super Bowl history. At 2c YES, this is the most overpriced of the three.
For makers: Post NO limit orders at 98c in the Q4 buckets and let the lottery ticket buyers come to you. The flow is there (2,000+ contracts of volume per bucket), the math is on your side, and the structural edge against recreational long-shot buyers is real.
Disclaimer: This is analysis for entertainment and educational purposes. Past Super Bowl outcomes don't predict future ones. The per-contract edge is small and the strategy requires volume to be meaningful. Don't oversize on any single prop market.
Sources:
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Nothing here is trading advice — just data, probabilities, and our best read of the markets. Event-market trading involves risk and you should make your own decisions. We may hold positions in the markets we discuss and receive compensation through affiliate links.