What Does Both Halves Under 1.5 Mean in Betting?
Both halves under 1.5 is a soccer market that wins only if each half, taken separately, contains at most one goal. A 1-1 draw with one goal in each half wins; a 2-0 with both goals before halftime loses. Pricing it means estimating goal rates for each half and accounting for how the halves are linked.
How the market settles
The market splits the match at halftime and applies an under 1.5 goals line to each half separately. Selecting yes wins only if the first half has zero or one goal and the second half also has zero or one goal. Most bookmakers offer it as a yes or no market.
That means the full-time score alone does not settle it. Winning full-time scores are limited to 0-0, 1-0, 0-1, 1-1, 2-0 and 0-2, and the two-goal results win only if one goal came in each half. A 2-0 with both goals before the break loses, as does any match with three or more goals.
Bookmakers' rules generally treat the second half as ending at the final whistle of normal time, including stoppage time, with extra time and penalty shootouts excluded. Wording varies, so read the market rules of the book in question.
How it relates to other totals markets
Full-match under 2.5. Every winning both halves under 1.5 result also wins under 2.5, but not the reverse: a 2-0 with both goals in one half wins under 2.5 and loses this market. So both halves under 1.5 is always less likely than full-match under 2.5 in the same match.
Full-match under 1.5. Under 1.5 for the match requires one goal or none in total. Every such result also wins both halves under 1.5, so the full-match under 1.5 is the less likely of the two.
First half and second half under 1.5. Each half line on its own is a separate market. Both halves under 1.5 is the joint event, which is where the modelling question sits.
Pricing it with a Poisson model (illustrative)
Start with an expected goals total for the match, from a team-strength model or derived from match odds. Suppose, for illustration, the total is 2.6 goals. Scoring is generally observed to rise as matches go on, so assume an illustrative 45 to 55 split between halves: 1.17 goals expected in the first half and 1.43 in the second. Use your own league's split rather than this one.
Under a Poisson model, the probability of at most one goal in a half with rate L is e^(-L) times (1 + L). That gives about 0.674 for the first half and 0.582 for the second. If the halves are treated as independent, the joint probability is their product, about 0.392, which is fair decimal odds of about 2.55 before any margin.
For comparison, full-match under 2.5 in the same model is about 0.518. The gap, about 0.127, is exactly the chance that the match ends with two goals both scored in the same half.
Sensitivity
The total matters far more than the split. Keeping the 45 to 55 split, an illustrative total of 2.2 raises the probability to about 0.487, and 3.0 lowers it to about 0.310. Moving to an even 50 to 50 split at a total of 2.6 changes it only from 0.392 to 0.393. Under independence, an even split always gives the highest probability for a fixed total, because the log of each half's probability is concave in its rate.
Why the halves are not independent
The independent model is a starting point, not the answer. Heuer and Rubner found the Poisson description fits the Bundesliga quite well overall but with significant deviations linked to the current score and the time since the previous goal. Two mechanisms matter for this market.
Score effects. A first-half goal changes the second half. A trailing side commits more players forward, a leading side may sit deeper, and either can change the second-half rate in ways a fixed split cannot capture.
Uncertainty about the match rate. Your 2.6 is an estimate. If the true rate on the day is higher, both halves tend to be busier together; if lower, both tend to be quieter. Averaging over that uncertainty creates positive dependence between halves, so a model that plugs in a single rate and multiplies tends to understate the chance that both halves stay quiet together, relative to a model with the same marginal half probabilities.
Simulation handles both: draw the match rate from a distribution, simulate the first half, adjust the second-half rate by score state, and count how often both halves end with one goal or fewer.
Comparing a model price with the market
Convert the yes and no prices to implied probabilities and remove the bookmaker's margin before comparing them with a model figure. Then compare against equivalent combinations of other markets, such as the two half under 1.5 lines and the correct score grid, to see whether the joint market is priced consistently with its parts. Check results over many matches with a proper scoring rule rather than a short run of outcomes.
This page describes how the market is defined and modelled. It is not betting advice. If gambling stops being fun, take a break and use the support tools your operator or local regulator provides.
Frequently asked questions
- Does a 1-1 draw win both halves under 1.5?
- Only if the two goals came in different halves. A 1-1 with a 1-0 halftime score wins, because each half had exactly one goal. A 1-1 with both goals in the second half loses, because that half had two goals. The full-time score never settles this market on its own.
- Does extra time count in both halves under 1.5?
- Generally no. Bookmakers usually settle half markets on normal time, with the second half including stoppage time and ending at the final whistle of 90 minutes, and exclude extra time and penalty shootouts. Rules differ between operators and competitions, so check the specific market rules before relying on this, particularly for knockout matches that can go to extra time.
- Is both halves under 1.5 the same as under 2.5 goals?
- No. Every result that wins both halves under 1.5 also wins under 2.5, but a two-goal match with both goals in one half wins under 2.5 and loses both halves under 1.5. In an illustrative Poisson model with 2.6 expected goals, under 2.5 is about 0.518 while both halves under 1.5 is about 0.392.
- How do you calculate fair odds for both halves under 1.5?
- Estimate the expected goals for each half, compute each half's probability of zero or one goal, and combine them. Under a Poisson model with independent halves, the joint probability is the product of e^(-L)(1 + L) for each half's rate L. Fair decimal odds are one divided by that probability, before adjusting for correlation between halves and bookmaker margin.