Home 2.40-3.00 and Under 2.5 Under 1.70: The 0-0 and 1-1 Rates
Across 11,223 tight, low-priced games, the quietest scorelines turned up slightly more often than the prices implied. Here is where that gap lives and where it fades.
Written by Hunter HaywardCorrect Score & Over/Under 2.5 specialist
- 3.69Fair odds, 0-0/1-1
- 25.5%Expected from the 1X2 and over/under prices
- 27.1%Actual 0-0/1-1 rate
- 11,223Games on the rung (home 2.40-3.00, under below 1.70)
- Market
- Correct Score
- The question
- In games with the home side at 2.40-3.00 and under 2.5 priced below 1.70, how often does it finish 0-0 or 1-1 compared with the price-based expectation?
- Sample
- 22 European league divisions, 2005/06-2025/26; 155,895 matches with 1X2 and over/under 2.5 prices; rung n = 11,223
Some matches look cagey before a ball is kicked. The home side drifts out to 2.40-3.00, the under 2.5 shortens below 1.70, and the market is telling you it expects little between the teams and little in either box. I wanted to know how often those games actually end 0-0 or 1-1, because that pair is the first thing I check before writing up correct score tips on nights like this.
Across 22 European divisions from 2005/06-2025/26, 11,223 games sat on this rung. A 0-0 or 1-1 landed 27.1% of the time against 25.5% expected from the prices, a gap of +1.6 points, and fair odds for the pair come out at 3.69. That is a real tilt but a modest one, and the rest of this guide is about where it holds.
Rung 1Shorter under prices pull the 0-0 and 1-1 rate up
This chart holds the home price at 2.40-3.00 and walks down the under 2.5 ladder, showing what the prices implied against what happened. The climb is steep. The rate runs from 16.3% with the under at 2.20+ (1,544 games) to 30.1% with the under below 1.55 (3,113 games), where the expected figure was 27.3%.
What interests me is the direction of the gap. At the long end the actual rate sits below expectation, and the actual bar only moves ahead as the under shortens. On the rung itself the 95% range around 27.1% is ±0.8 points, so the +1.6 gap is bigger than ordinary sampling noise.
View the data: 0-0 or 1-1 as the under 2.5 price shortens
| Expected from prices | Actual | 95% range | |
|---|---|---|---|
| Under 2.5 under 1.70 (rung) (11,223 games) | 25.5% | 27.1% | ±0.8 |
| Under 2.5 under 1.55 (3,113 games) | 27.3% | 30.1% | ±1.6 |
| Under 2.5 1.55-1.70 (8,110 games) | 24.8% | 25.9% | ±1 |
| Under 2.5 1.70-1.85 (8,412 games) | 22.6% | 22.3% | ±0.9 |
| Under 2.5 1.85-2.00 (5,154 games) | 21.1% | 20.5% | ±1.1 |
| Under 2.5 2.00-2.20 (3,125 games) | 19.8% | 19.0% | ±1.4 |
| Under 2.5 2.20+ (1,544 games) | 17.8% | 16.3% | ±1.8 |
| All priced games (155,895 games) | 20.9% | 20.2% | ±0.2 |
One honest caveat before going further. The expected figures come from a Poisson model with a Dixon-Coles low-score correction, fitted to the margin-free 1X2 and over/under prices. They are not a quoted correct-score price. Across all 155,895 games that model expects 20.9% for the pair against 20.2% actual, so it slightly overrates 0-0 and 1-1 overall. That makes a positive gap here more interesting, not less.
Rung 21-1 leads the scorelines and outruns its price
The table lists the most frequent final scores on the rung. 1-1 is top at 15.7% against 14.4% expected, a gap of +1.3 points and fair odds of 6.37. 0-0 sits close to its price at 11.4% against 11.1%, with fair odds of 8.77.
So most of the pair's lead over the model is carried by the score draw, not the goalless one. At the other end, 0-2 fell furthest short at 5.5% against 6.3%, a gap of −0.8 points. These prices slightly overrate a comfortable away win.
| Score | Expected | Actual | Gap (pts) | 95% range | Fair odds |
|---|---|---|---|---|---|
| 1-1 | 14.4% | 15.7% | +1.3 | ±0.7 | 6.37 |
| 0-0 | 11.1% | 11.4% | +0.3 | ±0.6 | 8.77 |
| 1-0 | 10.5% | 11.4% | +0.9 | ±0.6 | 8.77 |
| 0-1 | 9.9% | 10.3% | +0.4 | ±0.6 | 9.71 |
| 2-1 | 7.8% | 8.3% | +0.5 | ±0.5 | 12.05 |
| 1-2 | 7.5% | 7.3% | −0.2 | ±0.5 | 13.70 |
| 2-0 | 6.9% | 6.5% | −0.4 | ±0.5 | 15.38 |
| 0-2 | 6.3% | 5.5% | −0.8 | ±0.4 | 18.18 |
If you price a correct score yourself, those fair odds are the line I'd compare against. A quoted 1-1 shorter than 6.37 is asking you to pay for frequency this history doesn't show.
Rung 3Goalless draws fade fastest as the under drifts
This stacked chart splits each under band into 0-0, 1-1, other draws and non-draws. With the under below 1.55, 13.4% of games ended 0-0 and 16.7% ended 1-1. With the under at 2.20+, those shares fall to 4.1% and 12.2%.
The 0-0 slice collapses far more sharply than the 1-1 slice, which holds up well right across the ladder. For a correct-score bettor that matters. The 1-1 is the sturdier of the pair, while the 0-0 depends heavily on the under being genuinely short.
View the data: how the draws split as the under price moves
| 0-0 | 1-1 | Other draw | Not a draw | |
|---|---|---|---|---|
| Under 2.5 under 1.70 | 11.4% | 15.7% | 5.5% | 67.4% |
| Under 2.5 under 1.55 | 13.4% | 16.7% | 4.8% | 65.1% |
| Under 2.5 1.55-1.70 | 10.6% | 15.3% | 5.8% | 68.3% |
| Under 2.5 1.70-1.85 | 8.7% | 13.5% | 7.0% | 70.8% |
| Under 2.5 1.85-2.00 | 7.6% | 13.0% | 7.1% | 72.3% |
| Under 2.5 2.00-2.20 | 6.4% | 12.6% | 8.4% | 72.6% |
| Under 2.5 2.20+ | 4.1% | 12.2% | 8.6% | 75.1% |
Rung 4The gap peaks where the home price sits 2.40-3.00
Now I flip the question. This chart holds the under 2.5 below 1.70 and moves the home price instead, showing actual minus expected for the pair. The gap runs from −1.5 points with the home side under 1.80 to +1.6 points on our rung.
The shape makes sense to me. A short home favourite in a low-scoring game tends to grind out a narrow win, so the draw-heavy pair falls short. The excess appears when the market sees the teams as close and the goals as scarce, then eases again as the home side lengthens further.
View the data: 0-0/1-1 gap at each home price
| Actual − expected | |
|---|---|
| Home under 1.80 | −1.5 pts |
| Home 1.80-2.10 | +0.5 pts |
| Home 2.10-2.40 | +1.1 pts |
| Home 2.40-3.00 (rung) | +1.6 pts |
| Home 3.00-3.80 | +0.8 pts |
| Home 3.80+ | −0.5 pts |
Rung 5The pattern holds across tiers and grows by era
Last, I split the rung by tier and by era. Top flights landed 26.5% (4,187 games) and lower divisions 27.4% (7,036 games), so this isn't a quirk of one level of football. By era the rate rose from 25.3% in 2005/06-2011/12 to 27.6% in 2012/13-2018/19 and 28.1% in 2019/20-2025/26.
View the data: 0-0 or 1-1 by tier and era
| Home 2.40-3.00 with under 2.5 under 1.70: actual 0-0/1-1 rate by split (games) | |
|---|---|
| Top flights (4,187) | 26.5% |
| Lower divisions (7,036) | 27.4% |
| 2005/06-2011/12 (3,504) | 25.3% |
| 2012/13-2018/19 (3,813) | 27.6% |
| 2019/20-2025/26 (3,906) | 28.1% |
I'd read that drift cautiously. Each era holds only a few thousand games, and small gaps on samples that size sit close to noise. It is a tendency to keep an eye on, not a betting system.
At this price
- Check the under first
The pair's rate swings from 16.3% to 30.1% on the under 2.5 price alone. Confirm the under is below 1.70 before reading anything into a 2.40-3.00 home price.
- Lean 1-1 over 0-0
1-1 landed 15.7% against 14.4% expected, while 0-0 ran almost exactly to its price at 11.4% against 11.1%. If you back only one scoreline here, the score draw has the stronger record.
- Compare against fair odds
Fair odds for the 0-0/1-1 pair on this rung are 3.69. A combined price shorter than that leaves you none of the historical tilt.
Questions bettors ask
How often does a match finish 0-0 or 1-1 when under 2.5 goals is short?
With the home side at 2.40-3.00 and under 2.5 below 1.70, a 0-0 or 1-1 landed 27.1% of the time across 11,223 matches. With the under below 1.55 that rose to 30.1%.
What are fair odds for 1-1 in a low-scoring, evenly priced match?
On this rung 1-1 finished 15.7% of games, which gives fair odds of 6.37. 0-0 finished 11.4%, which gives fair odds of 8.77.
Is backing 0-0 or 1-1 at these prices profitable?
Not as a system. The pair beat the model by +1.6 points, which is wider than the ±0.8 sampling range. Bookmaker margins and the model's own baseline error (20.9% expected against 20.2% actual overall) can absorb an edge of that size.
I'm Hunter Hayward, a football tipster specialising in Correct Score and Over/Under 2.5 markets, turning years of obsessive match-watching into structured, data-informed predictions.
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