BTTS by Elo Rating Gap: Both Teams to Score in Mismatches
A huge Elo mismatch cuts the both-teams-to-score rate far less than most bettors assume. What changes is who scores, and how often the underdog gets shut out.
- 53.2%BTTS when teams are within 50 Elo points
- 49.0%BTTS with an Elo gap of 300+
- −4.2 pointsChange from closest to widest gap
- 44.9%Gap 300+: only the stronger side scored
Every weekend I see the same assumption: a strong side against a weak one means BTTS no. It feels obvious. The favourite dominates, the underdog barely crosses halfway, and a clean sheet follows. I wanted to test that against a big sample of 67,047 matches across 21 European divisions from 2016/17–2025/26, measuring the mismatch with each side's pre-match Elo rating.
The answer is less dramatic than the folklore. When teams sit within 50 Elo points, both scored 53.2% of the time. With a gap of 300 or more, it was still 49.0%, a drop of just −4.2 points. Mismatches change the shape of the scoreline far more than the BTTS line itself, and that distinction drives how I build my free both teams to score picks page.
Q1Does a bigger Elo gap actually kill BTTS?
This chart covers 51,967 matches with Elo ratings, grouped by the size of the gap. The striking thing is how flat the first half of it is. At 50-99 points BTTS was 53.3%, essentially the same as the closest band, and at 100-149 it was still 52.8%.
Only past 150 points does it start to wobble downward, and even then not cleanly. The 200-249 band came in at 52.3%, above the 150-199 band. The real dip only shows at 300+, where 2,816 matches produced 49.0% with a range of ±1.8 points.
View the data: btts by elo rating gap between the teams
| Both teams scored, 51,967 matches with Elo ratings, gap in Elo points | |
|---|---|
| 0-49 | 53.2% |
| 50-99 | 53.3% |
| 100-149 | 52.8% |
| 150-199 | 50.6% |
| 200-249 | 52.3% |
| 250-299 | 50.3% |
| 300+ | 49.0% |
My reading is that a moderate Elo gap tells you almost nothing about BTTS on its own. If you're backing BTTS no simply because one side is rated higher, the numbers don't support you until the mismatch is genuinely extreme.
Q2If BTTS holds steady, who stops scoring in mismatches?
This is where the gap really shows. In the closest matches, only the stronger side scored 20.6% of the time and only the weaker side 17.9%, close to an even split. By 300+, only the stronger side scored 44.9% of the time, while the weaker side scoring alone collapsed to 3.3%.
The other quiet change is goalless draws. They made up 8.3% of matches in the 0-49 band and only 2.9% at 300+. A big favourite rarely fails to score, which removes one of the main routes to BTTS no.
View the data: who scored, by elo gap
| Both | Only stronger | Only weaker | Neither | |
|---|---|---|---|---|
| 0-49 | 53.2% | 20.6% | 17.9% | 8.3% |
| 50-99 | 53.3% | 23.9% | 14.5% | 8.3% |
| 100-149 | 52.8% | 27.4% | 12.4% | 7.3% |
| 150-199 | 50.6% | 33.5% | 9.3% | 6.6% |
| 200-249 | 52.3% | 35.5% | 7.1% | 5.2% |
| 250-299 | 50.3% | 39.6% | 5.8% | 4.3% |
| 300+ | 49.0% | 44.9% | 3.3% | 2.9% |
So the BTTS no outcomes don't grow much; they swap. Close games lose BTTS through 0-0s and single-goal results either way, while mismatches lose it almost entirely through the favourite keeping a clean sheet. That tells me where to focus: the underdog's attack and the favourite's back line, not the gap itself.
Q3What are fair BTTS odds at each Elo gap?
The table turns each frequency into fair odds with no margin. Fair BTTS yes sits at 1.88 in the closest band and drifts only to 2.04 at 300+, while BTTS no moves from 2.14 to 1.96. Across most of the table the two sides hover close to even money.
The last column is the one I'd circle. The weaker side's average shots on target slide steadily from 4.0 at a gap of 0-49 to 2.7 at 300+. Fewer efforts on goal, yet BTTS barely moves, which suggests underdogs in mismatches still convert enough chances, often late or on the break.
| Elo gap | Matches | BTTS | Fair odds yes | Fair odds no | Weaker side SOT |
|---|---|---|---|---|---|
| 0-49 | 17,561 | 53.2% | 1.88 | 2.14 | 4.0 |
| 50-99 | 13,366 | 53.3% | 1.88 | 2.14 | 3.8 |
| 100-149 | 8,513 | 52.8% | 1.89 | 2.12 | 3.7 |
| 150-199 | 4,752 | 50.6% | 1.98 | 2.02 | 3.5 |
| 200-249 | 3,035 | 52.3% | 1.91 | 2.10 | 3.3 |
| 250-299 | 1,924 | 50.3% | 1.99 | 2.01 | 3.2 |
| 300+ | 2,816 | 49.0% | 2.04 | 1.96 | 2.7 |
Bear in mind Elo has no home advantage built in, and ratings cover 77.5% of the sample, so a home side with a small Elo deficit can still be the market favourite. Treat these as a baseline model, not a price list.
Q4Does the Elo gap matter more in lower divisions?
Splitting by tier changes the picture. In top flights BTTS was 53.9% at a gap of 0-49 and still 50.8% at 200+ across 7,270 matches. Lower divisions started at 52.6% and fell to 47.5% at 200+, so big gaps bite harder there.
The sharpest split is at 150-199, where top flights held at 52.5% and lower divisions dropped to 45.3%. The lower-division 200+ group is only 505 matches, so I wouldn't lean on it too hard, but the direction is consistent.
View the data: btts by elo gap: top flights vs lower divisions
| Top flights | Lower divisions | |
|---|---|---|
| 0-49 (8,679 / 8,882 matches) | 53.9% | 52.6% |
| 50-99 (7,038 / 6,328 matches) | 53.8% | 52.6% |
| 100-149 (5,162 / 3,351 matches) | 54.3% | 50.7% |
| 150-199 (3,462 / 1,290 matches) | 52.5% | 45.3% |
| 200+ (7,270 / 505 matches) | 50.8% | 47.5% |
My guess is that elite underdogs keep enough quality to nick a goal, while weaker lower-league sides facing a much stronger opponent simply lack the attacking tools. In the second tier and below, I give the gap more weight.
The playbook
How we would use these numbers before the next BTTS bet.
- Ignore moderate gaps. Below 150 Elo points BTTS stayed between 52.8% and 53.3%, so don't price BTTS no off the rating gap alone. Look at shape, injuries and keeper form instead.
- Study the underdog attack. At 300+, only the weaker side scored just 3.3% of the time while only the stronger side scored 44.9%. The bet comes down to whether the underdog can find one goal, so check its shots on target trend.
- Weight gaps by tier. At 150-199, BTTS was 52.5% in top flights but 45.3% in lower divisions. Give a big Elo gap more respect when backing BTTS no below the top flight.
Data & method
- Data: 21 European divisions, 2016/17–2025/26, 67,047 matches with full match statistics.
- Elo rating gap = absolute difference between the two teams' pre-match Elo ratings; matches without both ratings are excluded.
- BTTS = both teams scored at full time.
- The 'stronger side' is the team with the higher Elo rating, regardless of venue.
- 95% ranges use the normal approximation; fair odds = 1 / observed frequency, no margin.
- Caveat: Elo ratings are available for 77.5% of matches in the sample.
- Caveat: Elo does not include home advantage, so a home side with a small Elo deficit may still be the market favourite.
Quick Q&A
- Is BTTS less likely when a strong team plays a weak team?
- Only slightly. BTTS was 53.2% when teams were within 50 Elo points and 49.0% with a gap of 300 or more, a drop of −4.2 points.
- What are fair odds for BTTS in a big mismatch?
- In this sample, fair BTTS yes odds were 2.04 at a gap of 300+, against 1.88 in the closest band. BTTS no was 1.96 at 300+.
- Do mismatches produce more 0-0 draws?
- No, fewer. Goalless draws were 8.3% of matches in the 0-49 band but only 2.9% at a gap of 300+, because big favourites rarely fail to score.
I'm Beatrix Lund, a betting writer who's narrowed right down to Both Teams To Score markets, where patient research into goal patterns tends to pay off.
More from Beatrix Lund →
