Spain vs Cape Verde Islands Prediction, Tips & Odds
Spain vs Cape Verde Islands
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About the Teams
Spain
Cape Verde Islands
Head to Head
Last 1 Meetings (evenly matched 0-0)In their only competitive meeting, Spain and Cape Verde Islands played to a 0-0 draw on June 15, 2026, during the World Cup. With just one match in their head-to-head history, the sample size is too small to draw any significant conclusions or identify a pattern. This result does not provide enough context to assess the relative strengths of the teams, especially considering the absence of any previous encounters.
Group H Standings
| # | Team | P | W | D | L | GF | GA | GD | Pts | Form |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Spain | 3 | 2 | 1 | 0 | 5 | 0 | 5 | 7 | WWWWW |
| 2 | Cape Verde Islands | 3 | 0 | 3 | 0 | 2 | 2 | 0 | 3 | LDDD |
| 3 |  Uruguay | 3 | 0 | 2 | 1 | 3 | 4 | -1 | 2 | LDD |
| 4 |  Saudi Arabia | 3 | 0 | 2 | 1 | 1 | 5 | -4 | 2 | DLD |
Key Statistics
2026 SeasonSpain have won 6 of their last 10 matches at home, drawing 4 and losing 0. Their recent home fixtures include beat Belgium 2-1 and beat Austria 3-0.
Overall, the wider run reads 12W 4D 0L from the last 16 games (75% win rate). The form line is positive, with more wins than defeats across the sample.
Cape Verde Islands have won 1 of their last 6 matches on the road, drawing 4 and losing 1. Their recent away fixtures include lost to Chile 4-2 and drew with Egypt 1-1.
Overall, the wider run reads 5W 6D 1L from the last 12 games (42% win rate). The form line is positive, with more wins than defeats across the sample.
Lineups
Lineups not yet announced
National-team lineups are genuinely unknown until 1 to 2 hours before kick-off, when the starting XI is confirmed. Until then, only predicted lineups are possible.
Unavailable Players
0 playersSpain
No reported absences
Cape Verde Islands
No reported absences
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The Daily Punt Analysis Team
Data-driven football predictions and betting tips
This forecast was built by the The Daily Punt Analysis Team using our in-house statistical model. We feed the model two layers of data for every fixture: each team's recent expected goals (xG and xGA) and their actual goals scored and conceded, split by home and away venue. The numbers run through a Poisson distribution that produces a probability for every possible scoreline, which we then convert into fair odds for the 1X2, correct score, BTTS, and over/under markets.
Before publishing, we cross-check our fair odds against the prices the major bookmakers are offering. Where a bookmaker is paying out more than our model says is mathematically fair, we flag that market as a value bet on this page.
