Primeira LigaTip Casa Pia vs Moreirense
Casa Pia and Moreirense face each other in Primeira Liga (Portugal). On this page we bring together recent form, head‑to‑head record, league standings and key absences, finishing with our EV+ statistical model’s pick for the 1X2 and goals markets.
Recent form and league table
Looking at recent form, Casa Pia show 2 win(s), 2 draw(s) and 1 defeat(s) in the last five league games, scoring 8 and conceding 8 goals. Meanwhile, Moreirense record 2 win(s), 0 draw(s) and 3 defeat(s) over the same span, with 4 goals scored and 7 conceded.
No standings available for this league/season.
Head-to-head (H2H)
In the most recent head‑to‑head meetings between Casa Pia and Moreirense, the teams have faced each other 7 time(s), with Casa Pia winning 4 match(es), Moreirense winning 2 and 1 draw(s), for an average of 2.7 goal(s) per game. At least three goals were scored in 4 of those games, which points towards a clear trend for open matches in terms of goals. Both teams scored in 4 of the 7 games analysed, reinforcing the idea of a match‑up where both attacks usually create danger. In the latest meeting, the score was Casa Pia 0-0 Moreirense, played on 01/03/2026 in the Primeira Liga, an extra data point to consider when framing the context of this new clash.
TABLE – Head-to-head
Main match odds
Full time 1X2
Total goals 2.5
Both teams to score
Conclusion – Casa Pia vs Moreirense
Given recent form, key absences and the usually balanced head‑to‑head record between Casa Pia and Moreirense, our EV+ statistical model finds positive expected value in the 1X2 market, highlighting the scenario above as the main betting angle. As an alternative or complement, the goals market suggested by the model offers an extra option for more conservative profiles or for diversifying exposure to this match.
EV reading guideline: values up to around 8 points are not particularly strong; above that level we are already talking about meaningful positive expected value. When EV moves beyond 15 points, it is recommended to further investigate contextual factors that might be inflating the model, such as teams already relegated or with nothing to play for, internal crises, heavy injury lists in key positions, recent coaching changes, schedule congestion, extreme weather or clear differences in competitive motivation.