MathPredictions

Brazil Serie A2 Women

CA Piauiense (W) vs Perolas Negras (W) Prediction

Kickoff (UTC):

Predicted score 2-0
Expected goals2.39 – 0.82
Avg goals3.20
Our pickHome
CA Piauiense (W) 71% Draw 18% Perolas Negras (W) 10%

Markets

MarketLineOur pickProbabilityFair oddsOdds
Match result (1X2) Home 71% 1.40 1.29
Double chance Home or draw 90% 1.11 1.02
Goals 2.5 Over 62% 1.61 1.78
Both teams to score Yes 51% 1.95
Corners 9.5 Over 60% 1.68
Correct score 2-0 12% 8.63 41.00

Bookmaker odds

Match result (1X2) Home 1.29  ·  Draw 5.00  ·  Away 8.00
Goals 2.75 Over 1.78  ·  Under 2.03

Latest pre-match prices from the odds feed, refreshed hourly until 30 minutes before kickoff.

Corner forecast

7.6 CA Piauiense (W)
10.4 Expected corners
2.8 Perolas Negras (W)
Corner line 9.50
Over 60% Under 40%

Match trends

CA Piauiense (W) — last 10 matches

DateH/AOpponentScoreCorners
2026-07-26 A L Paysandu (W) 1–2 11–2
2026-06-01 A L Itabirito (W) 1–2 5–2
2026-05-29 H D Santos (W) 1–1 6–4
2026-05-14 A D Uniao RN (W) 0–0 4–5
2026-05-03 A L 3B Sport AM (W) 0–1 8–5
2026-04-28 H W Rio Negro RR (W) 8–1 12–2
2026-04-20 A W Doce Mel EC (W) 2–0 7–1
2026-04-05 A W Ceara (W) 1–0 3–0
2026-03-30 H W Acao (W) 5–2 5–1
2025-10-08 H L Bahia (W) 1–2 5–6

Perolas Negras (W) — last 10 matches

DateH/AOpponentScoreCorners
2026-07-26 A D Acao (W) 0–0 2–9
2026-05-31 H D Itacoatiara (W) 2–2 11–1
2026-05-23 A D Rio Negro RR (W) 1–1 1–5
2026-05-20 H L Minas ICESP DF (W) 1–2 5–3
2026-05-17 A L Doce Mel EC (W) 1–2 2–0
2026-05-11 H D UDA AL (W) 1–1 7–6
2026-05-08 H D Liga Sao Joao (W) 1–1 4–3
2026-05-05 A D Sport Recife (W) 1–1 1–8
2026-04-26 H W Taubate (W) 2–1 8–4
2026-04-19 A W Ceara (W) 3–1 5–6

Match questions

Who is predicted to win CA Piauiense (W) vs Perolas Negras (W)?
Our model gives CA Piauiense (W) a 71% chance, the draw 18% and Perolas Negras (W) 10%. The most likely score is 2-0.
How many corners are expected in CA Piauiense (W) vs Perolas Negras (W)?
The corner model projects 10.4 total corners. Over 9.50 corners is rated at 60% probability.
How are these predictions calculated?
Predictions come from a statistical model fitted on multi-season match results: team attack/defense ratings with time decay, blended with current market lines. No human tipsters are involved, and every published prediction is settled and counted in our public accuracy record.