Forecasts for the Portuguese football league
Matchday 31 · Updated April 30, 2026
Predicted standings
Predicted standings based on 50,000 simulations. Mean points and probabilities for each outcome.
| # | Team | Pts | Predicted pts | Champion | Relegation |
|---|---|---|---|---|---|
| 1 |  POR | 82 | 89.8 | >99%5 | — |
| 2 |  SCP | 72 | 82.6 | <1%4 | — |
| 3 |  SLB | 75 | 81.1 | <1% | — |
| 4 |  BRA | 53 | 60.8 | — | — |
| 5 |  FAM | 51 | 55.6 | — | — |
| 6 |  GIL | 49 | 52.8 | — | — |
| 7 |  VSC | 42 | 45.2 | — | — |
| 8 |  MOR | 39 | 44.1 | — | — |
| 9 |  Alverca | 38 | 40.5 | — | — |
| 10 |  EST | 37 | 39.3 | — | — |
| 11 |  ARO | 35 | 39.0 | — | — |
| 12 |  RIO | 34 | 36.9 | — | — |
| 13 |  NAC | 31 | 35.8 | — | —1 |
| 14 |  STC | 32 | 35.3 | — | — |
| 15 |  CPA | 26 | 30.6 | — | 5%4 |
| 16 |  EAM | 28 | 30.4 | — | <1%3 |
| 17 |  TON | 21 | 24.6 | — | 93%7 |
| 18 |  AVS | 14 | 15.6 | — | 100% |
Luck or merit?
Expected points (xPts) computed from each match's expected goals (xG). The difference to actual points measures finishing efficiency and luck.
PORSLBSCPMORFAMVSCESTARORIOCPABRAGILAlvercaNACEAMSTCAVSTONxG data: FotMob
Title race
Championship probability evolution throughout the season.
Next matchday — Matchday 32
Probabilities for matchday 32 fixtures.
Paths to the title
What each team needs to win the league, based on model simulations.
Doesn't depend on other results
Relegation battle
What each at-risk team needs to avoid relegation.
Season outlook
The remaining fixtures with the biggest impact on the title race and relegation battle. Each result was simulated to measure its effect.
Relegation battle
TondelaCasa PiaRelegation battle
Relegation probability evolution throughout the season.
Schedule difficulty
Average remaining opponent strength based on model parameters.
CPATONPORPosition probabilities
Probability of each team finishing in each league position.
| Team | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Porto | 100 | |||||||||||||||||
Sporting | 82 | 18 | ||||||||||||||||
Benfica | 18 | 82 | ||||||||||||||||
Sp. Braga | 96 | 4 | ||||||||||||||||
Famalicão | 3 | 75 | 22 | |||||||||||||||
Gil Vicente | 21 | 78 | ||||||||||||||||
Vitória | 65 | 31 | 4 | |||||||||||||||
Moreirense | 32 | 52 | 12 | 3 | 1 | |||||||||||||
Alverca | 1 | 8 | 41 | 23 | 18 | 8 | 1 | |||||||||||
Estoril | 1 | 7 | 25 | 24 | 25 | 14 | 3 | |||||||||||
Arouca | 3 | 14 | 28 | 21 | 17 | 12 | 5 | |||||||||||
Rio Ave | 2 | 9 | 13 | 25 | 30 | 17 | 3 | |||||||||||
Nacional | 1 | 7 | 12 | 21 | 25 | 28 | 4 | |||||||||||
Santa Clara | 1 | 6 | 9 | 14 | 25 | 39 | 6 | |||||||||||
Casa Pia | 1 | 3 | 6 | 38 | 46 | 6 | ||||||||||||
Estrela | 1 | 5 | 46 | 47 | 1 | |||||||||||||
Tondela | 1 | 5 | 93 | |||||||||||||||
AVS | 100 |
Team strengths
Attack and defense parameters estimated by the Bayesian model.
SCPPORSLBBRAFAMGILESTSTCVSCNACAlvercaRIOMORAROEAMCPATONAVSAbout this model
We simulated the rest of the season 50,000 times, varying each match result based on team performance, squad value, and home advantage. The probabilities shown reflect how often each outcome occurs across those simulations.