La Liga: Predictions, Odds & Tips

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Model-based predictions for La Liga — Real Madrid, Barcelona, Atlético and the rest of the Spanish top flight, analysed by the same match model that powers PlaymakerAI. Ahead of every round the model computes 1X2 probabilities, a full score matrix, expected goals and over/under lines, built from hundreds of data points per team: strength, form, playing style, squad and weather.

The predictions are held against live odds from multiple bookmakers, with positive expected value (EV+) flagged where the model’s probability beats the implied odds. Played matches are graded openly — hit or miss — and everything updates continuously until kickoff.

Upcoming matches

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League table2025/26

New season with no matches played yet — the table shows the most recently completed season until the rounds get going.

Pos	Team	S	W–D–L	GF–GA	P	xP	xG	xGA	xGD	FT	Style
1	FC Barcelona	38	31–1–6	95–36	94	56,5	73,7	40,7	+33,0	78 %	Possession & high press
2	Real Madrid	38	27–5–6	77–35	86	60,0	69,9	42,9	+27,0	66 %	Possession & high press
3	Villarreal	38	22–6–10	72–46	72	56,7	51,3	49,0	+2,3	40 %	Balanced & physical
4	Atlético de Madrid	38	21–6–11	62–44	69	51,8	56,2	48,6	+7,6	54 %	Balanced & physical
5	Real Betis	38	15–15–8	59–48	60	54,6	50,5	48,3	+2,2	54 %	Balanced & physical
6	Celta Vigo	38	14–12–12	53–48	54	48,0	44,8	54,7	−9,9	45 %	Balanced & physical
7	Getafe	38	15–6–17	32–38	51	55,2	36,1	41,0	−4,9	42 %	Low block & direct
8	Rayo Vallecano	38	12–14–12	41–44	50	53,9	53,6	47,9	+5,7	52 %	Possession control
9	Valencia	38	13–10–15	46–55	49	55,7	50,9	47,5	+3,4	45 %	Counter-attacks & crosses
10	Real Sociedad	38	11–13–14	59–61	46	50,1	52,1	54,3	−2,2	48 %	Possession control
11	Espanyol	38	12–10–16	43–55	46	54,4	54,0	57,0	−3,0	40 %	Low block & direct
12	Athletic Club	38	13–6–19	43–58	45	58,3	54,0	39,1	+14,9	61 %	Possession & high press
13	Elche	38	10–13–15	49–57	43	42,2	45,6	57,0	−11,4	59 %	Possession control
14	Deportivo Alaves	38	11–10–17	44–56	43	58,3	54,3	49,0	+5,3	48 %	Possession control
15	Sevilla FC	38	12–7–19	46–60	43	48,5	41,4	45,2	−3,8	53 %	Possession control
16	Osasuna	38	11–9–18	44–50	42	54,0	50,2	49,0	+1,2	43 %	Low block & direct
17	Mallorca	38	11–9–18	47–57	42	47,7	47,1	59,3	−12,2	39 %	Low block & direct
18	Levante	38	11–9–18	47–61	42	48,1	47,9	61,2	−13,3	36 %	Low block & direct
19	Girona	38	9–14–15	39–55	41	47,1	47,1	62,3	−15,2	50 %	Balanced & physical
20	Real Oviedo	38	6–11–21	26–60	29	42,0	38,0	63,8	−25,8	36 %	Low block & direct

Latest articles

All articles

2026-05-22 · 1 min

Ligapuls: La Liga, 2025

Real Madrid took an important 1-0 victory against Sevilla while Barcelona continued their dominance with 3-1 against Real Betis, which means that Barcelona retains their 11-point lead at the top of the table. The week's big surprise was Valencia who won impressively 4-3 against Real Sociedad away from home, while Kylian Mbappé continues to excel for Real Madrid with the league's highest PlaymakerRank at 5.0.

2026-05-08 · 1 min

Player Profile: Lamine Yamal (FC Barcelona)

Lamine Yamal, 18-year-old right winger at Barcelona, has shown exceptional offensive production with 0.6 goals per match and 2.2 expected assists per match in La Liga. His combination of goal threat and creativity, together with 76 meters of progressive ball carries per match, makes him one of the league's most influential offensive players despite his young age.

2026-04-18 · 1 min

Scouting Report: Pedri (FC Barcelona)

Pedri, 24-year-old midfielder at FC Barcelona, shows exceptional quality as a regista with statistics that far exceed the La Liga average in passing play, chance creation and ball progression. His combined technical brilliance and tactical maturity make him a high-priority target for European top clubs.

Played matches

Prediction track record

No settled matches yet for this selection — the scorecard fills in after every played round.

How the predictions work

Every prediction comes from PlaymakerAI's match model — the same data platform professional clubs use for scouting and match analysis. The model is trained on event data from hundreds of thousands of matches and weighs over 200 factors per team: strength ratings, current form, playing style, squad player profiles, fixture congestion, travel and even matchday weather.

For each fixture the model produces a full goal distribution. From it we derive the 1X2 probabilities, the score matrix, expected goals, over/under lines and both-teams-to-score. Predictions are frozen before kickoff and never changed afterwards — once a match finishes we grade it openly, hit or miss.

Odds are collected continuously from several bookmakers. When the model's probability for an outcome exceeds what the odds imply, we flag it as value (EV+). That is the model's assessment, not a guarantee: even positive-EV bets lose often. Gamble responsibly.

Predictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.