Super Liga

Moldova · Season 2026/27

2026/27 2025/26

Matchday 12 of 14 86%

League Table

8 Teams

#	Team	P	W	D	L	GF–GA	GD	Pts	Form
1	Zimbru — Champion	12	8	2	2	27–11	+16	26	V V V V V
2	Sheriff Tiraspol	12	7	4	1	25–10	+15	25	V P S V P
3	Petrocub	12	6	3	3	23–13	+10	21	V P V S S
4	Dacia-Buiucani	12	5	2	5	16–16	+0	17	V S P P V
5	Politehnica UTM	12	4	3	5	18–18	+0	15	S V P S V
6	Milsami Orhei	12	3	5	4	11–16	-5	14	S V P V S
7	Sireți	12	0	7	5	7–17	-10	7	S S P P P
8	CSF Bălți	12	1	2	9	9–35	-26	5	S S S S S
1	Petrocub — Champion	6	5	0	1	17–6	+11	15	V S V V V
2	Sheriff Tiraspol	6	4	2	0	14–4	+10	14	V P V V P
3	Zimbru	6	4	1	1	13–7	+6	13	P S V V V
4	Dacia-Buiucani	6	3	1	2	9–10	-1	10	S S V P V
5	Politehnica UTM	6	2	3	1	9–4	+5	9	S P V P V
6	Milsami Orhei	6	2	2	2	5–5	+0	8	S V P V S
7	Sireți	6	0	4	2	3–6	-3	4	P P P P S
8	CSF Bălți	6	1	1	4	7–17	-10	4	P S S S S
1	Zimbru — Champion	6	4	1	1	14–4	+10	13	S V V V V
2	Sheriff Tiraspol	6	3	2	1	11–6	+5	11	V V P S V
3	Dacia-Buiucani	6	2	1	3	7–6	+1	7	V V S P S
4	Petrocub	6	1	3	2	6–7	-1	6	P V S S P
5	Politehnica UTM	6	2	0	4	9–14	-5	6	V V S S S
6	Milsami Orhei	6	1	3	2	6–11	-5	6	P P S P V
7	Sireți	6	0	3	3	4–11	-7	3	S P P P S
8	CSF Bălți	6	0	1	5	2–18	-16	1	S P S S S

Champion

End of season projections

Monte Carlo simulation · 10,000 simulated seasons · updated 15 Sep 2026

Champion

Team	Projected Pts	Schedule	Trend
Zimbru	45 (32–53) pos. ~1.5°	C4 · T5 ELO 1484	▼1%
Sheriff Tiraspol	43 (30–52) pos. ~1.7°	C5 · T4 ELO 1472	▲1%
Petrocub	37 (23–48) pos. ~2.9°	C5 · T4 ELO 1499	▲0%
Dacia-Buiucani	28 (17–41) pos. ~4.8°	C4 · T5 ELO 1520	·
Politehnica UTM	26 (15–40) pos. ~5.1°	C4 · T5 ELO 1503	·
Milsami Orhei	26 (16–39) pos. ~5.2°	C5 · T4 ELO 1492	·
Sireți	18 (7–31) pos. ~6.9°	C4 · T5 ELO 1486	·
CSF Bălți	9 (5–21) pos. ~8.0°	C5 · T4 ELO 1510	·

% = probability of reaching that zone or better. Each sparkline shows the trend of the most relevant probability for each team over the last 12 daily simulations.

Upcoming matches

Recent results

Model & advanced data

Model calibration for this league▾

Probability band	Sample	Expected (mid)	Actual	Δ
50–60%%	5	55.00%	60.0%	+5.00%
60–70%%	5	65.00%	80.0%	+15.00%
70–100%%	6	85.00%	100.0%	+15.00%

Based on 16 verified predictions · Δ ≤ 5% = excellent calibration

Frequently Asked Questions

What predictions are available for Super Liga?

For Super Liga, ForzaPitch provides 1X2 win probabilities, expected goals (xG), Over 1.5 and Over 2.5 signals and season projections for title, European qualification and relegation per team.

How accurate are predictions for Super Liga?

Accuracy for Super Liga is tracked match by match and shown on this page. The model is calibrated specifically for Super Liga using per-league historical data.

How are Super Liga season projections calculated?

Season projections use 10,000 Monte Carlo simulations of the remaining fixtures, sampling from match probability distributions to estimate title, Champions League, Europa League and relegation probabilities per team.