Aston Villa vs Tottenham Statistics & Analysis

Aston Villa

May 03, 2026 - 18:00

1 1.56

2 1.05

xG Accuracy: 66%

Tottenham

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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

Market Prediction Result Outcome
Lebih / Kurang 2.5 Kurang 2.5 Lebih 2.5 (3 goals) ✖ Incorrect
Kedua-dua Pasukan Menjaringkan Gol BTTS Tidak Ya ✖ Incorrect
1X2 Aston Villa Tottenham ✖ Incorrect
Cerapan skor tepat 1-1 1-2 ✖ Incorrect

Taklimat perlawanan AI

Ringkasan perlawanan AI

Pre-match snapshot for this fixture.

League: Premier League
Fixture: Aston Villa vs Tottenham
Kickoff: 2026-05-02 14:00:00
1X2 (model): Home 47.6% · Draw 28.5% · Away 24.0%
xG (showing): Aston Villa 1.56 — Tottenham 1.05 (total xG ≈ 2.61)
Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
Model: 51.6% · Implied: 43.8% · Probability edge: +7.8 pts · Est. EV: +14.5%
BTTS (model): Yes 52.9% · No 47.1%
Correct score (top bin): 1-1 (12.0%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

Correct score remains high-variance even when a line is most likely on paper.

Taruhan terbaik dan sebab

Primary pick from the decision engine: Under 2.5 goals.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

When several markets sit near +EV, keep stakes small — correlation means edges do not add cleanly.

FAQ

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

Faktor risiko

Price movement: implied probabilities and EV move with odds.
Sample / data gaps: low-information leagues widen forecast bands.
In-play state: goals and red cards are not modelled here.
Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Metodologi

Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
Narrative: Template sentence library with fixture-stable selection (no per-request LLM for this block).
Compliance: Educational framing only; not personalised advice.

Terakhir dikemas kini

May 01, 2026 (UTC)

Bagaimana untuk menggunakan ini

Fokus pada baris Utama apabila anda mahukan satu idea yang boleh diambil tindakan.
Jangan parlay banyak picks tepi nipis bersama-sama;tepi tidak menambah dengan pasti.
Anggap pukulan panjang sebagai permainan pilihan, bersaiz tinggi sahaja.

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Premier League — Kedudukan

#	PASUKAN	MP	M	S	K	PTS
1	Arsenal	36	24	7	5	79
2	Manchester City	36	23	8	5	77
3	Manchester United	37	19	11	7	68
4	Aston Villa	37	18	8	11	62
5	Liverpool	37	17	8	12	59
6	Bournemouth	36	13	16	7	55
7	Brighton	37	14	11	12	53
8	Brentford	37	14	10	13	52
9	Sunderland	37	13	12	12	51
10	Chelsea	36	13	10	13	49
11	Newcastle	37	14	7	16	49
12	Everton	37	13	10	14	49
13	Fulham	37	14	7	16	49
14	Leeds	37	11	14	12	47
15	Crystal Palace	37	11	12	14	45
16	Nottingham Forest	37	11	10	16	43
17	Tottenham	36	9	11	16	38
18	West Ham	37	9	9	19	36
19	Burnley	36	4	9	23	21
20	Wolves	37	3	10	24	19

#	PASUKAN	MP	GS	GC	+/-	PTS
1	Manchester City	36	75	32	+43	77
2	Arsenal	36	68	26	+42	79
3	Manchester United	37	66	50	+16	68
4	Liverpool	37	62	52	+10	59
5	Bournemouth	36	56	52	+4	55
6	Chelsea	36	55	49	+6	49
7	Aston Villa	37	54	48	+6	62
8	Brentford	37	54	51	+3	52
9	Newcastle	37	53	53	0	49
10	Brighton	37	52	43	+9	53
11	Leeds	37	49	53	-4	47
12	Everton	37	47	49	-2	49
13	Nottingham Forest	37	47	50	-3	43
14	Tottenham	36	46	55	-9	38
15	Fulham	37	45	51	-6	49
16	West Ham	37	43	65	-22	36
17	Sunderland	37	40	47	-7	51
18	Crystal Palace	37	40	49	-9	45
19	Burnley	36	37	73	-36	21
20	Wolves	37	26	67	-41	19

#	PASUKAN	MP	xG	xGC	+/-	PTS
1	Arsenal	36	62.1	27.7	+34.4	79
2	Manchester City	36	65.8	39.0	+26.8	77
3	Manchester United	37	62.8	47.7	+15.1	68
4	Chelsea	36	62.0	48.3	+13.7	49
5	Liverpool	37	57.2	45.7	+11.5	59
6	Crystal Palace	37	56.5	47.8	+8.7	45
7	Brighton	37	56.5	48.1	+8.4	53
8	Newcastle	37	56.9	49.8	+7.1	49
9	Brentford	37	58.1	51.4	+6.7	52
10	Bournemouth	36	59.5	53.2	+6.3	55
11	Leeds	37	52.8	52.4	+0.4	47
12	Fulham	37	46.2	51.9	-5.7	49
13	Aston Villa	37	46.0	53.0	-7.0	62
14	Everton	37	45.5	54.9	-9.4	49
15	Nottingham Forest	37	44.4	55.3	-10.9	43
16	West Ham	37	42.5	55.2	-12.7	36
17	Tottenham	36	38.1	51.2	-13.1	38
18	Sunderland	37	37.2	52.5	-15.3	51
19	Wolves	37	33.5	57.0	-23.5	19
20	Burnley	36	31.2	72.9	-41.7	21