Is It Profitable to Bet on Football Favourites?

Introduction

Betting on favourites in football might seem like the safest option. After all, favourites are expected to win most of the time, and casual bettors often see them as a reliable way to build profit slowly. But is this really the case over thousands of matches and across multiple leagues?

To answer this question, we analysed over 62,800 matches from 17 leagues, covering both summer and winter competitions, starting from the 2014/2015 season (or 2014 for summer leagues). All results are based on closing odds from 1xBet, giving us a clear picture of long-term betting outcomes.

In this article, we will explore:

Overall results of betting on favourites and underdogs.
How performance changes by odds range.
Case studies from the Premier League and LaLiga.
Key takeaways for football bettors.

Overall Results: Favourites vs Underdogs

When looking at all 62,848 matches across 17 leagues, the results are clear: blindly betting on favourites or underdogs does not generate profit in the long run.

Backing the favourite in every game would have resulted in a total loss of –1474 units, equivalent to a –2.35% yield. While favourites do win more often, the odds are adjusted so tightly by bookmakers that long-term profit disappears.

On the other hand, underdogs performed even worse. A blanket strategy of betting on the underdog in every match would have lost –5303 units, with a yield of –8.44%. Despite the occasional big upset, the losses accumulate heavily over time.

The evidence suggests that neither favourites nor underdogs are profitable when backed blindly. The market efficiently prices in the expected outcomes.

wdt_ID	wdt_created_by	wdt_created_at	wdt_last_edited_by	wdt_last_edited_at	League	Games	P/L Fav Home	P/L Fav Away	P/L Fav Total	Yield Fav Home	Yield Fav Away	Yield Fav Total
1	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	Brazil Serie A Betano	4,008	11.28	-36.25	-24.97	0.28	-0.90	-0.62
2	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	England Championship	5,617	-80.49	-24.88	-105.37	-1.43	-0.44	-1.88
3	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	England League One	2,864	-1.72	16.38	14.66	-0.06	0.57	0.51
4	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	England League Two	2,868	-100.37	-41.84	-142.21	-3.50	-1.46	-4.96
5	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	England Premier League	3,830	-57.37	-31.38	-88.75	-1.50	-0.82	-2.32
6	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	France Ligue 1	3,577	-63.65	-20.26	-83.91	-1.78	-0.57	-2.35
7	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	France Ligue 2	3,277	-30.21	-0.07	-30.28	-0.92	0.00	-0.92
8	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	Germany 2. Bundesliga	3,096	-87.16	-67.81	-154.97	-2.82	-2.19	-5.01
9	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	Germany Bundesliga	3,077	-97.39	-71.04	-168.43	-3.17	-2.31	-5.47
10	panifran_footiqo	09-09-25 01:58 PM	panifran_footiqo	09-09-25 01:58 PM	Italy Serie A	3,819	-41.34	60.13	18.79	-1.08	1.57	0.49
							∑ = -548.42	∑ = -217.02	∑ = -765.44

wdt_ID	wdt_created_by	wdt_created_at	wdt_last_edited_by	wdt_last_edited_at	League	Games	P/L Dog Home	P/L Dog Away	P/L Dog Total	Yield Dog Home	Yield Dog Away	Yield Dog Total
18	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	Brazil Serie A Betano	4,008	-69.63	-320.30	-389.93	-1.74	-7.99	-9.73
19	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	England Championship	5,617	29.82	-228.76	-198.94	0.53	-4.07	-3.54
20	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	England League One	2,864	-87.96	-171.38	-259.34	-3.07	-5.98	-9.06
21	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	England League Two	2,868	3.38	-92.39	-89.01	0.12	-3.22	-3.10
22	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	England Premier League	3,830	30.15	-79.10	-48.95	0.79	-2.07	-1.28
23	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	France Ligue 1	3,577	-62.85	-72.29	-135.14	-1.76	-2.02	-3.78
24	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	France Ligue 2	3,277	-58.79	-140.22	-199.01	-1.79	-4.28	-6.07
25	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	Germany 2. Bundesliga	3,096	3.36	-155.14	-151.78	0.11	-5.01	-4.90
26	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	Germany Bundesliga	3,077	73.65	-123.88	-50.23	2.39	-4.03	-1.63
27	panifran_footiqo	10-09-25 01:41 PM	panifran_footiqo	10-09-25 01:41 PM	Italy Serie A	3,819	-298.51	-279.99	-578.50	-7.82	-7.33	-15.15
							∑ = -437.38	∑ = -1,663.45	∑ = -2,100.83

By Odds Range

Breaking down results by odds interval provides more detail. Interestingly, only the very shortest odds (1.01–1.50) produced a small positive return, with a +0.40% yield. However, this edge is tiny, and with bookmaker margins and variance, it is not realistically exploitable.

From odds 1.51 up to around 2.50, losses remain moderate, with yields between –1.3% and –2.9%. As odds increase further, the situation worsens significantly. Matches in the 2.51–3.00 range lost almost –3.8%, and odds between 3.01–4.00 generated losses close to –7%.

The biggest losses came from very large outsiders at odds above 4.00, where the strategy produced a –10.8% yield. This shows that longshot favourites, while tempting, are especially overpriced by the market.

League :

Odds Interval :

Games :

PL :

Yield :

wdt_ID	wdt_created_by	wdt_created_at	wdt_last_edited_by	wdt_last_edited_at	League	Odds Interval	Games	PL	Yield
35	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	Brazil Serie A Betano	1.01 - 1.50	500	-2.23	-0.45
36	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	Brazil Serie A Betano	1.51 - 1.75	713	-32.62	-4.58
37	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	Brazil Serie A Betano	1.76 - 2.00	639	20.08	3.14
38	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	Brazil Serie A Betano	2.01 - 2.25	529	-6.55	-1.24
39	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	Brazil Serie A Betano	2.26 - 2.50	413	17.88	4.33
40	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	Brazil Serie A Betano	2.51 - 3.00	570	7.28	1.28
41	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	Brazil Serie A Betano	3.01 - 4.00	432	-11.91	-2.76
42	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	Brazil Serie A Betano	> 4.00	211	-49.28	-23.36
43	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	England Championship	1.01 - 1.50	277	5.51	1.99
44	panifran_footiqo	10-09-25 01:51 PM	panifran_footiqo	10-09-25 01:51 PM	England Championship	1.51 - 1.75	647	1.65	0.26
					League	Odds Interval	Games	PL	Yield
							∑ = 4,931	∑ = -50.19

Premier League Case Study

Looking at the Premier League, we restricted the sample to clubs with at least 100 matches played as favourites. This ensures statistical relevance and avoids distortion from smaller samples.

Across all qualifying clubs, the strategy of backing the favourite produced a total loss of –94.6 units over 3320 matches, equivalent to a –2.85% yield. Even in one of the most popular and liquid betting markets, the odds remain efficient.

Some clubs performed slightly better than others. For example, Arsenal managed to stay close to break-even with a +0.79% yield. However, most other teams, including Chelsea and Manchester United, still showed clear long-term losses when backed blindly.

This highlights that even in the Premier League, where favourites are often household names, blindly betting on them is not a profitable strategy.

wdt_ID	wdt_created_by	wdt_created_at	wdt_last_edited_by	wdt_last_edited_at	Teams	GAMES FAV HOME	PL FAV HOME	GAMES FAV AWAY	PL FAV AWAY	TOTAL FAV GAMES	PL TOTAL FAV	YIELD FAV HOME	YIELD FAV AWAY	YIELD FAV OVERALL
18	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Arsenal	170	11.69	147	-9.18	317	2.51	6.88	-6.24	0.79
19	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Aston Villa	81	1.51	44	-2.43	125	-0.92	1.86	-5.52	-0.74
20	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Bournemouth	85	-4.56	22	2.43	107	-2.13	-5.36	11.05	-1.99
21	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Brighton	93	-32.92	45	-6.43	138	-39.35	-35.40	-14.29	-28.51
22	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Chelsea	175	-20.71	148	-3.46	323	-24.17	-11.83	-2.34	-7.48
23	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Crystal Palace	102	2.47	31	2.45	133	4.92	2.42	7.90	3.70
24	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Everton	116	5.92	53	-6.63	169	-0.71	5.10	-12.51	-0.42
25	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Leicester	108	2.00	55	6.24	163	8.24	1.85	11.35	5.06
26	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Liverpool	181	2.92	162	-1.87	343	1.05	1.61	-1.15	0.31
27	panifran_footiqo	10-09-25 02:03 PM	panifran_footiqo	10-09-25 02:03 PM	Manchester City	190	-5.04	181	-9.24	371	-14.28	-2.65	-5.10	-3.85

LaLiga Case Study

For LaLiga, the analysis also focused on clubs with at least 100 matches played as favourites. Here the picture looks slightly different compared to the Premier League.

Across all qualifying teams, betting blindly on favourites produced a small overall loss of just –12.6 units over 2913 matches, equivalent to a –0.43% yield. This is close to break-even, suggesting that favourite pricing in Spain is tighter than in England.

Certain teams, such as Real Betis (+12.18% yield) and Atlético Madrid (+5.55% yield), delivered positive long-term results as favourites. However, others like Celta Vigo (–9.12%) and even Barcelona (–1.18%) offset these gains.

Overall, while LaLiga favourites came closer to profitability than in other leagues, the general conclusion remains the same: a blanket favourite strategy is not consistently profitable.

wdt_ID	wdt_created_by	wdt_created_at	wdt_last_edited_by	wdt_last_edited_at	Teams	GAMES FAV HOME	PL FAV HOME	GAMES FAV AWAY	PL FAV AWAY	TOTAL FAV GAMES	PL TOTAL FAV	YIELD FAV HOME	YIELD FAV AWAY	YIELD FAV OVERALL
34	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Ath Bilbao	160	6.57	96	-2.02	256	4.55	4.11	-2.10	1.78
35	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Atl. Madrid	177	21.38	163	-2.50	340	18.88	12.08	-1.53	5.55
36	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Barcelona	190	-2.64	181	-1.74	371	-4.38	-1.39	-0.96	-1.18
37	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Betis	131	13.41	45	8.03	176	21.44	10.24	17.84	12.18
38	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Celta Vigo	140	-11.79	50	-5.53	190	-17.32	-8.42	-11.06	-9.12
39	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Espanyol	88	-1.07	12	-0.49	100	-1.56	-1.22	-4.08	-1.56
40	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Getafe	110	11.93	28	-9.23	138	2.70	10.85	-32.96	1.96
41	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Real Madrid	190	-1.96	174	-0.24	364	-2.20	-1.03	-0.14	-0.60
42	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Real Sociedad	159	-22.83	92	12.18	251	-10.65	-14.36	13.24	-4.24
43	panifran_footiqo	10-09-25 02:14 PM	panifran_footiqo	10-09-25 02:14 PM	Sevilla	159	1.56	104	-8.02	263	-6.46	0.98	-7.71	-2.46

Conclusions

The results from over 62,800 matches across 17 leagues leave little doubt: betting blindly on favourites or underdogs is not profitable. Favourites lose on average –2.35% yield, while underdogs perform even worse with –8.44%. Odds intervals confirm that only the very shortest prices (1.01–1.50) come close to profit, but the edge is tiny and practically impossible to exploit in real betting conditions.

Even in the most followed leagues, such as the Premier League (–2.85% yield) and LaLiga (–0.43% yield), the strategy fails to deliver consistent long-term returns. Individual clubs may show temporary positive results, but across thousands of matches, bookmaker efficiency prevails.

The key lesson: successful betting requires deeper analysis. Rather than blindly backing favourites or underdogs, bettors should explore more specific angles, such as recent form, home vs away performance, referee tendencies, or manager profiles. That is exactly where Footiqo helps: free access to advanced filters and segmented stats for smarter football research.

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FAQ — Betting on Football Favourites

Is blindly backing favourites profitable long term?

No. Across 17 leagues since 2014, favourites were slightly negative overall, while underdogs were more negative. Markets are generally efficient and the bookmaker margin (overround) erodes returns.

Do very short favourites (e.g., 1.01–1.50) perform better?

Yes, they were close to break-even overall in our sample, but the apparent edge is small and can vanish once you account for variance, league cycles, and changing team strength. Always cross-check current form: Teams 1X2 (Full Time).

Are away favourites better than home favourites?

On average they lost less in our data. A plausible explanation is that home-field narratives can be slightly overpriced at shorter odds. Validate per league using: Leagues 1X2.

Which leagues were most “favourite-friendly”?

Only a few showed marginally positive long-run results for favourites. Always re-test on fresh data and by half: 1X2 Full Time, Goals.

Does splitting by first/second half help?

Sometimes. Momentum and game state differ by half. Explore first-half and second-half prices alongside BTTS and Cards for context: Teams BTTS, Referees – Cards.

How should I build a more selective strategy?

Combine odds filters, recent form, and league specificity. Then validate out-of-sample. Slice by season windows and venue: Teams 1X2, Leagues 1X2.

Key Terms & Methodology

Key terms

Favourite: the team with the shortest closing price in the 1X2 market.
Underdog: the opponent of the favourite (the longer-priced team in 1X2).
Home/Away favourite: favourite playing at home/away, used for venue splits.
P/L (Profit/Loss): sum of returns staking 1 unit per bet (win: odds − 1 ; loss: −1 ).
Yield: P/L ÷ number of bets . We report yield as a proportion (convertible to %).
Odds intervals: favourite closing price bands: 1.01–1.50, 1.51–1.75, 1.76–2.00, 2.01–2.25, 2.26–2.50, 2.51–3.00, 3.01–4.00, >4.00.

Data & scope

Leagues: 17 domestic competitions; total sample ≈ 62,848 matches.
Window: seasons from 2014 or 2014/15 (summer/winter calendars) through the latest available data in this study.
Odds source: 1xBet closing 1X2 prices (pre-match).
Coverage (as labelled in the dataset): Brazil Serie A (Betano), England: Premier League, Championship, League One, League Two; France: Ligue 1, Ligue 2; Germany: Bundesliga, 2. Bundesliga; Italy: Serie A, Serie B; Netherlands: Eredivisie; Portugal: Liga Portugal; Spain: LaLiga, LaLiga2; Turkey: Süper Lig; USA: MLS.

How we computed the results

For every match with available closing 1X2 odds, identify the favourite and the underdog.
Create four streams per league: home favourites, away favourites, home underdogs, away underdogs.
Stake 1 unit on the relevant side in every eligible match; aggregate P/L and compute Yield.
For the odds-band study, bucket matches by the favourite’s closing price using the intervals above and aggregate across leagues.
For team-level sections (Premier League & LaLiga), include only clubs with ≥100 matches as favourites to reduce small-sample noise.

Quality checks & notes

De-duplication, basic outlier checks on odds, and consistency checks across seasons.
Results are in units (currency-agnostic). No commissions or rebates assumed.
No in-play trading, no line-shopping, no Kelly sizing, this is a flat-stake, pre-match view.
Historical comparability can be affected by changes such as VAR adoption, fixture congestion, and evolving team strengths.

Limitations

Bookmaker margin and market efficiency compress long-run returns; small positives may be sample-specific.
Sample sizes vary by interval & league; very short or very long price bands can be volatile.
Past performance does not guarantee future results. This analysis is for information & education only.

Glossary of Markets

1X2 (Win–Draw–Loss): Home win (1), Draw (X), Away win (2). The most common match outcome market.
Goals (Over/Under): Total number of goals in the match compared with a line (e.g., Over/Under 2.5).
Both Teams to Score (BTTS): A “Yes/No” on whether each side scores at least once.
Cards: Bookings market based on yellow/red cards (often converted to points in some bookmakers).
Corners: Total corners in a match; can also be split by team or by half.

Time splits

Full Time (FT): Entire 90 minutes plus stoppage time.
First Half (1H) & Second Half (2H): Market performance limited to the respective 45-minute periods (plus stoppage).

Why the splits matter

Tempo & tactics often differ by half; some sides start slow and finish strong.
Game state (leading/behind) drives goal risk, card pressure, and corner frequency.
Referees & managers can have repeatable tendencies that only surface in half-level data.

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