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Venue Guide/Tennis

Which Grand Slam Is Best for Favourites? Four Venues Compared

Four Grand Slams, two tours, one question: does the venue change how reliably the favourite wins? On clay the men's market leans short, and in New York it doesn't.

Hana SeoWritten by Tennis Predictions specialist
Which Grand Slam Is Best for Favourites? Four Venues Compared
Venue card
Sport
Tennis
Question
Do tennis favourites win more often than their prices imply at Melbourne Park, Roland Garros, Wimbledon or Flushing Meadows, for men and for women?
Survey
Grand Slam singles 2010-2025 (no Wimbledon in 2020), 15,507 priced, completed matches
Ground readings

Every Grand Slam sells itself on its surface, its crowd and its weather. I wanted to know whether any of that shows up where a bettor feels it: in how often the shorter-priced player actually wins compared with what the closing price said. The study covers 15,507 priced, completed Slam singles matches from 2010-2025, split by venue and by tour.

The headline is that men's favourites beat their prices at three of the four majors, most clearly at Roland Garros, where they won 78.5% against a priced 75.4%. Flushing Meadows is the outlier, with men's favourites at 74.6%, almost exactly on their price. In the women's draws the market is close to accurate everywhere. I lean on this every fortnight a major comes round, and it sits underneath my tennis predictions page.

Ground 1Men's favourites outrun their prices everywhere except New York

Each dumbbell pairs the margin-free closing chance with the actual win rate. For the men, the gap opens in Melbourne (priced 75.0%, won 77.6%), widens at Roland Garros, and holds at Wimbledon (priced 74.8%, won 77.2%). At the US Open the two dots almost touch: priced 74.7%, won 74.6%.

The women's rows are tighter. Wimbledon even dips slightly below price, with 71.2% won against 71.4% priced, while the US Open is the only women's venue with a visible edge, at 73.7% against 72.0%.

Grand Slam favourites: priced vs wonMargin-free closing chance vs actual win rate
PricedWon95% range
Melbourne ATP1,945 matches
75.0% โ†’ 77.6% +2.6
Melbourne WTA2,005 matches
72.0% โ†’ 72.8% +0.8
Roland Garros ATP1,963 matches
75.4% โ†’ 78.5% +3.1
Roland Garros WTA1,988 matches
71.8% โ†’ 72.2% +0.4
Wimbledon ATP1,836 matches
74.8% โ†’ 77.2% +2.4
Wimbledon WTA1,867 matches
71.4% โ†’ 71.2% โˆ’0.2
US Open ATP1,908 matches
74.7% โ†’ 74.6% โˆ’0.1
US Open WTA1,995 matches
72.0% โ†’ 73.7% +1.7
65%70%75%80%85%
View the data: grand slam favourites: priced vs won
PricedWon95% range
Melbourne ATP (1,945 matches)75.0%77.6%ยฑ1.9
Melbourne WTA (2,005 matches)72.0%72.8%ยฑ1.9
Roland Garros ATP (1,963 matches)75.4%78.5%ยฑ1.8
Roland Garros WTA (1,988 matches)71.8%72.2%ยฑ2
Wimbledon ATP (1,836 matches)74.8%77.2%ยฑ1.9
Wimbledon WTA (1,867 matches)71.4%71.2%ยฑ2.1
US Open ATP (1,908 matches)74.7%74.6%ยฑ2
US Open WTA (1,995 matches)72.0%73.7%ยฑ1.9

My reading is about movement. Slow red clay over best of five gives the better player time to recover position and grind through a bad set, which is exactly the kind of resilience a single price struggles to capture. One honest warning: these gaps of two or three points sit close to the ยฑ1.9 or so error ranges, so I treat them as tendencies rather than rules, and I only compare men with women within the same venue, since the formats differ.

Ground 2Backing every men's favourite paid only on clay and grass

Win rates matter less than returns, so this chart converts everything into flat-stake profit at closing prices. Men's favourites returned +1.6% at Roland Garros, +1.1% in Melbourne and +0.9% at Wimbledon, then fell to โˆ’2.7% at the US Open. Across all four, the men's total is a near-flat +0.2%.

Women's favourites lost money at every venue: โˆ’3.0% at Wimbledon, โˆ’2.5% at Roland Garros, โˆ’2.1% in Melbourne and only โˆ’0.1% in New York, for โˆ’1.9% overall.

Flat-stake return backing every favouriteClosing prices, 1 unit per match
ATPWTA
Melbourne
+1.1% / โˆ’2.1%
Roland Garros
+1.6% / โˆ’2.5%
Wimbledon
+0.9% / โˆ’3.0%
US Open
โˆ’2.7% / โˆ’0.1%
All four
+0.2% / โˆ’1.9%
โˆ’4.0%0+4.0%
View the data: flat-stake return backing every favourite
ATPWTA
Melbourne+1.1%โˆ’2.1%
Roland Garros+1.6%โˆ’2.5%
Wimbledon+0.9%โˆ’3.0%
US Openโˆ’2.7%โˆ’0.1%
All four+0.2%โˆ’1.9%

What strikes me is how the US Open flips the pattern for both tours. It is the venue where men's favourites do worst and women's favourites do best, which tells me the hard courts in New York reward something different from the other three.

Ground 3The shortest favourites are most dependable in Melbourne

Here both tours are combined and sliced by how strongly the favourite was priced. In the 90%+ band, Melbourne stands out at 97.2% across 567 matches, ahead of Wimbledon at 95.5%, the US Open at 94.8% and Roland Garros at 94.7%.

Roland Garros earns its edge further down, at 89.5% in the 80-90% band, the best figure in that column. At the coin-flip end, favourites priced 50-65% won between 56.6% in Melbourne and 57.9% in New York.

Favourite win rate by price band at each SlamBoth tours; band = margin-free chance of the favourite
50-65%
65-80%
80-90%
90%+
Melbourne
56.6%
75.6%
87.4%
97.2%
Roland Garros
57.3%
74.8%
89.5%
94.7%
Wimbledon
57.6%
74.6%
85.9%
95.5%
US Open
57.9%
74.2%
85.8%
94.8%

Smallest cell: 445 matches

View the data: favourite win rate by price band at each slam
50-65%65-80%80-90%90%+
Melbourne56.6%75.6%87.4%97.2%
Roland Garros57.3%74.8%89.5%94.7%
Wimbledon57.6%74.6%85.9%95.5%
US Open57.9%74.2%85.8%94.8%

So the clay advantage is not about heavy odds-on favourites: it lives in the band where a clearly better player meets a capable opponent. That is where I expect slow conditions and long rallies to pull the stronger mover through.

Ground 4Underdogs fall short of their prices in both weeks

The table splits upsets into rounds 1-2 and round 3 onward. Every cell in both 'vs priced' columns is negative, so underdogs won less often than their prices suggested at every Slam and every stage. Roland Garros shows the steadiest shortfall, at โˆ’1.7 early and โˆ’1.6 later.

The US Open is the interesting one. Its early-round underdogs came closest to their price, at โˆ’0.7, before falling to โˆ’1.5 from round 3 on. Wimbledon has the highest late upset rate, 26.4%, though still below price at โˆ’1.3.

Underdog wins: first week vs second weekRounds 1-2 vs round 3 onward, both tours
SlamR1-R2 nR1-R2 upsetsvs pricedR3+ nR3+ upsetsvs priced
Melbourne2,98724.8%โˆ’1.896325.0%โˆ’1.2
Roland Garros2,99324.5%โˆ’1.795825.4%โˆ’1.6
Wimbledon2,79825.7%โˆ’1.090526.4%โˆ’1.3
US Open2,94725.9%โˆ’0.795625.7%โˆ’1.5

I read the US Open early rounds as the softest spot for favourites in this whole study. Players arriving from a hot, crowded hard-court summer often carry fatigue that a ranking hides, and the first week is where that tends to show.

Where to look

  • Respect clay favourites

    Men's favourites at Roland Garros won 78.5% against a priced 75.4% and returned +1.6%, so I don't fade a clear clay favourite just because the price looks short.

  • Question early New York favourites

    US Open underdogs in rounds 1-2 came within โˆ’0.7 points of their price, the closest of any Slam, so first-week favourites in New York deserve extra scrutiny.

  • Avoid blanket women's favourites

    Backing every women's favourite lost money at all four Slams, worst at Wimbledon with โˆ’3.0%, so selection matters far more than the label.

Tennis PredictionsToday's tennis picksDaily predictions, read against the same records.
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Questions bettors ask

Which Grand Slam is best for backing favourites?

For men, Roland Garros: favourites won 78.5% against a priced 75.4% and returned +1.6% at flat stakes. The US Open was the weakest, at โˆ’2.7%.

Do women's favourites win more often than their odds suggest at Slams?

Barely. Across all four Slams, women's favourites returned โˆ’1.9%, with the US Open closest to break-even at โˆ’0.1%.

Are there more upsets in the first week or the second week of a Slam?

Rates are similar in both weeks; Wimbledon's round 3 onward upset rate of 26.4% is the highest. At every venue and stage, underdogs won less often than their prices implied.

Hana Seo
Written byHana Seo

I'm Hana Seo, based in Seoul, and I write the expert tennis predictions at horse-racing.tips โ€” where surface and scheduling tell me more than the seedings ever do.

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