Tennis · M15 Rodez · 07/10, 12:00

Prediction: Robin Eldin vs Noah Boutleux

Team pages: Robin Eldin · Noah Boutleux

Prediction summary
Winner
47% 53%
Robin Eldin Noah Boutleux
Estimated games
20.4
Recent form · 10 last
Robin Eldin 8-2 (W-L)
WLWWWLWWWW
Noah Boutleux 5-5 (W-L)
LLWLWWLWWL
Our model (Elo) vs Market Rating Elo · Robin Eldin 1543 · Noah Boutleux 1523
Robin EldinNoah Boutleux
Our model53%47%
Market42%58%

The bar above blends our model with the market: where our probability diverges most from the odds is where the model sees the widest gap.

Statistics

Robin EldinNoah Boutleux
Win %70%60%
Win % · Clay 50% (2) –
Sets (G-P)1.5-0.91.2-0.9
Games (G-P)10.3-9.29.5-10.1
Aces2.73.8
Double faults1.23.9
1st serve %68.4%71.5%
Break %54.8%35.9%
Estimated total games (ours) 20.4

Last 10 matches played

Last matches of each player (sets and games). W = win, L = loss. Common opponents to both are in blue.

Robin Eldin

LWLWW

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Date Opponent Sets Games Res.
06/10 Jeremy Laumon
M15 Rodez
2-0 12-6 W
05/10 Julien Dando
M15 Rodez
2-0 12-2 W
21/09 Laurens Harnoth Manrubia
M15 Forbach
1-2 9-11 L
20/09 Yannick Baluska
M15 Forbach
2-0 13-8 W
17/09 Samir Banerjee
M25 Nevers
0-2 8-13 L
16/09 Luke Hooper
M25 Nevers
2-1 17-12 W
14/09 Kyle Overmyer
M25 Nevers
2-0 12-8 W
13/09 Jeremy Condere
M25 Nevers
2-1 9-10 W
09/09 Walid Ahouda
M25 Rabat · ~Clay
0-2 3-12 L
08/09 Dorian Tremblay
M25 Rabat · ~Clay
2-1 8-10 W

Noah Boutleux

WLWWL

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Date Opponent Sets Games Res.
26/09 Stefan Seifert
M15 Forbach
0-2 6-12 L
24/09 Tom Zeuch
M15 Forbach
2-0 12-8 W
22/09 Mac Visser
M15 Forbach
2-0 14-12 W
16/09 Samir Banerjee
M25 Nevers
0-2 4-12 L
14/09 Pierre Ngijol Carre
M25 Nevers
2-0 13-10 W
13/09 Romeo Nobili
M25 Nevers
2-0 12-5 W
09/09 Luc Fomba
M25 Plaisir
0-2 4-12 L
07/09 Pierre Ngijol Carre
M25 Plaisir
2-0 14-11 W
07/09 Mathys Picard
M25 Plaisir
2-1 11-7 W
23/08 Giovanni Boi
M15 Cap d'Agde
0-2 5-12 L

Frequently asked questions

Who is the favourite in Robin Eldin vs Noah Boutleux?

Our model gives 53% to Noah Boutleux, using surface Elo on clay.

What is the prediction based on?

On an Elo model by surface (clay) adjusted for opponent quality, compared with the market odds.