2014 Ethias Trophy – Singles

Radek Štěpánek was the defending champion but chose not to participate.

Singles
2014 Ethias Trophy
Champion David Goffin
Runner-up Steve Darcis
Final score6–3, 6–3
Main article: 2014 Ethias Trophy

David Goffin won his 4th title of the year, defeating compatriot Steve Darcis in the final 6–3, 6–3.

Seeds
  1. David Goffin (Champion)
  2. Igor Sijsling (Second round)
  3. Jiří Veselý (Semifinals)
  4. Thomaz Bellucci (Second round)
  5. Dudi Sela (First round)
  6. Paul-Henri Mathieu (withdrew)
  7. Andreas Haider-Maurer (Second round)
  8. Dustin Brown (Second round)
  9. Tobias Kamke (Quarterfinals)

Draw

Key

Finals
Semifinals Final
          
1/WC David Goffin 7 4 6
  Marsel İlhan 5 6 1
1/WC David Goffin 6 6
PR Steve Darcis 3 3
3 Jiří Veselý 4 4
PR Steve Darcis 6 6

Top Half
First Round Second Round Quarterfinals Semifinals
1/WC D Goffin 77 6
LL J Huta Galung 61 0 1/WC D Goffin 7 6
  N Mahut 3 6 63 Q M Bachinger 5 2
Q M Bachinger 6 3 77 1/WC D Goffin 6 6
  I Bozoljac 64 77 3   A Zverev 3 2
A Zverev 77 65 6   A Zverev 79 6
  N Gomboš 63 3 8 D Brown 67 3
8 D Brown 77 6 1/WC D Goffin 7 4 6
4 T Bellucci 6 77 M İlhan 5 6 1
K de Schepper 4 64 4 T Bellucci 67 4
Alt J Pospíšil 4 64 M İlhan 79 6
M İlhan 6 77   M İlhan 6 77
I Marchenko 6 3 4 9 T Kamke 4 63
Q A Arnaboldi 4 6 6 Q A Arnaboldi 1 4
F Dustov 1 63 9 T Kamke 6 6
9 T Kamke 6 77

Bottom Half
First Round Second Round Quarterfinals Semifinals
7 A Haider-Maurer 6 6
WC J Cagnina 3 4 7 A Haider-Maurer 4 5
  A Ungur 2 6 63 R Bemelmans 6 7
R Bemelmans 6 4 77   R Bemelmans 4 6 63
Q M Teixeira 6 63 2 3 J Veselý 6 3 77
LL U Ignatik 2 77 6 LL U Ignatik 6 3 63
  V Millot 3 6 4 3 J Veselý 4 6 77
3 J Veselý 6 4 6 3 J Veselý 4 4
5 D Sela 1 63 PR S Darcis 6 6
PR S Darcis 6 77 PR S Darcis 6 6
Q Y Marti 6 0 6 Q Y Marti 2 4
WC K Coppejans 4 6 1 PR S Darcis 6 6
WC O Rochus 6 3 3 G Melzer 3 2
G Melzer 4 6 6   G Melzer 6 1 7
M Berrer 63 3 2 I Sijsling 4 6 5
2 I Sijsling 77 6
gollark: Meanwhile, GPT-3, OpenAI's latest GPT text generation thing, has *175 billion* parameters and uses, what, tens of gigabytes of memory?
gollark: No, lambda calculus is a relatively simple model you can understand fairly easily.
gollark: And with neural networks, you don't actually know *how* the network does its job, just that you feed in pixels and somehow get classification data out.
gollark: There is still not, as far as I know, an approach to detect what an object is other than just training neural networks on the task.
gollark: It's simple to say, for example, "the program should detect if something is a bird", but incredibly hard to actually explain how to detect birds.

References
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