kuklachert

Had a lot of luck in November resulting in a sizable ROI improvement. Stats since the last update:
Total stake: 75.00 (15 bets) Total winnings: 118.20 (112.29 after tax) Stats since the beginning of the thread:
Total stake: 655.00 (131 bets) Total winnings: 729.90 (693.41 after tax) ROI: 11.4% (5.9%) Next picks to be posted in December.

Mansouri v Droguet, M15 Monastir, 1.72 with bet365

Cornut Chauvinc v Lopez San Martin, M15 Madrid, 1.90 with bet365

Tilbuerger v Avdeeva, W15 Antalya, 2.62 with bet365

Poljak v Orlov, M15 Sharm El Sheikh, 2.00 with bet365

Zarycka v Lamens, W25 Las Palmas, 1.65 with bwin

Ouahab v Weis, M15 Villena, 2.25 with bet365 Crepaldi v Deviatiarov, M15 Sharm El Sheikh, 2.25 with bet365

This post didn't get traction here, but I'll allow myself one more plug. The US Open tipping competition has been set up and has almost 20 tipsters as of now (primarily from reddit). If you want to participate and to measure your tipping performance against other gamblers, write me a private message and I'll share the link with you. I promise not to spam here any more and hope this post is still within the acceptable boundaries. Good luck everyone!

Going on a break was obviously useful.

enjoy your break ??

A fitting end to this week, the match again being decided against me by a couple of points. Weekly summary:
Total stake: 125.00
Total winnings: 106.95 (102.10 after tax)
Totals since thread start:
Total stake: 170.00
Total winnings: 159.40 (152.18)
ROI: -6.2% (-10.5%)
Going on a small break, will continue posting towards the end of next week. Hope you'll miss me. ?

Second time this week, my pick loses after being 5-2 up in the third set. But I'm not surrendering ?
 

Results:
A disappointing couple of days, every close match went the wrong way, but these things happen.

Roundup of the first week:
Total stake: 45.00 Total winnings: 52.45 (50.08 after tax) ROI: 16.6% (11.3% after tax)

First results:
I will post totals/ROI at the end of each week.

Hi all,
in this thread I'll be sharing the results of my bets on ITF tournaments which I place using a model-based approach.
Why ITF?
ITF tournaments (lowest tier of professional tennis) seem to be an imperfect betting market where information is often scarce, so I assume bookies do not always know exactly what they're doing when they're offering odds. For Challenger/ATP/WTA tournaments my approach didn't work so well (albeit on a small sample) so I stopped betting there and concentrated on ITF. I bet on both men's and women's tournaments (no W60, W80, W100 because they attract a player field of a comparable level to ATP challengers which I find hugely unpredictable). The best bookies for ITF tournaments are bet365, Betclic. Bwin and Unibet occasionally also offer ok odds.
What does my model do?
It's a relatively simple Logistic Regression that predicts each player's win probabilities. Following main factors go into the model:
ELO rating (several versions calculated with different formulae - some place more weight in recent form, others are more influenced by long-term results) Recent changes in ELO rating Players' form on the surface played Head-to-head (overall/on surface played) Home advantage Additional factors I apply on top of the model as an "expert judgment" are:
Are "rising talents" involved in a match? (they tend to have ELO rankings lower than their true level) Are players from different playing fields involved? (In case 2 players meet, one of which mainly plays in Challengers and the other in Futures, the ELO of the Challenger player tends to underestimate his relative level because he plays in a stronger field; similarly, players from the Asian fields tend to be weaker than their European/American counterparts with the same ELO) Has the model performed well with the players I'm betting on/against? (if I bet against Roger Federer twice this week and he wins both times, I'm not likely to bet another time even if the model recommends me to) Do players have sufficient match form? (I won't bet on a player who hasn't played for 6 months if the model recommends me to) Tiredness (I won't bet on a player who yesterday played a 4-hour match). The probabilities generated by the model are then compared with to odds. I only bet on odds between 1.4 and 2.9. For higher odds, I found the model to be unreliable, for lower odds it just doesn't make sense as I live in Germany where all winnings on betting are taxed 5%. To account for model risks I apply an additional margin of conservatism to select my bets.
So if the model tells me that Player A wins with 60% probability, the lowest odds I want to take on Player A would be (1/0.6)*(1/0.95)*1,1=1.93. The (1/0.95) multiplier accounts for the betting tax, the 1.1 multiplier accounts for model error. In case I'm really convinced by the players' stats I might accept odds of 1.85-1.90.
The model is calibrated on an extensive history (ITF men's and women's matches starting 2001).
Final words
The 5% tax makes profitable betting in Germany pretty much impossible, so I only bet small amounts for fun. In this thread, I will show both profit before and after tax so people in other countries get a realistic view of the model performance. So far after ~950 bets I have achieved an ROI of around 7% before tax and 2% after tax which I find decent. I will always bet the same amount, let's say a symbolic 5 EUR on each match. Let's hope I can maintain my ROI after I start posting. I also hope this thread attracts some tennis betting enthusiasts, especially those who use statistical/ML methods and are willing to share their secrets because I truly believe a scientific approach can make betting profitable.

First results:
I will post totals/ROI at the end of each week.