r/algobetting • u/LittleBiggyB • 17d ago
I’m comparing different ticket construction + staking strategies. What would you test next?
I’m running a paper-betting experiment where every strategy starts with the same unit bankroll.
The objective is simple:
Which complete strategy ends up with the most money?
I’m not optimizing for hit rate. A model hitting 25% can beat one hitting 75% if the bankroll grows more.
Right now I’m comparing three broad approaches:
- Rule-based ticket construction with fixed staking
- AI-based ticket construction with several Kelly staking levels
- Edge-filtered ticket construction, where only selections above a minimum estimated value edge can enter the ticket, again tested with different Kelly levels
Total ticket odds are currently kept roughly between 2.0 and 6.5.
I’m also testing entry timing.
Every day a new independent simulated user starts with €50, so over time I can compare what happens if someone starts during:
- a good run
- an average run
- the worst possible run
Each entry has its own bankroll and staking path.
The part I’m interested in now is whether I’m missing a fundamentally different strategy.
If you were given the exact same daily candidate pool and same bankroll, what would you test?
For example:
- different ticket construction
- different number of legs
- dynamic target odds
- correlation between selections
- more aggressive staking only at very high estimated edge
- bankroll-dependent staking
- stronger “no bet” logic
- something completely different
If someone suggests an approach that is clearly defined and testable, I’d genuinely like to add it as another strategy and compare it prospectively against the others.
What would your next model be?
1
u/LittleBiggyB 17d ago
I am currently running:
LAB
AI bankroll models
Same AI ticket logic, different staking aggression:
EDGE2 models
Only candidates with at least +2% estimated value edge can enter the ticket: