Hey team,
Been looking at Zeitgeist for sports prediction markets. I noticed a gap most prediction market implementations have: no validation layer to check if initial market prices are reasonable before liquidity concentrates.
For sports markets specifically, this creates arbitrage opportunities for sophisticated traders who identify mispriced outcomes before the crowd corrects them.
I built a model using underlying team performance metrics (not historical results) that flags when market prices diverge significantly from expected fair value. 77% accuracy on moneyline predictions when the divergence exceeds a threshold.
Two potential integrations:
- Market creation helper: suggest starting prices based on performance data
- Liquidity warning: flag markets where early prices look exploitable
Is this something the team has considered? Happy to share methodology.
Rodney
hello@rsrodai.org
Hey team,
Been looking at Zeitgeist for sports prediction markets. I noticed a gap most prediction market implementations have: no validation layer to check if initial market prices are reasonable before liquidity concentrates.
For sports markets specifically, this creates arbitrage opportunities for sophisticated traders who identify mispriced outcomes before the crowd corrects them.
I built a model using underlying team performance metrics (not historical results) that flags when market prices diverge significantly from expected fair value. 77% accuracy on moneyline predictions when the divergence exceeds a threshold.
Two potential integrations:
Is this something the team has considered? Happy to share methodology.
Rodney
hello@rsrodai.org