When you make an in-play bet on a decentralized sportsbook or an oracle-based prediction market, it is reasonable to expect that the odds displayed to you are accurate representations of supply and demand. However, the reality is often far from the truth because every single blockchain transaction is impacted by a phenomenon known as Miner Extractable Value (MEV). Its numerous forms include the particularly malignant “sandwich attack,” in which a malicious searcher or block producer can capture the on-chain price feed and front-run and back-run your bet to turn live odds against you. This article will detail how MEV sandwich attacks function, how they affect live betting odds, and what measures both platforms, and bettors can take to defend against foul play.
What is a Sandwich Attack in Terms of MEV?
MEV stands for the value that may be captured by block producers (miners or validators) and some specialized searchers through transaction inclusion, exclusion, or reordering. A sandwich attack is a traditional MEV tactic that was first spotted in decentralized exchanges. Searchers make a lot of money off the outbound trades that have been set up in the mempool. These trades consist of a large swap leveraged trade as well as a smaller front-run trade that is priced higher than the smaller swap or push payment. In front-running transactions of multi- swap processes, searchers earn profit from all direction trades by exploiting spread between token price movements from buy and sell sides both pre-execution and post-execution.
For live betting, think of a prediction market contract that creates Yes/No shares from oracle prices as its value changes. When there’s a favorable implied probability, you place a large buy-Yes transaction. A sandwich attacker front-runs by buying Yes-shares at the pre-bet price—the lower pre-bid price—and driving up the cost for them to sell back their Yes-shares into the pool at the now-elevated price. They let your bet execute at worse ‘odds’ for you (higher payout), so they can take the delta, profit, and you’ll lose that payoff. Streamlined, that means for you, the outcome cost that you will need to back for rises by a few basis points for the attacker to profit directly of you losing.
How Sandwich Attacks Skew Live Odds
The return on investment for a parlay combination or high variance play in live betting decreases with a small shift in odds. Because sandwich attacks exploit the mechanism that adjusts the odds—the on-chain price update—there are loses artificial volatility when the odds count the most. Concrete examples will convey the effect better:
Slimming Favorite Margins: Let’s say you’re backing a heavy favorite at 1.02× on a large stablecoin pool. Odds suggest you will get a yield more than 1 dollar for every 1 dollar wagered per payout. You will have to lock in at 1.015x, hence you lose almost all of your edge due to a sandwich front-run.
Undercutting Underdog Bets: Now, back an underdog to win at odds of 5×. The attacker can raise the implied probability fractionally – in this case, from 20% to 20.3%. This would reduce the payout to 4.93×. In the long run, these micro-adjustments accumulate towards a significant change in your win-to loss ratio.
Parlay Cascades: When betting in parlays where the odds multiply across legs, a small shift in odds at each selection is magnified into a large drop in overall payout. Sandwich sybil attacks targeting the bigger parlays could shave upwards of 1–2% off your potential return without you ever noticing, unless you audit each on-chain receipt.
As sandwich attackers pay higher gas fees to secure inclusion into block priority, they are able to perform these tactics before or after your bet, within a single block span. The outcome is that the live odds on-chain are less a reflection of sentiment from bettors and more a medium for profit made by searchers.
Research Highlights and Real World Examples
Researchers from both academia and industries have recorded numerous cases of sandwich attacks on all major DeFi protocols, estimating that MEV bots reduce the profits of liquidity providers by, on average, 50%. An early-stage study within the betting domain reveals similar results as well. An investigation into a decentralized soccer betting market found that 28% of large in play bets (greater than 10,000 USD) were sandwich-attacked at least once, reducing the bettor’s odds by an average of 0.8%. In another report done on a prediction market that settles off the chain, it was noted that 15% of bets placed with high-velocity accepted front-run and back-run transactions which resulted in disproportionate bias against slower manual bettors.
These results confirm that sandwich attacks are not mere theoretical scenarios, but rather an imminent danger in environments that feature real-time odds, instant capital allocation, and price feed oracle systems. As the adoption of automated market makers and decentralized betting increases, the level of competition among MEV searchers trying to exploit predictable bet-flow patterns will become fiercer.
Supporting Strategies for Managed and Fair Gameplay
Both platforms and bettors face some degree of sandwich-driven odds exploitation, but some strategies can equally be adopted by all parties involved in the game.
Commit–Reveal Schemes: These are a two-phase processes wherein users first bet on a hash and then reveal the stake after a block is confirmed. By doing so, they hide the pending wagers from being exposed to the mempool and preventing searchers from being able to sandwich-attack.
Batch Auctions & Time-Windows: Grouping bets into fixed time windows where all bets are executed at once and all at a single clearing price ensures there is no individual transaction price exploitation that would allow for reactionary measures and ensures price realization fairness.
Private Mempools or Threshold Encryption: Using transaction concealment mechanisms such as those provided by Flashbots through private RPC nodes or encrypted order books shielding details of the bets until after they are placed in a block, eliminates the chances of frontrunning.
Dynamic Gas Price Floors: Shifting bet execution gas prices up or down attached to a floor creates limits for the attacker’s ability to suffocate genuine bettors, though this does not completely eliminate MEV.
Layer-2 Settlement with Batch-Finality: Bundling multiple bets together and moving them from Layer 1 to Layer 2 and then settling them as a single transaction onto Layer 1 marks the impact miner level rerouting can have. This method only works if the rollup operator resists the temptation to MEV manipulate.
While not many bettors may be willing to change their behavior, taking an interest in setting limit orders on betting contracts, splitting large bets into many small transactions, syndicating real-time on-chain monitoring for unsolicited sandwich strategies can exercise some level of control. While these strategies do not offer full protection, they raise the level of effort required by adversaries and tout for fair odds.
MEV-Resistant Betting Protocols: Moving Forward
The entire DeFi ecosystem is in a frenzy trying to develop MEV-resistant schemes, from fair-ordering relays like MEV-Boost to threshold-encrypted mempool cryptography and zero-knowledge mixnets. We will look forward to next generation betting platforms incorporating these technologies natively as fair live odds devoid of sandwich slippage will truly be a feast. In the meantime, using MEV sandwiches on a competitive field where slippage is a problem is detrimental and understanding how they function alongside appropriate defenses on protocols will be essential for any bettor that seeks fairness.
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