What if the airdrop distribution in the prediction market doesn't just consider trading volume, but also assigns significant weight to PNL (profit and loss)? Logically, this approach makes sense.

The core demand from project teams is quite clear—distinguishing between arbitrageurs and market makers. Those who make money are mostly genuine market makers and core users. Small hedging and repeated order placements belong to regular accounts. Accounts that are long-term losing and keep struggling are likely engaging in hedging arbitrage. Using PNL to quantify user quality can effectively isolate cheating behaviors.

Moreover, prediction markets are essentially Order Book models, where profitable users naturally contribute more. Conversely, rewarding solely based on trading volume can easily encourage machine-driven order spamming.