Since electronic trading exchanges have different possible models for matching algorithms, such as FIFO and pro-rata, if a trading strategy's performance depends on having a good place in the line, that is, other market participants' sizes ahead of the strategy's orders at the same price level, then it is important to accurately simulate that. In general, if the backtester is too optimistic in estimating a trading strategy's order's priority in the limit order book as compared to the rest of the market participants, that is, it assumes our order is ahead of more market participants than it actually is in live markets, this leads to false and inflated expectations of trading strategy performance.

When such trading strategies are deployed to a live market, they often do not realize the expected simulated trading performance, which can hurt the trading strategy profitability. Modeling an accurate place in line is often a difficult problem and requires a lot of research and careful software development to get correct.