Slippage in crypto trades, how to measure it, set limits, and avoid bad fills

You press buy, you see a price, and you still don’t get that price. It feels like the market “moved on purpose”, but usually it’s just crypto slippage doing what it does when liquidity is thin, spreads are wide, or your order is too big for the moment. Slippage is not only a DeFi thing, and not only a market-order thing. It shows up on CEXs with partial fills, and on DEXs with AMM price impact, and (when you’re unlucky) with MEV bots pushing you into a worse execution. This guide keeps it practical: how to measure slippage, how to set slippage limits, and how to reduce bad fills without creating new problems like failed orders or reverted swaps. TL;DR (quick checklist) Slippage = expected price vs executed price, measured on your real average fill (not one print). Track it in bps so it’s comparable: 1% = 100 bps. On CEXs, avoid surprise fills by using limit orders, checking order book depth, and avoiding low-liquidity pairs. On DEXs, separate slippage tolerance (your max) from price impact (pool math), and respect MEV/sandwich risk. Start with conservative tolerances for majors, increase only when the trade would otherwise fail (and you accept the risk). Too-tight settings can cause expired limit orders or reverted swaps, sometimes with extra fees (gas, priority fees, retry costs). This is not financial advice, it’s execution hygiene. What slippage is (and what it isn’t) In plain words, slippage is the gap between the price you think you will trade at, and the price you actually trade at. The generic finance definition is similar, and if you want the broader background outside crypto, Investopedia’s explanation helps: https://www.investopedia.com/terms/s/slippage.asp Slippage is not always “bad behavior”. Some slippage is normal when: Spread widens (the best bid and best ask are far apart). Liquidity is shallow (few coins available near the current price). Volatility jumps (news candles, liquidations, thin weekend books). Your order is large relative to the market at that moment. On DEXs, slippage also gets mixed with price impact, which is the AMM curve moving against you as your swap size pushes the pool price. Visual: why a market order slips Order book levels getting “eaten” creates an average fill price, this illustration was created with AI. How to measure slippage (expected vs executed, average fill, bps) To measure slippage, you need two numbers: 1) Expected price (P_expected)This is your reference price at the time you decided to trade. Common choices: Last traded price (easy, but noisy). Best ask for a buy, best bid for a sell (more realistic). Quote price shown on your swap preview (DEX UI quote). 2) Executed average price (P_exec_avg)If you got multiple partial fills, do not guess. Compute the weighted average: P_exec_avg = (Σ(price_i × qty_i)) / (Σ(qty_i)) Then your slippage percent is: Slippage % = ((P_exec_avg − P_expected) / P_expected) × 100% For sells, the sign flips (you usually get a lower price), but many traders track it as an absolute cost. Convert slippage into basis points (bps) bps makes logs clean across tokens and price levels: 1% = 100 bps 0.10% = 10 bps Slippage bps = Slippage % × 100 A quick example with partial fills You place a market buy expecting 100.00. You get filled: 0.4 at 100.20 0.6 at 100.90 P_exec_avg = (0.4×100.20 + 0.6×100.90) / 1.0 = 100.62Slippage % = (100.62 − 100.00) / 100.00 × 100% = 0.62%Slippage = 62 bps That 62 bps is the “quiet fee” you paid, on top of explicit trading fees. CEX slippage control: limits, depth checks, and timing On centralized exchanges, slippage mostly comes from crossing the spread and walking the order book (market orders do this by design). The fixes are not fancy, but they work when you actually apply them. Use limit orders for price certaintyA limit order can still partially fill, but it won’t fill at worse than your limit. If you want more control, “post-only” (maker) settings can help, but remember it can also reduce fill rate. Read the order book depth (not only the top price)Before you trade size, look at how much liquidity is within 5 bps, 10 bps, 25 bps. If depth is thin, your “small” order may not be small. Avoid low-liquidity pairs when execution mattersMajors and top stable pairs usually have tighter spreads. Long-tail pairs can have sudden gaps, and then even a modest market order becomes a ladder climb. Be careful around news and scheduled eventsRate decisions, ETF headlines, big unlocks, or exchange listing rumors can widen spreads fast. If you must trade in that time, reduce size or split orders. Maker vs taker is not only feesTaker fills are instant, but you pay spread and you may get slippage. Maker fills can reduce cost, but you take “won’t fill” risk. Your best setting depends on whether execution certainty or price certainty is your priority. DEX slippage tolerance: price impact, MEV, and when higher tolerance is OK On AMMs, you often set a slippage tolerance like 0.5% or 1%. This number is your maximum acceptable move from the quoted price before the swap reverts. Here is the confusing part: slippage tolerance is not the same as price impact. Price impact is the pool curve changing as you trade. Tolerance is your allowed downside if the quote becomes worse before inclusion. MEV and sandwich risk (2025 reality)If your transaction is public in the mempool and your tolerance is loose, bots can front-run, move price, and back-run, and you become the sandwich filling. This is more common on volatile pairs and thin pools. Use aggregators when routing helpsAggregators can split across pools and routes, sometimes giving less price impact than one pool. For a practical overview on slippage tolerance thinking (from a market making angle), see: https://kaironlabs.com/blog/crypto-market-making-101-what-is-slippage-and-slippage-tolerance Consider private submission or MEV protection where availableSome wallets and RPC routes support private transaction paths or MEV protection modes. It doesn’t guarantee perfection, but it can reduce the “broadcast my tolerance to everyone” problem. Safety note on tight tolerancesIf you set tolerance too tight, your swap can revert, and on many chains you still pay gas. In busy periods, repeated retries can become its own cost, so you are not “saving money”, you are paying a different bill. For extra practical ways to reduce slippage (in simple terms), this 2025 overview is useful: https://bitcoin.tax/blog/crypto-slippage/ Default starting ranges for slippage tolerance (majors vs long-tail) These are starting points, not promises. Your correct number depends on liquidity, volatility, and how urgent your execution is. Trade type CEX approach DEX slippage tolerance (starting range) Major pairs (BTC, ETH vs deep stables) Prefer limit, size-aware 0.1% to 0.5% Mid-cap with decent liquidity Limit or split orders 0.5% to 1.5% Long-tail, memecoins, thin pools Small size only, avoid market 2% to 5% (sometimes more, with high risk) A higher tolerance can be justified when the alternative is constant failure (fast-moving launch, thin liquidity, chain congestion). But you should treat that as paying for urgency, and also accepting MEV exposure. If you want a broader DeFi context on AMM liquidity and slippage behavior across big DEXs, this internal comparison can help your intuition: Uniswap vs SushiSwap slippage comparison Monitor the signals that predict bad fills (and track your own slippage) Slippage usually announces itself before it hits you. Watch these four metrics: Spread: wider spread means you pay more just to enter. Depth: thin depth means your size moves price faster. Volatility: higher volatility means quotes get stale quickly. Volume: low volume often means fragile liquidity. For personal tracking, keep it boring and consistent: export your CEX fills, calculate average execution vs your chosen expected price at order time, then log slippage in bps. On DEXs, save the quote and the final execution from the transaction details, then compare. After 30 to 100 trades, you’ll see patterns (certain hours, certain pairs, certain sizes) and you can adjust. Conclusion Slippage is not a mystery tax, it’s a measurable execution cost. When you track crypto slippage in bps, you stop guessing, and you start making small rule changes that protect you in the messy moments. Use limits on CEXs, respect price impact and MEV on DEXs, and don’t set tolerances so tight that you bleed on failed trades and extra fees. This is not financial advice, but it is the kind of routine that keeps your fills more fair when the market is acting wild.