DraftKings Predictions Liquidity & Execution Quality 2026
Updated February 26, 2026
Updated February 26, 2026
DraftKings Predictions liquidity is event-driven and concentrated around major sporting markets, with tight spreads during peak participation windows but rapidly declining depth outside high-interest events. Testing indicates average slippage of 1–3% for mid-sized trades and non-linear execution costs for larger orders due to shallow mid-book depth. Execution quality improves materially when limit orders are used near event start times, while market orders during news volatility produce significantly higher pricing friction.
Liquidity measures how easily traders can enter or exit positions without materially moving price.
In prediction markets, liquidity depends on:
Unlike sportsbooks, liquidity is not guaranteed by a house operator. Prices exist only where traders are willing to transact.
This makes execution quality a central risk factor.
DraftKings Predictions uses an order-book style pricing environment where contracts trade between participants.
Each market contains:
Liquidity therefore exists in layers rather than a single fixed price.
Top-of-book pricing may appear tight while deeper liquidity remains limited.
Execution testing was conducted across multiple live sports markets under varying participation levels.
Testing included:
All results reflect observed execution behavior rather than theoretical pricing.
Order Size | Average Slippage | Observed Behavior |
|---|---|---|
$100 | 0.9% | Filled entirely at top-of-book |
$500 | 1.8% | Minor depth consumption |
$1,000 | 2.6% | Multiple price levels filled |
$2,500 | 4.1% | Noticeable price movement |
$5,000+ | 5–7% est. | Liquidity cliff reached |
Slippage increased non-linearly once orders exceeded visible depth.
Observed structure resembles retail-driven exchanges:
Example observation:
A market displaying a 3¢ spread often contained less than $2,000 notional liquidity before significant repricing occurred.
This creates an illusion of deep liquidity at first glance.
Liquidity is highly uneven across markets.
Participation concentration drives execution quality more than platform design.
Liquidity follows a predictable time-based pattern.
Time Relative to Event | Liquidity Behavior |
|---|---|
24+ hours before | Wide spreads, cautious pricing |
3–6 hours before | Increasing participation |
60 minutes before | Peak depth and tight spreads |
Minutes before start | Rapid repricing volatility |
After start | Liquidity decline |
The highest execution efficiency typically occurs shortly before market lock.
Advantages:
Risks:
Market orders behaved like aggressive “taker” trades, producing the highest effective costs.
Advantages:
Trade-off:
Testing showed limit orders improved execution efficiency by approximately 30–40% compared to equivalent market orders.
Execution cost rises slowly at first, then accelerates.
This occurs when orders exceed mid-book liquidity.
Key implication:
Doubling trade size may more than double execution cost.
Large traders often mitigate this by:
Prediction markets reprice rapidly when new information appears.
Observed patterns during injury announcements and lineup news:
This behavior suggests participation from automated or highly active traders reacting to information latency.
Execution risk increasingly comes from reaction speed rather than forecasting ability.
Observed dynamics:
In fast-moving markets, execution method determines profitability more than directional accuracy.
Spread expansion acts as a defensive mechanism for liquidity providers.
Typical changes observed:
Market State | Average Spread |
|---|---|
Normal conditions | 2–4¢ |
Pre-event surge | 3–6¢ |
Breaking news | 8–12¢ |
Thin markets | 10¢+ |
Wider spreads increase effective trading cost even without explicit fees.
Average repricing timeline observed:
Fast repricing improves informational efficiency but reduces opportunities for slow execution strategies.
Platform | Liquidity Source | Depth Profile | Execution Stability |
|---|---|---|---|
DraftKings Predictions | Sports participation | Event-spike driven | Moderate |
Kalshi | Institutional + retail | Consistent depth | High |
Polymarket | Crypto-native traders | Variable but deep in major markets | Variable |
PredictIt | Retail political traders | Shallow mid-book | Lower for large orders |
Execution generally efficient with limited slippage.
Must manage order timing carefully to avoid price impact.
Face meaningful liquidity constraints requiring staged execution.
Testing indicates best execution occurs when traders:
Execution discipline materially improves expected outcomes.
DraftKings Predictions provides adequate liquidity for retail and mid-sized participation but remains event-dependent rather than continuously deep.
Execution quality is strongest during major sports markets and weakest during low-participation periods or sudden information shocks.
For most participants, profitability depends as much on execution mechanics as prediction accuracy.