Not all YAC is the receiver. How tracking data models expected yards after catch and separation to credit the right player.
Published June 6, 2026 · NFL Analytics
Yards after catch (YAC) is one of the most satisfying numbers in football: it is the part of a reception where the receiver has the ball in his hands and is doing something with it - breaking a tackle, turning upfield, outrunning the defense. But raw YAC is also one of the most misleading box-score stats, because it credits the pass-catcher for yards that the scheme and the throw handed him.
Consider the two ends of the spectrum. A running back catches a checkdown five yards behind the line with no defender within ten yards - he is going to gain easy YAC simply because he caught the ball in open space. A slot receiver catches a contested ball over the middle with a safety draped on him - even an elite athlete gains little after that catch, because there is nowhere to go. Same statistic, completely different difficulty. Crediting both players' YAC equally tells you almost nothing about who is actually better with the ball in his hands.
The NFL's Next Gen Stats player-tracking system records the position, speed, and direction of every player roughly ten times per second. At the precise moment a receiver catches the ball, that tracking data describes the situation he is in. A model then asks a simple question: given this exact catch situation, how many yards would an average receiver gain afterward? That prediction is expected YAC.
The inputs are the things that make a catch easy or hard to turn into yardage:
| Situational input at the catch | Why it changes expected YAC |
|---|---|
| Nearest defender distance | A receiver wide open with separation has far more room to run than one caught in tight coverage. |
| Catch depth / air yards | Shallow catches (screens, checkdowns) happen in front of the defense with blockers ahead; deep catches usually happen with defenders converging. |
| Defenders between receiver and the end zone | The number and positioning of defenders in front sets how much open field is realistically available. |
| Field position and direction | Where on the field the catch happens, and which way the receiver is facing, shapes the running lane. |
| Receiver speed and momentum | A pass-catcher already moving upfield at speed is positioned to gain more than one catching flat-footed. |
Once the model produces an expected value for each catch, the rest is subtraction. YAC over expected is simply what actually happened minus what the situation predicted:
YACOE = Actual YAC − Expected YAC
Summed or averaged across a season, the formula generalizes to:
$$ \text{YACOE} = \sum_{i=1}^{n} \left( \text{YAC}_i - \mathbb{E}[\text{YAC}_i] \right) $$A positive YACOE means a receiver consistently gains more after the catch than the situation warranted - he is creating yardage. A negative YACOE means he is leaving yards on the field relative to the chances he is given.
The cleanest way to see why expected YAC matters is to hold raw YAC fixed and let the situation vary. The numbers below are invented to illustrate the concept - they are not real player stats.
Both players average 6.0 YAC per reception on the season. The box score would call them identical run-after-catch threats. Their catch situations were not:
YACOE is most powerful when you read it alongside the throw itself. As covered in our breakdown of air yards, aDOT, and YAC, every receiving yard is either an air yard (how far the ball traveled past the line to the target point) or a yard after the catch. Air yards belong to the throw and the route; YAC - and the skill inside it, YACOE - belongs to what happens next.
That gives you a clean division of labor across a single completion:
| Phase of the play | Metric | Mostly credits |
|---|---|---|
| Before / at the catch | Air yards, aDOT, separation | Quarterback's throw, route design, getting open |
| The throw's difficulty | CPOE | Quarterback accuracy on a tough target |
| After the catch | YAC, YACOE | Receiver's run-after-catch skill |
A receiver with a low aDOT but a strongly positive YACOE is a genuine YAC weapon - he is asked to do work in space and he beats the expectation. A receiver with a high aDOT and a near-zero YACOE is a downfield specialist whose value is in the catch, not the run after it. And on the throwing side, pairing YACOE with completion percentage over expected (CPOE) helps separate a quarterback who earns easy completions and easy YAC from one whose receivers are creating after contested catches.
Expected YAC is an estimate from a model, and different providers use different inputs and training data. Two sources can disagree on the same play, so stay within one system when you compare players.
A receiver who runs for YAC behind a great downfield block by a teammate gets credited for it. Some YACOE is really other players springing the runner, not the ball-carrier's own elusiveness.
A back used on screens will face easy catch situations all year; a deep threat rarely gets YAC chances at all. YACOE adjusts for difficulty, but a tiny sample of catches makes any per-reception rate noisy.
A high YACOE per catch on a handful of receptions is not the same as sustaining it across a heavy target load. Pair the per-catch skill with how often the player is actually used.
Raw YAC rewards receivers for the space a scheme and a throw hand them; YAC over expected fixes that by modeling how many yards an average player would gain from the same catch situation - defender proximity, catch depth, defenders in front, field position - and crediting the receiver only for what he adds on top (YACOE = actual YAC minus expected YAC). Read it as the after-the-catch companion to air yards and separation: air yards and the throw create the catch, separation describes how open the player got, and YACOE isolates the run-after-catch skill. Just remember it is model-dependent, that downfield blocking inflates it, and that role dictates how many YAC chances a player even sees - so treat it as one well-aimed piece of a receiver profile, not the whole picture.
Want the code behind these metrics? Work through the 45-chapter NFL analytics tutorial.
Browse tutorials Free tools