The big chance is a subjective stat
"Big chances missed" has become one of the most quoted lines in Premier League punditry. A striker goes through a cold spell, the graphic appears showing he has squandered the most big chances in the division, and the verdict writes itself: he is wasteful, profligate, not clinical enough. The number feels like hard data because it sits next to xG and pass completion in the same stat package. But a big chance is not a measurement the way a shot or a pass is. It is a label applied by a human analyst watching the match and deciding, in their judgment, that a player "should reasonably be expected to score." The stat is a subjective opinion formatted to look like a fact.
What the definition actually says
The standard data definition of a big chance is a situation where a player should reasonably be expected to score, usually in a one-on-one with the keeper or from very close range. Read that again: "should reasonably be expected." There is no coordinate threshold, no fixed expected-goals cutoff that triggers the flag automatically. A trained analyst makes the call live, the same way a basketball scorekeeper decides whether a pass earned an assist. That means the big chance inherits all the problems of any discretionary stat — inconsistency between analysts, drift over a season, and a boundary that moves depending on who is watching and how the move looked rather than what the geometry was.
It is a binary slapped onto a continuum
Expected goals exists precisely because scoring opportunities live on a continuum. A chance might be worth 0.18 or 0.34 or 0.61 expected goals, and the whole value of xG is that it refuses to round those into "chance" and "not a chance." The big chance throws that resolution away. It draws a line somewhere on the continuum and declares everything above it a big chance and everything below it not, with no gradation. A 0.40 xG header that gets flagged and a 0.75 xG open net that gets flagged count as the same event in the big-chances column, even though one was twice as likely to be scored. The binary discards exactly the information xG was built to preserve.
Double-counting with the model
Because a big chance is, definitionally, a high-xG opportunity, the two stats are not independent. When a broadcast shows a striker's xG and his big chances missed side by side as if they were two separate pieces of evidence, they are largely the same evidence counted twice. The big chances are a subset of the xG, re-expressed as a count. A player with high xG underperformance will almost by construction show up with big chances missed, because the missed high-value shots that dragged his goals below his xG are the same shots an analyst flagged as big chances. The two numbers nodding at each other is not corroboration. It is an echo.
Finishing variance is mostly noise
Underneath the "wasteful striker" narrative is an assumption that converting big chances is a stable, repeatable skill that separates clinical finishers from profligate ones. The evidence for that is weak. Finishing skill exists, but it is small relative to variance, and it takes a very large sample to detect. Over a ten or fifteen match window — the window pundits actually use — the gap between a striker scoring his big chances and missing them is dominated by chance, the bounce of the ball, a fingertip save, a defender's recovery. A player leading the league in big chances missed in November is frequently a player getting into excellent positions repeatedly, which is the hard part, and running cold on the easy part, which tends to correct.
The stat punishes the players doing it right
There is a perverse incentive buried in the criticism. To miss a big chance, a striker first has to generate a big chance, and generating high-value opportunities at volume is the single most valuable thing a forward does. A striker who takes only safe, low-pressure shots will never top the big-chances-missed table, and will also never score twenty goals. The player getting pilloried for his misses is often the same player whose underlying numbers are excellent, because he keeps arriving in the six-yard box. Judging him on the conversion of a noisy, subjectively-flagged subset of his chances penalizes the exact behavior a manager wants more of.
Analyst-to-analyst inconsistency
Because the flag is a judgment call, who is making it matters. Different data providers staff different analysts, apply slightly different internal guidance, and update their conventions over time, which means the same passage of play can be a big chance in one feed and an ordinary chance in another. For a stat that gets quoted to the decimal in transfer debates and end-of-season awards arguments, that inconsistency is rarely disclosed. A striker's big-chances-missed total is partly a statement about the player and partly a statement about how aggressively a particular provider's analysts were flagging chances that season. The reader sees only the count and assumes it came off a fixed measuring stick.
Compare that to a shot or a touch, events with hard physical triggers that any two analysts will log identically. The big chance has no such anchor, so it cannot be audited the way an objective event can. When a number cannot be reproduced from the footage without a human deciding what "should reasonably be expected" means, it belongs in the category of informed opinion, however useful that opinion is. Treating it as interchangeable with the objective parts of the data package is the mistake the broadcast graphic quietly invites every weekend.
It is worth being precise about what would make finishing a reliable skill worth grading. You would need a striker to out-convert his expected goals by a meaningful margin across hundreds of chances, sustained over multiple seasons, with the edge holding as he changes teams and service. A handful of elite finishers clear that bar. The vast majority of players who top a big-chances-missed table in any given month do not, and will quietly converge back toward the expected rate as the sample grows. The table is a snapshot of a noisy process caught at a bad moment, dressed up as a character flaw.
The honest read
Treat big chances as a useful piece of color commentary, not as a finishing grade. The stat captures something real — this player got into good positions and did not score — but the flag is a human judgment, the binary throws away the gradation xG keeps, and the count largely repeats information already in the xG line. Before you call a striker wasteful, look at whether the underperformance is large enough and sustained over enough shots to be more than variance, and lean on the continuous expected- goals figure rather than the rounded count of chances someone decided were big. A cold finishing run inside a strong chance- creation profile is usually the most encouraging signal a striker can give, even as the broadcast graphic insists it is the most damning.