Faceoff Win Percentage Calculator

Faceoff Win Percentage Calculator

Face-offs won as a share of face-offs taken, for an ice hockey player or team — with what the published research says the statistic is actually worth, which is less than its prominence suggests.

Face-off win percentage

Wins ÷ draws taken
The NHL’s FOW. A face-off has exactly one winner, so a player’s wins and losses add to the draws they took.
The NHL’s FOL. Enter the losses rather than the total, because a scoresheet gives both and deriving one from the other hides a transcription error.
51.0%Example

2,364 face-offs won and 2,271 lost — the Detroit Red Wings’ 2025-26 NHL regular season

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Formula

Face-off win percentage = 100 × face-off wins ÷ (wins + losses)
FOW%
the NHL’s own definition: “Face-off win percentage is calculated as face-off wins divided by total face-off draws taken by a player or team”. The league states the same arithmetic for its situational versions as SH FOW/(SH FOW + SH FOL), which is why wins and losses are the two inputs here
the 50% line
the only fixed reference on this scale, and it is an identity rather than a benchmark. Every face-off has one winner, so across a whole league wins equal losses and the aggregate percentage is exactly 50%. A side above 50% is above average by definition and the question is only by how much it matters
what the research says it is worth
less than its prominence suggests. The SPORTLOGiQ study of 71,147 face-offs from 2017-18 reports “face-off win percentages are not well correlated to goals or wins” — “-1.8% and 0.03% correlated, respectively” in that season — and concludes that “players who generate the most value from face-offs do not necessarily have higher face-off win rates”
~75 face-off wins per goal
a figure the SPORTLOGiQ paper QUOTES rather than derives: “it takes on average ~75 face-off wins to achieve a +1 goal differential”, attributed there to Schuckers, Pasquali and Curro (2017). That source was not read for this page, so the figure is reported as a second-hand citation and is not built into the calculator
a clean win is not any win
the same study found clean offensive-zone wins “led to a shot event 38.6% of the time compared to 30.3% for non-clean ones”. That distinction is not in any public box score, so it cannot be computed here — which is part of why the headline percentage carries less information than it looks like it should
bounds
between 0 and 100, because a face-off is won or lost and there is no third outcome. Zero face-offs taken returns no value

Worked example

2,364 face-offs won and 2,271 lost — the Detroit Red Wings' 2025-26 NHL regular season
2,364 + 2,271 = 4,635 face-offs taken, which is the total the NHL publishes for Detroit in 2025-26
100 × 2,364 ÷ 4,635 = 51.0%. The league publishes 0.51003, and 2,364 ÷ 4,635 = 0.5100323
The NHL publishes the total and the percentage but not the win and loss counts, so 2,364 is the only whole number of wins that reproduces the published figure: 2,363 gives 0.50981 and 2,365 gives 0.51024
The win differential is 2,364 − 2,271 = 93, which is 46.5 wins above an even split across a whole 82-game season. On the second-hand figure of about 75 face-off wins to a goal, that is of the order of one goal of difference
It is a rate. Double both — 4,728 won and 4,542 lost — and the answer stays 51.0%. Halve the losses to 1,135.5 and it rises to 67.6%, which is what happens when the denominator halves while the numerator does not
Enter 0 won and 0 lost and the calculator returns no value: a player who has taken no draws has no percentage, and 0% would read as having lost all of them
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Five teams’ 2025-26 face-offs

Team, 2025-26 NHL regular seasonFace-offs takenFace-off win %Implied winsWin differential
Ottawa Senators4,61054.5112,513+416
Dallas Stars4,35951.5942,249+139
Detroit Red Wings4,63551.0032,364+93
Utah Mammoth4,71749.2472,323−71
Buffalo Sabres4,68245.8992,149−384
Totals and percentages are the NHL’s own published 2025-26 figures. The league does not publish the win counts, so the implied wins are the whole numbers that reproduce the published percentages, and the differentials follow from them. Note the spread: the best and worst teams in a 32-team league are about eight and a half percentage points apart, which over a season is 800 face-offs of difference and, on the second-hand ~75-wins-per-goal figure, perhaps ten goals.

What the published research found, and what it did not

FindingFigureWhere it comes from
Face-off win percentage against goals, 2017-18−1.8% correlatedSPORTLOGiQ, 71,147 face-offs from the 2017-18 NHL season
Face-off win percentage against wins, 2017-180.03% correlatedthe same paper, the same season
Clean offensive-zone win leading to a shot event38.6%, against 30.3% for a non-clean winthe same paper
Face-off wins needed for a +1 goal differentialabout 75quoted by that paper from Schuckers, Pasquali and Curro (2017), which was not read for this page
A rate per minute, or a value per draw by zonenot computable from a box scorethe zone and clean-win data are tracking data, published by nobody for free
The paper’s own tables arrived as captions only when it was read, so no figure here comes from one of them — every number above is from its prose. The last two rows are the honest limits of this page: the research that makes face-offs look valuable is about WHICH face-offs, and the distinction it rests on is not in any public statistic.

A percentage everyone quotes and nobody has shown to matter much

This page is about ice hockey — the game played with a puck on an ice rink, whose international rules are the IIHF’s and whose North American professional rules are the NHL’s own. It is not about field hockey, the eleven-a-side game on a turf pitch governed by the FIH, whose periods, set pieces and statistical definitions are different; this site keeps the two sports in separate sections for that reason.

A face-off is the puck drop that restarts play, and its winner is whichever side ends up with the puck. The arithmetic is the NHL’s own: “Face-off win percentage is calculated as face-off wins divided by total face-off draws taken by a player or team”. There is no third outcome, so wins and losses add to draws taken, the percentage is bounded between 0 and 100, and the two inputs here are the two columns a scoresheet gives.

The 50% line on that scale is an identity, not a benchmark. Every face-off won by one side is lost by the other, so across a whole league wins equal losses and the aggregate is exactly 50%. That makes the statistic easy to read — above 50 is above average, by construction — and it is also the reason the spread is narrow. In 2025-26 the best and worst teams in the NHL were about eight and a half percentage points apart, from Ottawa’s 54.5% to Buffalo’s 45.9%.

Then comes the awkward part, and it is the reason this page has a research table on it. The published work does not find face-off win percentage to be worth much. A SPORTLOGiQ study of 71,147 face-offs from the 2017-18 NHL season reports flatly that “face-off win percentages are not well correlated to goals or wins”, and that in that season “they were -1.8% and 0.03% correlated, respectively”. The same paper separates clean wins from scrambled ones and finds that a clean offensive-zone win “led to a shot event 38.6% of the time compared to 30.3% for non-clean ones”, and concludes that “players who generate the most value from face-offs do not necessarily have higher face-off win rates”. A frequently quoted figure of about 75 face-off wins for one goal of difference appears in that paper as a citation of Schuckers, Pasquali and Curro (2017) rather than as its own finding, and that source was not read for this page, so it is reported here as second-hand and is deliberately not built into the calculator.

What follows for a reader is modest and worth saying anyway. A face-off percentage is a real rate, correctly computed, and it is a poor single answer to the question of whether a centre is good. The distinction the research says matters — a clean win that produces a shot, in a zone where that shot is dangerous — rests on tracking data nobody publishes for free, so no public calculator can get at it. Where the puck goes after the draw is better approached through shot attempt share, and where the draw happened through the zone-start share the NHL publishes beside it. For the situations in which a face-off is most clearly worth something — the start of a power play or a penalty kill — the special-teams percentages are the figures that register the outcome.

Frequently asked questions

How do you calculate face-off win percentage?

Face-offs won divided by face-offs taken, times 100. The NHL’s definition is face-off wins divided by total face-off draws taken by a player or team. 2,364 won from 4,635 taken is 51.0%.

Why is the league average exactly 50%?

Because every face-off has one winner and one loser. Summed over a whole league, wins equal losses, so the aggregate percentage is 50% as a matter of arithmetic rather than as a finding. That is what makes the 50 line the only fixed reference on the scale.

How much does winning face-offs actually matter?

Less than its prominence suggests. A SPORTLOGiQ study of 71,147 face-offs from the 2017-18 NHL season reports that face-off win percentages “are not well correlated to goals or wins”, giving −1.8% and 0.03% for that season, and finds that the players who generate the most value from face-offs are not necessarily those with the highest win rates.

How many face-off wins are worth a goal?

A figure of about 75 is widely quoted. It appears in the SPORTLOGiQ paper as a citation of Schuckers, Pasquali and Curro (2017) rather than as that paper’s own estimate, and that original was not read for this page — so treat it as a second-hand number. This calculator deliberately does not convert your face-offs into goals using it.

What is a good face-off percentage?

This page prints no band, partly because nobody publishes a threshold and partly because the research does not support one. For scale, the 2025-26 NHL spread ran from about 54.5% to about 45.9% across 32 teams. Anything far outside that on a small number of draws is sample size, not skill.

What is a clean face-off win?

One where the winning side gains clear possession rather than scrambling for a loose puck. The distinction comes from tracking data and is not in any public box score, so it cannot be computed here. It matters: the SPORTLOGiQ study found a clean offensive-zone win led to a shot event 38.6% of the time against 30.3% for a non-clean one.

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References

  1. National Hockey League. NHL Stats Glossary, served as JSON at api.nhle.com/stats/rest/en/glossary (read 12 Oct 2026; 103,774 characters). The league’s own definitions and formulas, quoted verbatim wherever this site states one. nhl.com itself is robots-disallowed, and edge.nhl.com/en/glossary redirects to a page with no definitions on it.
  2. National Hockey League. Team face-off percentages, 2025-26 regular season, as JSON at api.nhle.com/stats/rest/en/team/faceoffpercentages (read 12 Oct 2026; 32 teams). Publishes totalFaceoffs and faceoffWinPct but not the win and loss counts, so the win count behind this page’s worked example is the unique integer that reproduces the published percentage.
  3. Czuzoj-Shulman N, Yu D, Boucher C, Bornn L, Javan M. “Winning Isn’t Everything: A contextual analysis of hockey face-offs.” SPORTLOGiQ, Montreal; arXiv:1902.02397 (read 12 Oct 2026). 71,147 face-offs from the 2017-18 NHL regular season, from proprietary tracking data. Its figure of “~75 face-off wins to achieve a +1 goal differential” is quoted from Schuckers, Pasquali and Curro (2017), which was NOT read for this page. The paper’s tables came through as captions only, so no table value is used here — every figure quoted is from its prose.