Average Fishing Guide Day Rates by State
Builds guide sites for a livingPublished July 23, 2026Last updated July 26, 202639 min read
- The 2018 SOC contains 867 detailed occupations, 459 broad occupations, 98 minor groups and 23 major groups, and every federal agency publishing occupational data must use it.
- Resolution is decided centrally, so a trade without its own detailed code is absorbed into a broader category and cannot be reported separately.
- A day rate is a price with fuel, shuttle, insurance, gear and permits inside it, not an earnings figure, so the two are not comparable even where both exist.
- Variation within a state routinely exceeds variation between states, so a state average reports the wrong variable.
- Research the five to fifteen operations a client on your water would genuinely compare you with, annually, and date what you find.
- Treat platform listings as a description of operations with capacity to fill rather than as the market.
Every federal agency publishing occupational data is required to use one classification system, and that system carries 867 detailed occupations. Whether a trade appears in a published wage statistic depends entirely on whether it has one of those 867 codes to itself.
Which is the mechanical reason there is no reliable state-by-state figure for what a fishing guide charges, and it is a better reason than anybody usually gives. The classification decides the resolution, and the resolution decides what can be reported. There is a second reason underneath it, which is that a day rate is a price rather than a wage, and the two are different measurements of different things. No average day rate is asserted anywhere on this page. Related material is indexed at the guide industry data hub.
| Level | Count in the 2018 structure |
|---|---|
| Major groups | 23 |
| Minor groups | 98 |
| Broad occupations | 459 |
| Detailed occupations | 867 |
What does the classification actually do?
Fixes the resolution of every federal occupational statistic at once.
The Office of Management and Budget announced its final decision for the 2018 revision of Statistical Policy Directive No. 10, the Standard Occupational Classification, in a notice published at 82 FR 56271 on 28 November 2017.
The notice states that the classification covers all occupations for which work is performed for pay or profit, covering all jobs in the national economy including the public, private and military sectors, and that all federal agencies publishing occupational data for statistical purposes are required to use it.
It records that the 2018 structure contains 867 detailed occupations, aggregated into 459 broad occupations, combined into 98 minor groups and 23 major groups.
And it notes that the classification was designed and developed solely for statistical purposes, with readers interested in non-statistical uses directed to the relevant agency.
The notice is on the Federal Register.
Why the absence of data is structural rather than accidental is set out in the methodology piece.
Why does the resolution matter so much?
Because a trade without its own code cannot be reported separately.
867 detailed occupations is a fine-grained system by most standards and it is nowhere near fine enough to isolate every trade somebody works in.
Which means a great many occupations are absorbed into broader categories, and a wage figure published for such a category describes the mixture rather than any of its parts.
The consequence for anybody looking for a guiding figure is that the number they find, if they find one, is a figure about a wider grouping.
The specific coding treatment of guiding occupations could not be confirmed for this page, because the classification manual itself sits on a site that would not serve a request, and it is not quoted here on that account.
What can be said from the notice alone is the structural point: resolution is decided centrally, and no agency can publish below it.
How to read any figure that does appear is set out in the methodology piece.
Why a state average would mislead even if it existed. Imagine a state with 300 operations, of which 200 run half-day inshore trips at $450 and 100 run full-day float trips at $750. The arithmetic mean is $550, which is a price nobody charges and which describes neither group. Splitting by trip type gives two useful numbers and splitting by state gives one useless one. Every figure here is a stated assumption used to show the structure, not a measurement of any state.
Is a day rate even a wage?
No, and this is the second reason the search fails.
Occupational wage statistics measure what workers are paid, which for an employee is a wage and for a self-employed operator is not a published quantity at all.
A guide's day rate is a price charged to a client, out of which come fuel, shuttle, insurance, gear, permits and the operator's own return.
Which means the two numbers are not comparable even where both exist, and treating a day rate as an earnings figure overstates income substantially.
The distinction matters practically for anybody comparing guiding to a salaried alternative, since the correct comparison is against the residual after costs rather than against the rate.
Which is precisely what the model in the income piece computes and precisely what no published figure supplies.
That calculation is set out in the income model piece.
No day rate figure is given here, for any state. Nothing of the kind was found in any source consulted, nothing has been estimated from adjacent categories, and no range has been offered as a compromise. The classification notice described sets the structure of federal occupational statistics and says nothing about guiding rates. The coding treatment of guiding occupations was not confirmed and is not asserted. Nothing on this page is financial or statistical advice.
What actually sets a rate on a given water?
Four things, and none of them is the state line.
The scarcity of access, since water requiring a permit, a boat or local knowledge supports a higher rate than water anybody can walk to.
The travel a client has already committed, because somebody who flew in and booked a lodge is price-insensitive relative to somebody driving forty minutes.
The length and difficulty of the day, which is the only one guides usually adjust and the one clients understand best.
And the operator's own position, meaning how booked they are, which is the variable that moves rates most and is invisible to everybody outside.
All four operate at the level of a fishery and an operation, which is why a figure aggregated to a state is measuring across them rather than within.
Any of the four can be assessed locally in an afternoon, and none can be looked up.
Which is the practical answer to the question the search was really asking.
Does the season length change the picture?
Considerably, and it works against the intuitive reading.
An operation with a ten-week window has to recover its annual fixed costs across far fewer days than one working nine months, which pushes the required rate up.
Which means a short-season fishery can support and require higher day rates than a longer one, independently of anything about the fishing.
Comparing a rate in a short-season state to one in a year-round state without adjusting for that is comparing two different cost structures and concluding something about demand.
The same effect appears within a state wherever a high-country fishery and a valley fishery sit in the same jurisdiction.
Which is another way of saying that the state is not the unit of analysis, and that any table organised by state is organised by the wrong variable.
Working out your own required rate from your own fixed base and your own realistic day count is the calculation that replaces it.
That calculation is set out in the income model piece.
What about historical figures?
Useful only where they are dated, and almost none are.
A rate figure from several years ago would be genuinely informative if it were labelled, because the direction of movement is worth knowing.
What circulates instead is undated figures that were probably accurate at some point and are quoted as current, which is worse than no figure.
The specific danger is a guide anchoring their own pricing on a number that predates several years of cost movement, and concluding they are already expensive.
Which is a real and common way operations end up underpriced for years without anybody making a decision.
The correction is to date every figure you rely on, including your own from previous seasons, and to distrust anything undated regardless of source.
Where a page carries no date at all, that is itself the answer to the question of how seriously to take it.
The rate review this belongs to is set out in the raising rates piece.
Is there any figure worth quoting to a client?
Your own, and only about what is included.
Clients comparing operations are rarely comparing rates in isolation; they are trying to work out what the day involves and what it comes with.
Which means the useful number to publish is not a rate in a market context but a complete statement of what the rate buys, itemised.
An operation whose page lists the hours, the water, the gear, the food and the transport has answered the comparison question without ever mentioning anybody else.
Which converts a price comparison into a value comparison, and it is the only move available to an operation that is not the cheapest.
Quoting an industry average to justify your own rate has the opposite effect, since it invites the client to go and check.
Nobody has ever booked a trip because a guide cited a statistic.
What the page should contain instead is set out in the booking page piece.
What varies within a state?
More than varies between states, which inverts the whole question.
Two guides on the same river, in the same week, running the same length of day, frequently charge materially different amounts, and the difference reflects experience, demand and positioning rather than geography.
Which means a state average conceals the variation that actually matters and reports the one that does not.
The variation that does track geography is cost rather than price, since fuel, insurance, permits and the cost of living differ by region in ways that are real.
But cost differences are smaller than the within-state price spread in most markets, so a state figure is dominated by the noise it was supposed to remove.
The comparison a guide actually needs is against the two or three operations a prospective client would consider alongside them, which is a handful of websites rather than a statistic.
That comparison takes twenty minutes and produces something a state average never could.
How to price against it is set out in the pricing piece.
How should a guide research their own market?
By looking at the operations a client would actually compare you with.
List the operations that appear when somebody searches for a guide on your water, which is between five and fifteen in most markets.
Record what each publishes for a comparable day, what is included, and what is not, which takes an afternoon once a year.
Which produces a genuine local picture with a known population, a known count and a known date, satisfying the three questions that no published average can.
What it does not tell you is what those operations actually receive, since published rates and realised rates differ everywhere, and the gap is invisible from outside.
Which is a real limitation and it is a much smaller one than any state average carries.
Repeating it annually turns it into a series, and the direction of local pricing is more useful than the level.
The realised-rate distinction is set out in the income model piece.
What about platform listings?
A genuine sample of one population, and a biased one for this purpose.
Booking platforms list large numbers of operations with prices attached, which is the closest thing to a rate data set that exists.
What it describes is operations that chose to list, which skews towards those with capacity to fill and away from those booked out on direct business.
Which biases the visible rates downward relative to the market, and the bias is largest in exactly the fisheries where the best operations never list at all.
It also captures the listed price rather than the realised one, and platform pricing frequently carries promotional structures that do not appear in the headline.
None of which makes the listings useless; it makes them a description of the listing population, which is the same conclusion every page in this cluster reaches.
Reading them with the population named is the whole discipline.
The platform question generally is examined in the channel share piece.
Why does the figure keep getting published anyway?
Because a table of states is an irresistible format.
A page with fifty rows and a dollar figure in each is easy to produce, easy to rank and easy to link to, and it satisfies a search that people genuinely perform.
Which is why such pages exist in quantity and why almost none of them names a population, a count or a date.
Tracing any of those figures usually terminates in a platform's listings, a handful of phone calls, or another table.
The test worth applying is the same as everywhere else: who was asked, how many answered, and when.
Where a page cannot answer those, the fifty numbers are fifty impressions arranged in a grid.
Which is not a criticism of anybody's honesty; it is a description of what the format rewards.
The test itself is set out in the methodology piece.
What would a useful state page contain?
Costs rather than prices, because costs are knowable.
The genuinely state-specific facts about guiding are licensing requirements, permit costs, insurance requirements and access rules, all of which are published by state agencies and all of which are checkable.
Which are the things a person actually needs when deciding whether to operate somewhere, and they are available where the rate figure is not.
A page giving those, sourced to the agency and dated, would be more useful than any table of averages and is considerably more work to produce.
Confirm the current requirements and fees directly with the relevant state agency in any case, since both change and neither is reliably reported second-hand.
The rate question then becomes a local research exercise rather than a lookup, which is the honest shape of it.
What those requirements involve is set out in the licence requirements piece.
Why is the direct match file interesting?
Because it shows how job titles get resolved into codes.
The classification notice describes a Direct Match Title File, introduced in the 2010 revision and updated for 2018, listing job titles that map one-to-one to a single detailed occupation.
Which is the mechanism by which what somebody calls themselves becomes what they are counted as, and it is where the resolution problem becomes concrete.
A title that does not appear on such a list has to be assigned by judgment to whichever detailed occupation fits best, and the fit for an unusual trade is frequently loose.
That assignment is invisible in any published figure, and it is a substantial part of why occupational statistics for small or hybrid trades behave oddly.
Anybody wanting to know how a particular title is treated has to consult the classification materials directly, which this page did not manage to retrieve.
Which is stated rather than papered over, because the alternative would be to guess at the very thing the page is about.
What should a reader take away?
That the absence is structural, and that the substitute is local and cheap.
The figure does not exist because the machinery that would produce it operates at a resolution that does not reach this trade, and because a day rate is not the quantity that machinery measures.
Which means no amount of searching will surface it, and every page that appears to have it is doing something else.
The substitute is an afternoon a year looking at the operations a client would genuinely compare you with, which produces something better than the statistic would have been.
Better because it has a named population, a known count and a date, and because it describes the comparison the client is actually making.
Nobody publishes it because it is worthless to anybody but you, which is precisely why it is worth doing.
What to do with the answer is a pricing decision rather than a research one.
Where does the search go wrong?
Six ways, and looking for a state average is the first.
Seeking a figure at a geographic resolution that conceals the variation that matters.
Treating a day rate as an earnings figure, when it is a price with costs inside it.
Reading a platform's listings as the market, when they describe operations with capacity to fill.
Accepting a table whose numbers cannot answer who, how many and when.
Comparing against operations a client would never consider alongside you.
And using a figure without a date, in a period when costs have moved sharply.
The pricing decision it should inform is set out in the pricing piece.
What is the working approach?
Local research, annually, and no average at all.
Accept that no defensible state figure exists and stop looking, because the format that promises one cannot deliver it.
List the five to fifteen operations a client on your water would genuinely compare you with, and record what each publishes and what it includes.
Repeat it once a year so the local picture becomes a series, and read direction rather than level.
Treat platform listings as a description of operations with capacity to fill rather than as the market.
Never treat a day rate as income, since the residual after costs is a different and much smaller number.
For anything genuinely state-specific, go to the state agency, and date what you find.
The classification authority is 44 U.S.C. 3504, and the notice is mirrored on govinfo.
The residual calculation is set out in the income model piece.
How this was checked. The classification facts come from the Office of Management and Budget notice, Standard Occupational Classification (SOC) System, Revision for 2018, published at 82 FR 56271 on 28 November 2017 and retrieved from the Federal Register on 26 July 2026. The notice announces OMB's final decision for the 2018 revision of Statistical Policy Directive No. 10; states that federal statistical agencies will begin using the 2018 SOC for occupational data published for reference years beginning on or after 1 January 2018; states that the 2018 SOC was designed and developed solely for statistical purposes and directs readers interested in effective dates for non-statistical purposes to the relevant agency; cites 31 U.S.C. 1104(d) and 44 U.S.C. 3504(e) as authority; states that the SOC classifies all occupations for which work is performed for pay or profit, covering all jobs in the national economy including the public, private and military sectors, and that all federal agencies that publish occupational data for statistical purposes are required to use it; records that compared to the 2010 SOC the 2018 revision realised a net gain of 27 detailed occupations and one minor group, that the net number of broad occupations fell by two and the number of major groups was unchanged, that the 2018 structure contains 867 detailed occupations aggregated into 459 broad occupations combined into 98 minor groups and 23 major groups, that 472 detailed occupations remained unchanged from 2010 and seventy are new; records that the SOC has been revised four times since its inception, in 1980, 2000, 2010 and 2018; describes the Direct Match Title File introduced in the 2010 SOC, listing job titles that map one-to-one to a single detailed occupation; and records that the revision process was initiated by a notice at 79 FR 29620 on 22 May 2014 and involved two requests for public comment reviewed by the SOC Policy Committee through eight workgroups. The SOC Manual itself and the classification's treatment of guiding occupations were not retrieved, because the site hosting them did not serve the request, and nothing about that treatment is asserted here. No average day rate, range or typical figure for guided fishing is asserted anywhere on this page, for any state; none was found in any source consulted, none has been estimated from adjacent categories, and none is offered as a compromise. The figures in the arithmetic panel are stated illustrative assumptions used to demonstrate a structure. Licensing requirements, permit costs and access rules vary by state, were not researched here, and should be confirmed with the relevant state agency. Nothing on this page is financial or statistical advice.
If your booking calendar has more open weeks than you’d like, I’ll build you a free preview of your booking site before you pay a cent.
Get a free website previewWhy the figure does not exist, why a day rate is not a wage, and what to research instead
Why is there no state figure?
Because the classification decides the resolution of every federal occupational statistic at once. The OMB notice at 82 FR 56271 records that the 2018 Standard Occupational Classification contains 867 detailed occupations covering all jobs in the national economy, and that all federal agencies publishing occupational data for statistical purposes are required to use it. A trade without its own detailed code is absorbed into a broader category, and no agency can publish below the resolution.
Is a day rate a wage?
No, and this is the second reason the search fails. Occupational wage statistics measure what workers are paid. A day rate is a price charged to a client, out of which come fuel, shuttle, insurance, gear, permits and the operator's own return. Treating it as an earnings figure overstates income substantially, and the correct comparison against a salaried alternative is the residual after costs.
What varies within a state?
More than varies between states. Two guides on the same water in the same week charge materially differently, reflecting experience, demand and positioning rather than geography. What does track geography is cost, being fuel, insurance, permits and living costs, and those differences are usually smaller than the within-state price spread. A state figure is dominated by the noise it was meant to remove.
What sets a rate on a given water?
Four things, none of them a state line. The scarcity of access, since permitted or boat-only water supports more than water anybody can walk to. The travel the client already committed, since somebody who flew in is less price-sensitive. The length and difficulty of the day. And how booked the operator already is, which moves rates most and is invisible from outside.
How should a guide research their market?
List the five to fifteen operations that appear when somebody searches for a guide on your water, and record what each publishes for a comparable day, what is included and what is not. That produces a local picture with a named population, a known count and a date, which is exactly what no published average has. Repeat it annually so it becomes a series, and read direction rather than level.
What about platform listings?
A genuine sample of one population and a biased one for this purpose. They describe operations that chose to list, which skews towards those with capacity to fill and away from those booked out on direct business, so visible rates run low relative to the market. They also capture listed rather than realised prices. Useful once the population is named, misleading when read as the market.
Does season length matter?
Considerably, and against the intuitive reading. An operation with a ten-week window recovers its annual fixed costs across far fewer days than one working nine months, which pushes the required rate up. So a short-season fishery can support and require higher rates independently of anything about the fishing, and the same effect appears within a state between a high-country and a valley fishery.
Sources & methods
- The Office of Management and Budget notice, Standard Occupational Classification (SOC) System, Revision for 2018, published at 82 FR 56271 on 28 November 2017 and retrieved from the Federal Register on 26 July 2026. The notice announces OMB's final decision for the 2018 revision of Statistical Policy Directive No. 10; states that federal statistical agencies will begin using the 2018 SOC for occupational data published for reference years beginning on or after 1 January 2018; states that the 2018 SOC was designed and developed solely for statistical purposes; cites 31 U.S.C. 1104(d) and 44 U.S.C. 3504(e) as authority; states that the SOC classifies all occupations for which work is performed for pay or profit, covering all jobs in the national economy including public, private and military sectors, and that all federal agencies publishing occupational data for statistical purposes are required to use it; records that the 2018 structure contains 867 detailed occupations aggregated into 459 broad occupations combined into 98 minor groups and 23 major groups, that the revision realised a net gain of 27 detailed occupations and one minor group, that 472 detailed occupations were unchanged from 2010 and seventy are new; records that the SOC has been revised in 1980, 2000, 2010 and 2018; describes the Direct Match Title File introduced in 2010 and updated for 2018, listing job titles that map one-to-one to a single detailed occupation; and records that the revision process began with a notice at 79 FR 29620 on 22 May 2014. The SOC Manual itself and the classification's treatment of guiding occupations were not retrieved, because the site hosting them did not serve the request, and nothing about that treatment is asserted here.
- 44 U.S.C. 3504 at the Office of the Law Revision Counsel, cited as one of the two statutory provisions identified in the notice as its authority, the other being 31 U.S.C. 1104(d). No average day rate, range or typical figure for guided fishing is asserted anywhere on this page, for any state.
- The 28 November 2017 issue of the Federal Register published on govinfo, used as an independent copy of the notice relied on above. The figures in the arithmetic panel are stated illustrative assumptions used to demonstrate a structure. Licensing requirements, permit costs and access rules vary by state, were not researched here, and should be confirmed with the relevant state agency. Nothing on this page is financial or statistical advice.
Every figure here is traced to a named public source and checked against it. Licensing, tax, and fee rules change. Verify your state’s current rules with the agency directly before you count on any number here.
Evan Knox
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