What Cleveland’s No. 1 DUPR Growth Ranking Actually Measures

Cleveland ranked No. 1 among the places in DUPR’s 2026 top-10 list, based on a 71% increase in DUPR users over the preceding 12 months. That is a platform-user growth result—not a finding that Cleveland’s total pickleball-playing population increased 71%.

Choose a ranked place and enter a starting user count to translate its percentage into estimated users added.

Huntsville placed second at 70.6%, while Seattle was third at 70%, according to DUPR’s published ranking. Cleveland therefore led the published list by 0.4 percentage points over Huntsville and by 1 percentage point over Seattle.

Those differences describe growth rates, not differences in the numbers of users added. DUPR did not publish the starting or ending city-level user totals needed to make that second comparison.

The Full DUPR City Ranking

DUPR reported the following increases in users over 12 months. The list was published publicly in September 2026, but the public post did not state the precise start and end dates of the underlying measurement period.

Rank	Place	DUPR User Increase
1	Cleveland, Ohio	71%
2	Huntsville, Alabama	70.6%
3	Seattle, Washington	70%
4	Philadelphia, Pennsylvania	64%
5	Fremont, California	62%
6	Ashburn, Virginia	61%
7	Lexington, Kentucky	60.1%
8	Fort Lauderdale, Florida	60%
9	Las Vegas, Nevada	57%
10	Cumming, Georgia	56%

Source: DUPR’s published top-10 list. The percentages and order were also reproduced by The Kitchen on September 16, 2026.

The ranking is close at the top. Cleveland’s reported 71% is only 0.4 percentage points above Huntsville’s 70.6%. Seattle is another 0.6 percentage points behind Huntsville. The gap between first and third is therefore 1 percentage point.

The published percentages use mixed precision: some are whole percentages, while Huntsville and Lexington are shown to one decimal place. Without unrounded values or a stated rounding method, the displayed figures are the appropriate basis for comparison. They establish the published order but do not reveal whether the underlying difference between two places was slightly larger or smaller before rounding.

The tenth-ranked place, Cumming, posted 56% growth in DUPR users. Cleveland’s rate was 15 percentage points higher. That comparison still says nothing about which place added more users because each percentage was applied to a different, undisclosed starting base.

Cleveland’s 71% Means 1.71 Times the Starting Total

A 71% increase means the ending number of Cleveland DUPR users was 1.71 times the starting number, assuming the percentage represents conventional net user growth.

The calculation is: ending users equal starting users multiplied by 1.71. Users added equal starting users multiplied by 0.71.

If Cleveland had started with 1,000 DUPR users, 71% growth would produce 1,710 users—an increase of 710. If it had started with 10,000, the same rate would represent 7,100 additional users and an ending total of 17,100.

Those are examples, not reported Cleveland totals. DUPR’s public post did not give Cleveland’s starting count, ending count or absolute increase. The 1,000- and 10,000-user scenarios show how the published rate works, but neither should be presented as an estimate of Cleveland’s actual user base.

The distinction matters because a percentage cannot be converted into an absolute increase without a baseline. The same 71% rate can represent hundreds, thousands or another number of added users depending on how many users were present at the start.

If a reliable starting count becomes available, the calculator above can apply the published rate. Until then, Cleveland’s absolute number of added DUPR users remains unknown from the ranking alone.

First In Growth Rate Does Not Mean Most Users Added

Cleveland ranked first by percentage growth, which is a relative measure. It did not necessarily add the greatest number of DUPR users.

A place beginning with a smaller user base can post a high percentage after adding fewer users than a larger market. Conversely, a place with a lower percentage can add more users if its starting base is sufficiently large. Comparing absolute additions therefore requires both the growth rate and starting total for every place being compared.

The ranking supplies only one of those two values. It gives each listed place’s percentage increase but omits its initial number of users. As a result, it cannot answer whether Cleveland added more DUPR users than Huntsville, Seattle or any other place.

It also cannot establish which listed place had the most DUPR users at the end of the period. Ending size depends on starting size as well as growth. A No. 1 growth rate and a No. 1 total are separate claims, and the published data support only the former.

The word “fastest” in a growth ranking refers to the rate of change under the publisher’s metric. It does not by itself mean largest, busiest or most consequential in absolute terms. Cleveland’s result is strongest when described with all three defining elements: percentage growth, DUPR users and the 12-month period.

DUPR User Growth Is Not Total Player Growth

DUPR is a player-rating platform rather than a representative population survey. Growth in its user total measures adoption of or presence on that platform. It does not directly count everyone who plays pickleball in a city.

DUPR’s account guidance says previous tournament players may already have an account available to claim. It also says newly registered players can have “No Rating” status until match data initializes a rating. These pathways show why platform-user growth and growth in the underlying player population are not interchangeable.

A person could have played pickleball before joining or claiming a DUPR account. That person would be new to the platform’s user count without necessarily being new to the sport. Increased use of rated leagues, clubs, tournaments or match reporting could also bring existing players onto the platform.

At the same time, some genuinely new players may create DUPR accounts. The public ranking does not divide its increase into new pickleball participants, established players newly adopting DUPR, returning users or other account pathways. It therefore cannot identify how much of Cleveland’s 71% resulted from underlying participation growth and how much resulted from platform adoption.

For more on what the platform measures and how ratings are created, see the DUPR rating system.

The Ranking Does Not Measure Courts or Demand

Nothing in the published percentage establishes that Cleveland has the most pickleball players, courts or court demand. Those questions require different datasets.

A court comparison would need a consistently defined inventory covering the same types of facilities and geographic boundaries. A participation comparison would need representative local estimates or another population-based measure. A demand comparison could involve usage, reservations, waiting times or other evidence, none of which appears in this ranking.

The DUPR list should not be used as a substitute for those measures merely because all of them relate to pickleball growth. Platform registrations, total players, court supply and court pressure can move together, but they are not the same variable.

The ranking also does not show that Cleveland added the most pickleball players nationally. It covers the places in DUPR’s published top 10 and reports user growth rates for them. It does not provide a national count of newly participating players by city.

Missing Method Details Limit Broader Comparisons

DUPR’s public post does not disclose city-level starting totals, ending totals, minimum sample thresholds, geographic boundary rules or a complete list of places considered. It also does not state the precise start and end dates behind the described 12-month period.

The absence of starting totals prevents calculation of absolute user additions. The absence of minimum thresholds makes it impossible to tell from the public post how large a user base a place needed to enter the analysis. Growth rates can be especially sensitive to the starting denominator, so that threshold would help readers assess comparisons between markets of different sizes.

Geographic definitions matter because labels can refer to city limits, postal areas, metropolitan areas or another platform-defined boundary. The public ranking names places but does not explain which boundary was used for each calculation. The figures should therefore be attributed to DUPR’s named places rather than silently expanded to a county, metropolitan area or broader region.

A complete list of places considered would show the ranking’s comparison universe. The public post provides a top 10, but it does not identify every eligible place or allow readers to reconstruct why another location fell outside the list.

These omissions do not disprove the reported 71% increase. They limit what can be independently checked and what can be inferred beyond the published ranking. The appropriate response is to preserve the scope of the claim rather than replace the missing details with assumptions.

The Defensible Cleveland Claim

The supported statement is: Cleveland ranked first on DUPR’s published 2026 U.S. top-10 list for percentage growth in DUPR users over 12 months, with a reported increase of 71%.

It is also accurate to say Cleveland’s published rate exceeded Huntsville’s by 0.4 percentage points and Seattle’s by 1 percentage point. Those comparisons come directly from the displayed rates.

The ranking does not establish that Cleveland’s total pickleball population grew 71%, that it added the most players or DUPR users, or that it leads the country in players, courts or demand. Claims at that broader level would require user totals, a representative participation survey or another measure designed for the specific question.