Butler (KS) Investor Pulse Report (2025-Q4)

Real Estate comprehensive investment analysis of investor activity in the Butler (KS) single-family residential housing market. Discover ownership trends, transaction patterns, and market insights.

Market Overview

Total SFR Properties in Butler (KS)
21,543
Total Investors in Butler (KS)
4,654
Investor Owned SFR in Butler (KS)
4,746(22.0%)
Individual Landlords
Landlords
3,773
SFR Owned
3,001
Corporate Landlords
Landlords
881
SFR Owned
1,788
Understanding Property Counts

Distinct Count Methodology: The total 4,746 represents distinct properties — if 2+ landlords co-own the same property, it's counted only once. This provides the most accurate representation of investor-owned SFR properties.

Why totals don't sum: When broken down by Individual vs Corporate ownership (or by tier), properties with co-ownership across categories are counted once per category. For example, if a property is co-owned by an individual AND a corporate landlord, it appears in both counts. This is why Individual + Corporate totals may exceed the distinct total by 2-4%, and percentages may sum to 100-104%.

Market Visualization

Chart Section2 Coverage
Chart Section3 Ownership Donut
Chart Section4 Distribution

Key Market Insights

Mom-and-pop landlords control 87.5% of Butler County's investor market as institutions become net sellers.
Investors own 4,746 SFR properties in Butler County, representing 22.0% of the market. Small mom-and-pop landlords (1-10 properties) dominate with an 87.5% share, while institutions hold just 0.4%. In Q4, landlords acquired 32.0% of all homes sold, paying 21.0% less than traditional homeowners, even as institutional investors shifted to become net sellers.
Landlord Owned Current Holdings
Investors own 4,746 SFR properties in Butler County, with individuals holding a 63.2% majority.
The investor portfolio is heavily cash-based, with 3,901 properties owned outright versus just 845 financed. A significant 95.8% of investor-owned homes (4,548 properties) are classified as rented, indicating a strong focus on generating rental income.
Landlord vs Traditional Homeowners
Butler County landlords paid 21.0% less than traditional homeowners in Q4 2025, a $67,881 average discount.
The landlord purchasing discount has been substantial but volatile throughout 2025, widening to 21.0% in Q4 from a low of 13.7% in Q3. Earlier in the year, the discount was even more pronounced, reaching 35.8% in Q2 and 33.1% in Q1.
Current Quarter Purchases
Landlords captured 32.0% of the Butler County market in Q4, purchasing 110 single-family homes.
Mom-and-pop landlords (1-10 properties) dominated buying activity, accounting for 71.8% of all investor purchases (79 properties). In sharp contrast, institutional investors (1000+ properties) were nearly absent, acquiring just 1.8% of the investor total with only 2 properties.
Ownership by Tier
Mom-and-pop landlords (1-10 properties) overwhelmingly dominate Butler County, controlling 87.5% of all investor-owned homes.
Institutional investors with 1000+ properties have a negligible footprint, holding just 0.4% of the market (18 properties). However, their Q4 purchase of 2 homes represents a significant 11.1% expansion of their small local portfolio in a single quarter.
Ownership by Tier & Type
In Butler County, companies become the majority owners in portfolios of 6-10 properties, marking a key professionalization threshold.
Individual investors form the base of the market, owning 82.2% of single-property portfolios and over 60% of portfolios up to 5 properties. Company ownership share then surges to 77.9% in the 6-10 property tier and a near-total 99.4% in the 21-50 property tier.
Geographic Distribution
The 67042 zip code is the investor hub in Butler County by volume, containing 1,547 investor-owned properties.
While 67042 leads in raw count, smaller zip codes show far higher market saturation. The 67045 and 66842 zip codes have the highest penetration rates, with investors owning 66.7% and 56.8% of the local SFR housing stock, respectively.
Historical Transactions
While the overall landlord market was a strong net buyer in Q4 (135 buys vs 37 sells), institutions retreated as net sellers.
Landlords have been consistent net buyers throughout 2025, adding a net 373 properties to their portfolios for the year. In a significant divergence, institutional investors flipped their strategy in Q4, selling 3 properties while only acquiring 2, marking a shift towards divestment.
Current Quarter Transactions
Landlords participated in 26.4% of all Butler County housing transactions in Q4, totaling 135 transactions.
A massive price gap exists between investor types: institutional investors paid an average of just $47,292, which is 82.3% less than the $267,110 paid by new single-property landlords. Institutions also sourced 50.0% of their Q4 purchases from other landlords, compared to just 6.9% for new entrants.

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Current Holdings Portfolio

Analysis of landlord property holdings by type, financing method, and owner category

Chart Section5 Holdings
Key Insight
Investors own 4,746 SFR properties in Butler County, with individuals holding a 63.2% majority.
Detailed Findings

Investors hold a significant 22.0% share of the Single-Family Residential market in Butler County, with a total portfolio of 4,746 properties.

Individual 'mom-and-pop' investors are the backbone of the rental market, owning 3,001 properties, which accounts for 63.2% of all investor-owned SFRs. In contrast, company-owned portfolios consist of 1,788 properties, making up the remaining 37.7%.

The ownership structure by entity count shows an even wider gap, with 3,773 individual landlords compared to 881 company landlords. This highlights that the market is primarily composed of small, individual operators.

Cash is overwhelmingly the preferred method for holding assets, with 3,901 properties owned free and clear. This is over 4.6 times the number of properties that are financed (845), suggesting a market with low leverage and high equity.

The portfolio is almost entirely dedicated to rentals, with 4,548 of the 4,746 properties (95.8%) being non-owner-occupied. This confirms that the vast majority of investor activity is focused on providing housing supply for the rental market.

Acquisition Timing & Pricing

Comparison of acquisition prices between landlords and traditional homeowners

Key Insight
Butler County landlords paid 21.0% less than traditional homeowners in Q4 2025, a $67,881 average discount.
Detailed Findings

Investors consistently purchase properties at a significant discount compared to traditional homeowners in Butler County. In Q4 2025, landlords paid an average of $254,884, while homeowners paid $322,765, representing a 21.0% price advantage for investors.

This price gap translated to an average savings of $67,881 per property for landlords in the last quarter, showcasing a distinct strategic advantage in acquisition.

The investor discount has fluctuated throughout the year. The 21.0% Q4 discount marks a significant increase from the 13.7% gap observed in Q3, suggesting changing market dynamics or investor strategies toward the end of the year.

However, the Q4 discount is still below the highs seen earlier in 2025, when landlords achieved massive discounts of 35.8% in Q2 and 33.1% in Q1. This volatility indicates that the negotiation power of investors varies considerably from quarter to quarter.

The data reveals a clear and persistent pattern of landlords acquiring properties for substantially less than the general market, a key element of their investment model.

Chart Section6 Prices
Chart Section6 Prices Alt
Chart Section6 Trends
Chart Section6 Yoy Comparison

Current Quarter Purchase Summary

Analysis of Q4 2025 purchase activity by investor tier and type

Chart Section7 Purchases
Chart Section7 Tiers
Key Insight
Landlords captured 32.0% of the Butler County market in Q4, purchasing 110 single-family homes.
Detailed Findings

Investor activity accounted for nearly a third of all single-family home sales in Butler County during Q4 2025, with landlords purchasing 110 of the 344 properties sold.

The market continues to be fueled by new and small investors. In Q4, 72 new single-property landlord entities entered the market, acquiring 51 homes, which represents 46.4% of all investor purchases for the quarter.

Mom-and-pop landlords (portfolios of 1-10 properties) were the primary drivers of acquisition activity, collectively purchasing 79 properties. This amounts to 71.8% of all homes bought by investors, reinforcing the importance of small-scale operators in the market.

Mid-size investors also showed notable activity, particularly the 11-20 property tier, which acquired 21 properties, making up 19.1% of investor purchases.

Institutional buyers with portfolios over 1,000 properties had a minimal impact on the market, purchasing only 2 homes. Their 1.8% share of investor acquisitions stands in stark contrast to the 71.8% share held by mom-and-pop buyers.

Ownership by Purchase Tier

Distribution of investor-owned properties across portfolio size tiers

Key Insight
Mom-and-pop landlords (1-10 properties) overwhelmingly dominate Butler County, controlling 87.5% of all investor-owned homes.
Detailed Findings

The investor landscape in Butler County is unequivocally controlled by small-scale landlords. Those owning 1-10 properties (Tiers 01-04) hold a combined 87.5% of all investor-owned SFRs, challenging the narrative of large corporate dominance.

First-time and single-property investors form the largest segment of the market by a wide margin. Landlords owning just one rental property control 2,720 homes, which is 55.2% of the entire investor-owned housing stock.

In stark contrast, institutional investors (Tier 09, 1000+ properties) have a minimal presence, owning only 18 properties in the county. This represents a mere 0.4% of the investor-owned market.

The distribution is heavily skewed towards the smallest players. The first four tiers (1-10 properties) represent 87.5% of holdings, while the next four tiers (11-1000 properties) combined hold only 12.1%.

Despite their tiny overall share, institutional investors showed signs of growth in Q4. Their acquisition of 2 properties expanded their local 18-property portfolio by 11.1%, a notable increase for a single quarter.

Chart Section8 Distribution
Chart Section8 Prices
Chart Section8 Prices Q4
Chart Section8 Yoy Comparison

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Ownership by Tier & Owner Type

Breakdown of individual vs corporate ownership across portfolio tiers

Chart Section9 Ownership
Chart Section9 Growth
Chart Section9 Growth Q4
Chart Section9 Yoy Comparison
Key Insight
In Butler County, companies become the majority owners in portfolios of 6-10 properties, marking a key professionalization threshold.
Detailed Findings

A clear shift from individual to corporate ownership occurs as portfolio sizes increase in Butler County. While individuals dominate smaller portfolios, companies take majority control starting at the 6-10 property tier.

Individual landlords are the foundation of the market's entry levels. They own 82.2% of single-property portfolios, 65.0% of two-property portfolios, and 60.7% of portfolios with 3-5 properties.

The crossover point happens decisively in the 6-10 property tier, where company ownership jumps to 77.9%, while individual ownership falls to just 22.1%. This suggests that once a portfolio grows beyond 5 properties, incorporating becomes the standard strategy.

Corporate dominance intensifies in larger tiers. Companies own 78.1% of portfolios in the 11-20 property range and a commanding 99.4% in the 21-50 property range, with only one individually held property in that tier.

This pattern reveals a distinct lifecycle for real estate investors in the region: starting as individuals and transitioning to a corporate structure to manage growth, liability, and operational complexity at a portfolio size of around six properties.

Geographic Distribution

Regional breakdown of investor activity and ownership patterns

Key Insight
The 67042 zip code is the investor hub in Butler County by volume, containing 1,547 investor-owned properties.
Detailed Findings

Investor ownership in Butler County is geographically concentrated, with the top five zip codes accounting for a significant portion of the 4,746 investor-owned properties.

The 67042 zip code is the epicenter of investor activity by sheer volume, with 1,547 properties, more than the next four largest areas combined. However, its investor ownership rate of 28.4% is not the county's highest.

A key finding is the distinction between areas with high property counts and those with high ownership rates. The highest concentrations of investor ownership are found in smaller zip codes. For example, investors own 66.7% of the SFRs in 67045 and 56.8% in 66842.

This divergence indicates different investment strategies across the county. The focus in 67042 appears to be on scale within a large market, while in areas like 66842 and 67045, the strategy appears to be achieving dominant market share in a smaller housing stock.

The top three regions by property count are 67042 (1,547 properties), 67010 (818 properties), and 67002 (675 properties), which together represent 63.9% of all investor holdings in the county.

Chart Section10 Top Regions
Chart Section10 Top Pct

Historical Transactions

Buy/sell transaction trends over time for all landlords and institutional investors

Chart Section11 Buysell
Chart Section11 Buysell Price
Chart Section11 Yoy All Landlords
Chart Section11 Institutional
Chart Section11 Institutional Price
Chart Section11 Yoy Institutional
Key Insight
While the overall landlord market was a strong net buyer in Q4 (135 buys vs 37 sells), institutions retreated as net sellers.
Detailed Findings

The landlord market in Butler County displayed strong, positive acquisition momentum throughout 2025. In Q4, landlords were net buyers by a margin of 98 properties, with 135 acquisitions against only 37 sales.

This net buying trend has been consistent, with landlords adding a net 93 properties in Q3 and 98 in Q2. For the full year of 2025, total net acquisitions reached 373 properties, signaling sustained portfolio growth across the sector.

However, a critical divergence in strategy emerged in the institutional tier (1000+ properties) during the last quarter. While smaller landlords continued to buy, institutions became net sellers, disposing of 3 properties while only purchasing 2.

This Q4 reversal for institutional investors is a notable shift from their position earlier in the year. They were net buyers in Q3 (5 buys vs 3 sells) and for the year 2025 overall (13 buys vs 6 sells), indicating their recent move to sell is a new development.

The opposing trends—strong net buying from the broad market versus net selling from the largest players—suggest a potential strategic pivot or differing market outlooks between small-scale landlords and large institutions.

Current Quarter Transactions

Q4 2025 transaction analysis by tier, price, and inter-landlord activity

Key Insight
Landlords participated in 26.4% of all Butler County housing transactions in Q4, totaling 135 transactions.
Detailed Findings

In Q4 2025, landlords were a significant force in the market, participating in 135 of the 512 total SFR transactions, a 26.4% share of all activity.

A staggering pricing disparity reveals different acquisition strategies across investor tiers. Institutional investors (1000+) paid an average of only $47,292 per property, while new, single-property landlords paid $267,110. This 82.3% price difference suggests institutions target distressed or lower-value assets not pursued by smaller buyers.

Mom-and-pop landlords (Tiers 01-04) were the most active, conducting 100 of the 135 investor transactions. This group's activity was led by 72 transactions from new single-property buyers, highlighting the continuous influx of small investors.

Sourcing of properties also differs dramatically by tier. Institutional investors relied heavily on the existing investor network, with 50.0% of their two purchases coming from other landlords. In contrast, new single-property landlords sourced only 6.9% of their acquisitions from other investors, indicating they primarily buy from the open market.

The data shows a clear divide: new mom-and-pop landlords buy higher-priced homes from the public market, while large institutional players acquire heavily discounted properties, often from within the investor community itself.

Chart Section12 Transactions
Chart Section12 Prices
Chart Section12 Prices Detail

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Executive Summary

Mom-and-pop landlords command 87.5% of Butler County's investor market as institutions retreat as net sellers.
Holdings
In Butler County, KS, landlords own 4,746 single-family residential properties, which constitutes 22.0% of the total market. Individual investors hold the clear majority with 3,001 properties (63.2%), while companies own 1,788 properties (37.7%).
Pricing
Landlords demonstrated a significant purchasing advantage in Q4 2025, paying 21.0% less than traditional homeowners. This amounted to an average discount of $67,881 per property, with landlords paying $254,884 versus the homeowner price of $322,765.
Activity
Investors were highly active in Q4 2025, purchasing 110 homes and capturing 32.0% of all market sales. The market's growth was driven by small players, with 72 new single-property landlords entering and mom-and-pop tiers accounting for 71.8% of all investor acquisitions.
Market Share
The investor market is overwhelmingly dominated by small landlords (1-10 properties), who control 87.5% of all investor-owned housing. In stark contrast, institutional investors (1000+ properties) hold a marginal share of just 0.4%.
Ownership Type
Individual investors form the foundation of the market, but a clear professionalization threshold exists. Companies become the majority owners in portfolios of 6-10 properties and their dominance grows to 99.4% in the 21-50 property tier.
Transactions
While landlords as a whole remained strong net buyers in Q4 with a 3.65x buy-to-sell ratio (135 buys vs 37 sells), institutional investors diverged from this trend. The largest players became net sellers, disposing of more properties than they acquired (2 buys vs 3 sells).
Market Narrative

In Butler County, KS, the real estate investor market is fundamentally shaped by small, independent operators rather than large corporations. Investors own a notable 4,746 single-family homes, representing 22.0% of the county's total SFR stock. This portfolio is primarily in the hands of individuals, who own 63.2% of these properties. The market structure heavily favors mom-and-pop landlords (1-10 properties), who command an overwhelming 87.5% of investor-owned housing, while large institutional firms with over 1,000 properties control a mere 0.4%, directly challenging the narrative of Wall Street dominance in this local market.

Investor behavior in Q4 2025 highlighted a dynamic and bifurcated market. Landlords were highly active, acquiring 32.0% of all homes sold while securing them at a 21.0% discount compared to traditional homeowners. This activity was fueled by the entry of 72 new single-property investors. However, a significant strategic split has emerged: while the broad market of small-to-mid-size landlords continued as strong net buyers, the small cohort of institutional investors shifted to become net sellers, signaling a potential divergence in market outlook between the largest and smallest players.

The key takeaway from the Butler County data is a story of two markets. One is a robust and growing ecosystem of individual and small-scale landlords who are actively acquiring properties at a discount and providing the vast majority of rental housing. The other is a micro-market of institutional players who are not only insignificant in size but are now showing signs of divestment. This reveals a healthy, decentralized rental market where opportunity is primarily being capitalized on by local entrepreneurs, not distant corporations.

About This Report

Report Methodology

This report analyzes BatchData's Investor Pulse dataset, covering single-family residential (SFR) investor activity across the United States.

Data is extracted from 15 CSV files covering ownership, transactions, and pricing trends, then analyzed using AI-powered insights.

Property Counting Methodology:

Distinct Counts: All headline totals represent distinct properties. If 2+ landlords co-own the same property, it's counted only once. This provides accurate market representation.

Category Breakdowns: When analyzing by tier (01-09), owner type (Individual/Corporate), or occupancy status, properties with co-ownership across categories are counted once per category. This causes breakdowns to sum 2-4% higher than totals, and percentages may sum to 100-104%. This is expected and reflects co-ownership patterns.

TierPropertiesCategory
01-041-10Mom-and-Pop
05-0711-100Mid-Size
08101-1000Large
091000+Institutional
About BatchData

BatchData provides comprehensive real estate data and analytics, offering insights into property ownership, investor activity, and market trends across the United States.

The Investor Pulse dataset tracks single-family residential (SFR) investor behavior at national, state, county, and MSA levels.

For more information, visit batchdata.io or explore our API documentation.

Data Freshness
Report GeneratedMarch 16, 2026 at 05:04 PM
Data PeriodQ4 2025
Geography LevelCounty
GeographyButler (KS)
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Chart Section2 Coverage
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Chart Section3 Ownership Donut
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Chart Section3 Ownership Bar
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Chart Section4 Distribution
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Chart Section5 Holdings
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Chart Section6 Prices
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Chart Section6 Prices Alt
Chart Section6 Prices Alt
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Chart Section6 Yoy Comparison
Chart Section6 Yoy Comparison
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Chart Section6 Trends
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Chart Section7 Purchases
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Chart Section7 Tiers
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Chart Section8 Distribution
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Chart Section8 Prices
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Chart Section8 Prices Q4
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Chart Section8 Prices 2020
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Chart Section8 Yoy Comparison
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Chart Section9 Ownership
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Chart Section9 Growth
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Chart Section9 Growth Q4
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Chart Section9 Yoy Comparison
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Chart Section10 Top Regions
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Chart Section10 Top Pct
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Chart Section11 Buysell
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Chart Section11 Buysell Price
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Chart Section11 Yoy All Landlords
Chart Section11 Yoy All Landlords
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Chart Section11 Institutional
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Chart Section11 Institutional Price
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Chart Section11 Yoy Institutional
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Chart Section12 Transactions
Chart Section12 Transactions
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Chart Section12 Prices
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Chart Section12 Prices Detail
Chart Section12 Prices Detail