{"success":true,"data":{"query":"Market Velocity","limit":10,"count":10,"sources":["wiki_artificial_intelligence.hat","wiki_real_estate.hat","web_1779060034.hat","wiki_dallas.hat"],"synced":[],"results":[{"source":"wiki_artificial_intelligence.hat","text":"Risks and harm\nPrivacy and copyright\nMachine learning algorithms require large amounts of data. The techniques used to acquire this data have raised concerns about privacy, surveillance and copyright.\nAI-powered devices and services, such as virtual assistants and IoT products, continuously collect personal information, raising concerns about intrusive data gathering and unauthorized access by third parties. The loss of privacy is further exacerbated by AI's ability to process and combine vast amounts of data, potentially leading to a surveillance society where individual activities are constantly monitored and analyzed without adequate safeguards or transparency.\nSensitive user data collected may include online activity records, geolocation data, video, or audio. For example, in order to build speech recognition algorithms, Amazon has recorded millions of private conversations and allowed temporary workers to listen to and transcribe some of them. Opinions about this widespread surveillance range from those who see it as a necessary evil to those for whom it is clearly unethical and a violation of the right to privacy.\nAI developers argue that this is the only way to deliver valuable applications and have developed several techniques that attempt to preserve privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. Since 2016, some privacy experts, such as Cynthia Dwork, have begun to view privacy in terms of fairness. Brian Christian wrote that experts have pivoted \"from the question of 'what they know' to the question of 'what they're doing with it'.\"\nGenerative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code; the output is then used under the rationale of \"fair use\". Experts disagree about how well and under what circumstances this rationale will hold up in courts of law; relevant factors may include \"the purpose and character of the use of the copyrighted work\" and \"the effect upon the potential market for the copyrighted work\". Website owners can indicate that they do not want their content scraped via a \"robots.txt\" file. However, some companies will scrape content regardless because the robots.txt file has no real authority. In 2023, leading authors (including John Grisham and Jonathan Franzen) sued AI companies for using their work to train generative AI. Another discussed approach is to envision a separate sui generis system of protection for creations generated by AI to ensure fair attribution and compensation for human authors.","score":53.16641805025819,"links":[]},{"source":"wiki_artificial_intelligence.hat","text":"Bad actors and weaponized AI\nArtificial intelligence provides a number of tools that are useful to bad actors, such as authoritarian governments, terrorists, criminals or rogue states.\nA lethal autonomous weapon is a machine that locates, selects and engages human targets without human supervision. Widely available AI tools can be used by bad actors to develop inexpensive autonomous weapons and, if produced at scale, they are potentially weapons of mass destruction. Even when used in conventional warfare, they currently cannot reliably choose targets and could potentially kill an innocent person. In 2014, 30 nations (including China) supported a ban on autonomous weapons under the United Nations' Convention on Certain Conventional Weapons, however the United States and others disagreed. By 2015, over fifty countries were reported to be researching battlefield robots.\nAI tools make it easier for authoritarian governments to efficiently control their citizens in several ways. Face and voice recognition allow widespread surveillance. Machine learning, operating this data, can classify potential enemies of the state and prevent them from hiding. Recommendation systems can precisely target propaganda and misinformation for maximum effect. Deepfakes and generative AI aid in producing misinformation. Advanced AI can make authoritarian centralized decision-making more competitive than liberal and decentralized systems such as markets. It lowers the cost and difficulty of digital warfare and advanced spyware. All these technologies have been available since 2020 or earlier—AI facial recognition systems are already being used for mass surveillance in China.\nThere are many other ways in which AI is expected to help bad actors, some of which can not be foreseen. For example, machine-learning AI is able to design tens of thousands of toxic molecules in a matter of hours.","score":53.16641805025819,"links":[]},{"source":"wiki_artificial_intelligence.hat","text":"History\nThe study of mechanical or \"formal\" reasoning began with philosophers and mathematicians in antiquity. The study of logic led directly to Alan Turing's theory of computation, which suggested that a machine, by shuffling symbols as simple as \"0\" and \"1\", could simulate any conceivable form of mathematical reasoning. This, along with concurrent discoveries in cybernetics, information theory and neurobiology, led researchers to consider the possibility of building an \"electronic brain\". They developed several areas of research that would become part of AI, such as McCulloch and Pitts design for \"artificial neurons\" in 1943, and Turing's influential 1950 paper 'Computing Machinery and Intelligence', which introduced the Turing test and showed that \"machine intelligence\" was plausible.\nThe field of AI research was founded at a workshop at Dartmouth College in 1956. The first AI program, Logic Theorist, was presented at the workshop, created by future Turing Award winner Allen Newell and future Nobel Laureate Herbert A. Simon, in collaboration with J. C. Shaw. Many of the workshop attendees became the leaders of AI research in the 1960s. They and their students produced programs that the press described as \"astonishing\": computers were learning checkers strategies, solving word problems in algebra, proving logical theorems and speaking English. Artificial intelligence laboratories were set up at a number of British and U.S. universities in the latter 1950s and early 1960s.\nResearchers in the 1960s and the 1970s were convinced that their methods would eventually succeed in creating a machine with general intelligence and considered this the goal of their field. In 1965 Herbert Simon predicted, \"machines will be capable, within twenty years, of doing any work a man can do\". In 1967 Marvin Minsky agreed, writing that \"within a generation ... the problem of creating 'artificial intelligence' will substantially be solved\". They had, however, underestimated the difficulty of the problem. In 1974, both the U.S. and British governments cut off exploratory research in response to the criticism of Sir James Lighthill and ongoing pressure from the U.S. Congress to fund more productive projects. Minsky and Papert's book Perceptrons was understood as proving that artificial neural networks would never be useful for solving real-world tasks, thus discrediting the approach altogether. The \"AI winter\", a period when obtaining funding for AI projects was difficult, followed.\nIn the early 1980s, AI research was revived by the commercial success of expert systems, a form of AI program that simulated the knowledge and analytical skills of human experts. By 1985, the market for AI had reached over a billion dollars. At the same time, Japan's fifth generation computer project inspired the U.S. and British governments to restore funding for academic research. However, beginning with the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, longer-lasting winter began.\nUp to this point, most of AI's funding had gone to projects that used high-level symbols to represent mental objects like plans, goals, beliefs, and known facts. In the 1980s, some researchers began to doubt that this approach would be able to imitate all the processes of human cognition, especially perception, robotics, learning and pattern recognition, and began to look into \"sub-symbolic\" approaches. Rodney Brooks rejected \"representation\" in general and focussed directly on engineering machines that move and survive. Judea Pearl, Lotfi Zadeh, and others developed methods that handled incomplete and uncertain information by making reasonable guesses rather than precise logic. But the most important development was the revival of \"connectionism\", including neural network research, by Geoffrey Hinton and others. In 1990, Yann LeCun successfully showed that convolutional neural networks can recognize handwritten digits, the first of many successful applications of neural networks.\nAI gradually restored its reputation in the late 1990s and early 21st century by exploiting formal mathematical methods and by finding specific solutions to specific problems. This \"narrow\" and \"formal\" focus allowed researchers to produce verifiable results and collaborate with other fields (such as statistics, economics and mathematics). By 2000, solutions developed by AI researchers were being widely used, although in the 1990s they were rarely described as \"artificial intelligence\" (a tendency known as the AI effect).\nHowever, several academic researchers became concerned that AI was no longer pursuing its original goal of creating versatile, fully intelligent machines. Beginning around 2002, they founded the subfield of artificial general intelligence (or \"AGI\"), which had several well-funded institutions by the 2010s.\nDeep learning began to dominate industry benchmarks in 2012 and was adopted throughout the field.\nFor many specific tasks, other methods were abandoned.\nDeep learning's success was based on both hardware improvements (faster computers, graphics processing units, cloud computing) and access to large amounts of data (including curated datasets, such as ImageNet). Deep learning's success led to an enormous increase in interest and funding in AI. The amount of machine learning research (measured by total publications) increased by 50% in the years 2015–2019.","score":53.16641805025819,"links":[]},{"source":"wiki_real_estate.hat","text":"History of real estate\nThe natural right of a person to own property as a concept can be seen as having roots in Roman law as well as Greek philosophy. The profession of appraisal can be seen as beginning in England during the 1500s, as agricultural needs required land clearing and land preparation. Textbooks on the subject of surveying began to be written and the term \"surveying\" was used in England, while the term \"appraising\" was more used in North America. Natural law which can be seen as \"universal law\" was discussed among writers of the 15th and 16th century as it pertained to \"property theory\" and the inter-state relations dealing with foreign investments and the protection of citizens private property abroad. Natural law can be seen as having an influence in Emerich de Vattel's 1758 treatise The Law of Nations which conceptualized the idea of private property.\nOne of the largest initial real estate deals in history known as the \"Louisiana Purchase\" happened in 1803 when the Louisiana Purchase Treaty was signed. This treaty paved the way for western expansion and made the U.S. the owners of the \"Louisiana Territory\" as the land was bought from France for fifteen million dollars, making each acre roughly 4 cents. The oldest real estate brokerage firm was established in 1855 in Chicago, Illinois, and was initially known as \"L. D. Olmsted & Co.\" but is now known as \"Baird & Warner\". In 1908, the National Association of Realtors was founded in Chicago and in 1916, the name was changed to the National Association of Real Estate Boards and this was also when the term \"realtor\" was coined to identify real estate professionals.\nThe stock market crash of 1929 and the Great Depression in the U.S. caused a major drop in real estate worth and prices and ultimately resulted in depreciation of 50% for the four years after 1929. Housing financing in the U.S. was greatly affected by the Banking Act of 1933 and the National Housing Act in 1934 because it allowed for mortgage insurance for home buyers and this system was implemented by the Federal Deposit Insurance as well as the Federal Housing Administration. In 1938, an amendment was made to the National Housing Act and Fannie Mae, a government agency, was established to serve as a secondary market for mortgages and to give lenders more money in order for new homes to be funded.\nTitle VIII of the Civil Rights Act in the U.S., which is also known as the Fair Housing Act, was put into place in 1968 and dealt with the incorporation of African Americans into neighborhoods as the issues of discrimination were analyzed with the renting, buying, and financing of homes. Internet real estate as a concept began with the first appearance of real estate platforms on the World Wide Web (www) and occurred in 1999.","score":36.327294707324214,"links":[]},{"source":"wiki_real_estate.hat","text":"Chawls\nHavelis\nIgloos\nHuts\nThe size of havelis and chawls is measured in Gaz (square yards), Quila, Marla, Beegha, and acre.\nSee List of house types for a complete listing of housing types and layouts, real estate trends for shifts in the market, and house or home for more general information.\n\nDevelopment\nReal estate development involves planning and coordinating of housebuilding, real estate construction or renovation projects. Real estate development can be less cyclical than real estate investing.\nThe price of real estate increases with demand and decreases with supply according to demand and supply.","score":36.327294707324214,"links":[]},{"source":"wiki_real_estate.hat","text":"A real estate developer who secures funding for the project;\nOne or more financial institutions or other investors that provide the funding;\nLocal planning and code authorities;\nA surveyor who performs an ALTA/ACSM and construction surveys throughout the project;\nConstruction managers who coordinate the effort of different groups of project participants;\nLicensed architects and engineers who provide building design and prepare construction documents;\nThe principal design engineering disciplines which normally include the following professionals: civil, structural, mechanical engineers, building services, HVAC (Heating, Ventilation and Air Conditioning), plumbing and drainage. Other design engineer specialists may also be involved such as fire prevention, acoustic, façade engineers, building physics, Telecoms, AV (Audio Visual), BMS (Building Management Systems) Automatic controls etc. These design engineers also prepare construction documents which are issued to specialist contractors to obtain a price for the works and to follow for the installations.\nLandscape architects;\nInterior designers;\nOther consultants;\nContractors who provide construction services and install building systems such as climate control, electrical, plumbing, decoration, fire protection, security and telecommunications;\nMarketing or leasing agents;\nFacility managers who are responsible for operating the building.\nBuildings are typically subject to planning and building regulations depending on their jurisdiction, including zoning ordinances, building codes, and other regulations such as fire codes, life safety codes, and related standards.\nVehicles—such as trailers, caravans, ships, and passenger aircraft—are treated as \"buildings\" for life safety purposes.","score":36.327294707324214,"links":[]},{"source":"web_1779060034.hat","text":"Menu Using App Router Features available in /app Latest Version 16.2.6 This page is also available as Markdown at /docs/app/guides.md . For an index of Next.js documentation , see /docs/llms.txt . Copy page Guides Last updated May 13, 2026 AI Coding Agents Learn how to configure your Next.js project so AI coding agents use up-to-date documentation instead of outdated training data. Analytics Measure and track page performance using Next.js Speed Insights Authentication Learn how to implement authentication in your Next.js application. Backend for Frontend Learn how to use Next.js as a backend framework Caching (Previous Model) Learn how to cache and revalidate data using fetch options, unstable_cache, and route segment configs for projects not using Cache Components. CDN Caching Learn how CDN caching works with Next.js, including what works today, cache variability, and the direction toward pathname-based cache keying. CI Build Caching Learn how to configure CI to cache Next.js builds Content Security Policy Learn how to set a Content Security Policy (CSP) for your Next.js application. CSS-in-JS Use CSS-in-JS libraries with Next.js Custom Server Start a Next.js app programmatically using a custom server. Data Security Learn the built-in data security features in Next.js and learn best practices for protecting your application's data. Debugging Learn how to debug your Next.js application with VS Code, Chrome DevTools, or Firefox DevTools. Deploying to Platforms Understand which Next.js features require specific platform capabilities and how to choose the right deployment target. Draft Mode Next.js has draft mode to toggle between static and dynamic pages. You can learn how it works with App Router here. Environment Variables Learn to add and access environment variables in your Next.js application. Forms Learn how to create forms in Next.js with React Server Actions. How Revalidation Works A deep dive into how Next.js revalidates cached content, including the tag system, cache consistency, and multi-instance coordination. ISR Learn how to create or update static pages at runtime with Incremental Static Regeneration. Instrumentation Learn how to use instrumentation to run code at server startup in your Next.js app Internationalization Add support for multiple languages with internationalized routing and localized content. JSON-LD Learn how to add JSON-LD to your Next.js application to describe your content to search engines and AI. Lazy Loading Lazy load imported libraries and React Components to improve your application's loading performance. Development Environment Learn how to optimize your local development environment with Next.js. Next.js MCP Server Learn how to use Next.js MCP support to allow coding agents access to your application state MDX Learn how to configure MDX and use it in your Next.js apps. Memory Usage Optimize memory used by your application in development and production. Migrating Learn how to migrate from popular frameworks to Next.js Migrating to Cache Components Learn how to migrate from route segment configs to Cache Components in Next.js. Multi-tenant Learn how to build multi-tenant apps with the App Router. Multi-zones Learn how to build micro-frontends using Next.js Multi-Zones to deploy multiple Next.js apps under a single domain. OpenTelemetry Learn how to instrument your Next.js app with OpenTelemetry. Package Bundling Learn how to analyze and optimize your application's server and client bundles with the Next.js Bundle Analyzer for Turbopack, and the `@next/bundle-analyzer` plugin for Webpack. PPR Platform Guide A guide for platform engineers on implementing PPR support, from basic origin rendering to optimized CDN integration. Prefetching Learn how to configure prefetching in Next.js Preserving UI state Learn how React's Activity component preserves UI state across navigations in Next.js and how to control what resets. Preventing Flash Learn how to correct server-rendered content before the browser paints, avoiding visible flash when the page hydrates. Production Recommendations to ensure the best performance and user experience before taking your Next.js application to production. PWAs Learn how to build a Progressive Web Application (PWA) with Next.js. Public pages Learn how to build public, \"static\" pages that share data across users, such as landing pages, list pages (products, blogs, etc.), marketing and news sites. Redirecting Learn the different ways to handle redirects in Next.js. Rendering Philosophy Learn how Next.js treats static and dynamic rendering as a spectrum at the component level, and what this means for deployment. Sass Style your Next.js application using Sass. Scripts Optimize 3rd party scripts with the built-in Script component. Self-Hosting Learn how to self-host your Next.js application on a Node.js server, Docker image, or static HTML files (static exports). SPAs Next.js fully supports building Single-Page Applications (SPAs). Static Exports Next.js enables starting as a static site or Single-Page Application (SPA), then later optionally upgrading to use features that require a server. Streaming Learn how streaming works in Next.js and how to use it to progressively render UI as data becomes available. Tailwind CSS v3 Style your Next.js Application using Tailwind CSS v3 for broader browser support. Testing Learn how to set up Next.js with four commonly used testing tools — Cypress, Playwright, Vitest, and Jest. Third Party Libraries Optimize the performance of third-party libraries in your application with the `@next/third-parties` package. Upgrading Learn how to upgrade to the latest versions of Next.js. Videos Recommendations and best practices for optimizing videos in your Next.js application. View transitions Learn how to use view transitions to communicate meaning during navigation, loading, and content changes in a Next.js app. Was this helpful? supported. Send","score":27.12400931168676,"links":[]},{"source":"wiki_dallas.hat","text":"Neighborhoods\nThe city of Dallas is home to many areas, neighborhoods, and communities. Dallas can be divided into several geographical areas which include larger geographical sections of territory including many subdivisions or neighborhoods, forming macroneighborhoods.\n\nCentral Dallas\nCentral Dallas is anchored by Downtown Dallas, the center of the city, along with Oak Lawn and Uptown, areas characterized by dense retail, restaurants, and nightlife. Downtown Dallas has a variety of named districts, including the West End Historic District, the Arts District, the Main Street District, Farmers Market District, the City Center Business District, the Convention Center District, and the Reunion District. This area includes Uptown, Victory Park, Harwood, Oak Lawn, Dallas Design District, Trinity Groves, Turtle Creek, Cityplace, Knox/Henderson, Greenville, and West Village.","score":19.64045859628254,"links":[]},{"source":"wiki_dallas.hat","text":"Economy\nIn its beginnings, Dallas relied on farming, neighboring Fort Worth's Stockyards, and its prime location on Native American trade routes to sustain itself. Dallas's key to growth came in 1873 with the construction of multiple rail lines through the city. As Dallas grew and technology developed, cotton became its boon and by 1900, Dallas was the largest inland cotton market in the world, becoming a leader in cotton gin machinery manufacturing.\nBy the early 1900s, Dallas was a hub for economic activity all over the Southern United States and was selected in 1914 as the seat of the Eleventh Federal Reserve District. By 1925, Texas churned out more than 1⁄3 of the nation's cotton crop, with 31% of Texas cotton produced within a 100-mile (160 km) radius of Dallas. In the 1930s, petroleum was discovered east of Dallas, near Kilgore. Dallas's proximity to the discovery put it immediately at the center of the nation's petroleum market. Petroleum discoveries in the Permian Basin, the Panhandle, the Gulf Coast, and Oklahoma in the following years further solidified Dallas's position as the hub of the market.\nThe end of World War II left Dallas seeded with a nexus of communications, engineering, and production talent by companies such as Collins Radio Corporation. Decades later, the telecommunications and information revolutions still drive a large portion of the local economy. The city is sometimes referred to as the heart of \"Silicon Prairie\" because of a high concentration of telecommunications companies in the region, the epicenter of which lies along the Telecom Corridor in Richardson, a northern suburb of Dallas. The Telecom Corridor is home to more than 5,700 companies including Texas Instruments (headquartered in Dallas), Nortel Networks, Alcatel Lucent, AT&T, Ericsson, Fujitsu, Nokia, Rockwell Collins, Cisco Systems, T-Mobile, Verizon Communications, and CompUSA (which is now headquartered in Miami, Florida). Texas Instruments, a major manufacturer, employs 10,400 people at its corporate headquarters and chip plants in Dallas.\nIn the 1980s Dallas was a real estate hotbed, with the increasing metropolitan population bringing with it a demand for new housing and office space. Several of Downtown Dallas's largest buildings are the fruit of this boom, but over-speculation, the savings and loan crisis and an oil bust brought the 1980s building boom to an end for Dallas as well as its sister city Houston. Between the late 1980s and the early 2000s, central Dallas went through a slow period of growth. However, since the early 2000s the central core of Dallas has been enjoying steady and significant growth encompassing both repurposing of older commercial buildings in Downtown Dallas into residential and hotel uses, as well as the construction of new office and residential towers. The opening of Klyde Warren Park, built across Woodall Rodgers Freeway seamlessly connecting the central Dallas CBD to Uptown/Victory Park, has acted synergistically with the highly successful Dallas Arts District, so both have become catalysts for significant new development in central Dallas.\nThe residential real estate market in the Dallas–Fort Worth metroplex has not only been resilient but has once again returned to a boom status. Dallas and the greater metro area have been leading the nation in apartment construction and net leasing, with rents reaching all-time highs. Single family home sales, whether pre-owned or new construction, along with home price appreciation, were leading the nation since 2015.\nA sudden drop in the price of oil, starting in mid-2014 and accelerating throughout 2015, has not significantly affected Dallas and its greater metro area due to the highly diversified nature of its economy. Dallas and the metropolitan region continue to see strong demand for housing, apartment and office leasing, shopping center space, warehouse and industrial space with overall job growth remaining very robust. Oil-dependent cities and regions have felt significant effects from the downturn, but Dallas's growth has continued unabated, strengthening in 2015. Significant national headquarters relocations to the area (as exemplified by Toyota's decision to leave California and establish its new North American headquarters in the Dallas area) coupled with significant expansions of regional offices for a variety of corporations and along with company relocations to Downtown Dallas helped drive the boom in the Dallas economy.","score":19.64045859628254,"links":[]},{"source":"wiki_dallas.hat","text":"Sports\nDowntown Dallas is home to two major league sports teams that play at the American Airlines Center: the Dallas Mavericks (NBA), who won the NBA Championship in 2011, and the Dallas Stars (NHL), who won the Stanley Cup in 1999. Nearby Arlington is home to the Dallas Cowboys (NFL), who play at the AT&T Stadium and have won five Super Bowls, the Texas Rangers (MLB), who play at Globe Life Field and won the World Series in 2023, and the Dallas Wings (WNBA), who play at College Park Center. MLS team FC Dallas plays at Toyota Stadium in Frisco and won the Lamar Hunt U.S. Open Cup in 1997 and 2016. The newest team in Dallas is Dallas Trinity FC, the first professional women's soccer team that plays at the historic Cotton Bowl (stadium). The city is home to several minor league and college sports programs in the area.\nSince joining the league as an expansion team in 1960, the Cowboys have enjoyed substantial success, advancing to eight Super Bowls and winning five. The Cowboys are financially the most valuable sports franchise in the world, worth approximately $4 billion. In 2009, they relocated to their new 80,000-seat stadium in Arlington, which was the site of Super Bowl XLV and is set to host the most matches during the 2026 FIFA World Cup. The Cowboys are currently part of the East Division of the National Football Conference (NFC).\nThe Texas Rangers won the American League pennant in 2010, 2011 and 2023, and won the World Series in 2023. The franchise relocated from Washington D.C. in 1972. They play in the West Division of the American League.\nThe Dallas Mavericks joined the league as an expansion team in 1980. They won their first National Basketball Association championship in 2011 led by Dirk Nowitzki. They play in the Southwest Division of the Western Conference.\nThe Dallas Stars moved to North Texas in 1993 as a relocation from the former team, the Minnesota North Stars. The Stars have won eight division titles in Dallas, two Presidents' Trophies as the top regular season team in the NHL, the Western Conference championship three times, and in 1998–99, the Stanley Cup. The team plays in the Central Division of the Western Conference.\nFC Dallas play at Toyota Stadium (formerly FC Dallas Stadium and Pizza Hut Park), a stadium that opened in 2005. They currently play in MLS's Western Conference. The team was originally called the Dallas Burn and used to play in the Cotton Bowl. Although FC Dallas has not yet won a MLS Cup, they won the Lamar Hunt U.S. Open Cup in 1997 and 2016 and the Supporters' Shield in 2016. Previously, the Dallas Tornado played in the North American Soccer League from 1968 to 1981.\nThe Dallas Wings came to The Metroplex in 2016 after relocating from Tulsa.\nThere are many notable minor league teams in the Dallas-Fort Worth. The Allen Americans are a professional ice hockey team headquartered at the Credit Union of Texas Event Center in Allen, Texas, which currently plays in the ECHL. They are the minor league affiliate of the NHL's Seattle Kraken. The team was founded in 2009 in the Central Hockey League(CHL). They have won 4 straight championships, 2 in the CHL (2012–13, 2013–14) and 2 in the ECHL(2014–15, 2015–16).\nThe Dallas Renegades are a professional football team in the UFL that plays their home games at Toyota Stadium.\nThe Dallas Sidekicks (2012) are an American professional indoor soccer team based in Allen, Texas, a suburb of Dallas. They play their home games in the Credit Union of Texas Event Center. The team is named after the original Dallas Sidekicks that operated from 1984 to 2004. The MLS-affiliated North Texas SC team is a member of MLS Next Pro and plays in Frisco at Toyota Stadium; it is the reserve team of FC Dallas. The Dallas Mavericks own an NBA G League team, the Texas Legends.\nRugby is a developing sport in Dallas and Texas in general. The multiple clubs, ranging from men's and women's clubs to collegiate and high school, are part of the Texas Rugby Football Union. Dallas was one of only 16 cities in the United States included in the Rugby Super League, represented by Dallas Harlequins. Australian rules football is also growing in Dallas. The Dallas Magpies, founded in 1998, compete in the United States Australian Football League.\nThe only Division I sports program within the Dallas political boundary is the Dallas Baptist University Patriots baseball team. Although outside the city limits, the Mustangs of Southern Methodist University are in the enclave of University Park. Neighboring cities Fort Worth, Arlington, and Denton are home to the Texas Christian University Horned Frogs, UT Arlington Mavericks, and University of North Texas Mean Green respectively. The Dallas area hosted the Final Four of the 2014 NCAA Men's Division I Basketball Tournament at AT&T Stadium. The college Cotton Bowl Classic football game was played at the Cotton Bowl through its 2009 game, but has moved to AT&T Stadium.\nThe Red River Showdown is an American college football rivalry game played annually at the Cotton Bowl Stadium during the second weekend of the State Fair of Texas in October. The game is played by the Oklahoma Sooners football team of the University of Oklahoma and the Texas Longhorns football team of the University of Texas at Austin. The 10,000-capacity Forester Stadium, which is used mainly for football and soccer, is also located in Dallas.\nDallas Trinity FC is the first professional women's soccer team in Dallas that plays at the historic Cotton Bowl (stadium) located in Downtown Dallas. Originally founded in May 2023 by the Neil family and managed by Chris Petrucelli, the club kicked off its inaugural season in August 2024 when they played Tampa Bay Sun FC, ending in a 1 v 1 tie. Following this match was two very significant matches for the club, the friendly match and home opener. The club played their friendly match vs FC Barcelona Femení where they lost 0-6 and the club's official home match was against DC Power FC where they tied 1-1.\nThe club finished the season 12–9–7, finishing third and getting eliminated by Tampa Bay Sun FC by the final score of 2–1 in the semi-finals of the USL Championship. Following its inaugural season, the teams parted ways with Pauline MacDonald and Gavin Beith.\nRecently, the team announced its State Fair Clasico Match during the Texas State Fair at Fair Park on October 18 vs Club América Femenil.\nMajor League Volleyball expanded to the Dallas market after announcing plans for a single, unified professional women's volleyball league with the former Pro Volleyball Federation (PVF) in 2025. The Dallas franchise of Major League Volleyball was officially named Dallas Pulse and confirmed Comerica Center in Frisco as its home court for their 2026 debut. In their inaugural season, the Pulse have clinched a postseason spot with Head Coach, Shannon Winzer, as they prepare to host the 2026 MLV Championship at Comerica Center.","score":19.64045859628254,"links":[]}]},"metadata":{},"timestamp":"2026-07-08T22:51:26.900Z"}