STRATEGY CENTRAL
For and By Practitioners
By Micah Smith - January 11, 2025
"In war, just as in poker, you must play the cards you are dealt." - General George S. Patton
"The best strategies are based not on what we want to happen, but on what is likely to happen." - Garry Kasparov
"The game does not reveal its secrets to those unwilling to study its patterns." - Doyle Brunson
Introduction- More Than a Game
In the realms of irregular warfare, financial markets, and high-stakes poker, decision-makers navigate environments defined by ambiguity and contested advantage. Whether a military commander operates in the gray zone, a trader positions through market uncertainties, or a poker professional exploits subtle edges, success depends on optimal decision-making with incomplete information while facing adaptive opponents. Modern irregular warfare extends beyond traditional operations into competition and deterrence, where actions and intentions remain deliberately ambiguous—much like the strategic concealment and revelation of information in both poker and financial markets.
It isn't just a game; it's a battlefield of wits, strategy, and calculated risks. From smoky saloons in the Old West to online tournaments with players spanning the globe, poker has transformed from a game of chance into a science where the best players leverage mathematics and psychology to outwit their opponents. Similarly, irregular warfare has evolved beyond traditional conflict into a complex spectrum of competition and deterrence, while financial markets have progressed from simple exchange floors to sophisticated algorithmic trading environments. Mastering strategic decision-making in these uncertain domains requires understanding how theories of optimal play, risk management, and adaptation apply across all competitive spaces. The evolution of strategic theory, particularly through game theory and mathematical optimization, illuminates parallel developments across military and market strategy - three domains where practitioners must master the art of decision-making in environments where nothing is certain and everything is contested.
The Origins of Poker as Strategic Competition
Poker comes in many variations, from 4-card Omaha to PLO 8 or better, 7-card stud, razz, and no-limit hold'em. While the rules differ, the fundamental principle remains constant: exploiting opponents' mistakes for advantage. This mirrors the varied domains of irregular warfare – which has all the complexities of traditional warfare but with an asymmetry of at least one irregular actor; these span from information operations to full proxy conflicts - and the diverse instruments of financial markets, from derivatives to currencies to commodities. All three domains operate on the principle of strategic competition, where success depends on exploiting adversary weaknesses while protecting against exploitation of one's own.
At its core, this competitive dynamic represents a zero-sum game, where one participant's gain equals another's loss. This fundamental characteristic is shared across domains, whether it's market share in economic competition, influence in irregular warfare, or capital in financial markets. While some engage in these arenas as hobbyists, others have made careers out of mastering these competitive spaces.
There is controversy regarding the exact date poker began, as some historians believe there could be a trace back to the 10th century from a domino card game played by Chinese emperors. Others believe some of the first traces of it came from a Persian card game, As Nas, which dates back to the 16th century. The closest European descendant was Poque, which gained popularity in France during the 17th century. French colonists brought Poque to their settlements in North America. English-speaking settlers made changes to Poque and coined it Poker, adding features of the modern game, including five cards for each participant and by 1834, a 52-card deck. From New Orleans, it spread throughout the US. In the 1870s and 1880s, it became an attraction in West saloons in frontier settlements. Texas Hold 'em became popular in the 1970s when it was the feature game during the World Series of Poker, the biggest yearly poker competition globally.
The Evolution of Strategy
When poker, specifically limit hold'em, took off in 1970, the tournaments available during the series were significantly low in both numbers and entries. The first Main Event in 1970 had just 6 entries. By comparison, the 2024 Main Event had 10,112 entries. This exponential growth parallels similar military operations and financial market revolutions—the increasing sophistication of modern irregular warfare and the rise of quantitative trading approaches.
Figure 1: WSOP Main Event Participation Growth (1970-2024). The graph illustrates the dramatic transformation of poker's competitive landscape. The sharp uptick following Moneymaker's 2003 victory (from approximately 800 to over 2,500 entries) marks a key inflection point in poker's evolution from niche competition to mainstream strategic pursuit. Note the sustained growth through the early 2000s, followed by market maturation and stabilization - a pattern often seen when new strategic paradigms emerge in competitive domains.
The dramatic increase in entries around the early 2000's stems from Chris Moneymaker's unprecedented run in 2003. Here was an amateur player who won a satellite online for $50 - tournaments where usually the top 10% of a field receive free entries into higher buy-in tournaments - and went on to outlast 839 entrants to win $2,500,000. The statistical likelihood of this happening was 0.12%, essentially lottery odds. Yet Moneymaker's victory catalyzed a transformation in competitive poker that mirrors similar paradigm shifts in warfare and markets.
The "Moneymaker Effect" demonstrates how rapidly competitive landscapes can transform. Everyone wanted to play poker, so the WSOP was advertised on ESPN, and amateurs from all over the world piled in to have their chance at winning the main event. Tournament entries increased 300% the following year, followed by another 200% increase the year after. Similar revolutionary moments have transformed both military strategy—like the advent of hybrid warfare—and financial markets, with the rise of retail trading platforms.
Back in the 1970's and even today, Doyle Brunson is considered the godfather of poker. His books Super System and Super System 2 revolutionized how players thought about the game. When computers were not as advanced or widely distributed, information on profitable strategies in No Limit Hold'em was not easily accessible. Players needed to practice, lose, and learn from mistakes. The volume you could put in was limited - averaging 30 hands per hour live, whereas now playing online can allow you to theoretically play 300 hands per hour. What took years of live experience can now be gained within months online.
The next revolution came through game theory optimal strategies. In 2006, Bill Chen and Jerrod Ankenman published The Mathematics of Poker, proposing that using mathematics as a foundation for creating strategies would yield both increased profitability and better protection against exploitation. While mathematical formulas had been applied to poker previously, this was the first comprehensive framework for implementing mathematics throughout one's entire strategy. Many pros initially resisted, but the results proved transformative.
These developments led Carnegie Mellon University researchers to create Cepheus, the first GTO poker bot, in 2015. It proved that artificial intelligence could compete in complex game trees with incomplete information. GTO revolutionized training as companies developed software allowing players to practice against GTO bots, determine optimal preflop ranges, calculate bet sizing on different board textures, and mathematically optimize tournament decisions.
The rise of computational decision support systems marks a crucial evolution across all three domains. Just as poker software revolutionized training and analysis, military planners now employ sophisticated modeling for irregular warfare scenarios, while quantitative traders utilize complex algorithms for market analysis. However, in each domain, the challenge remains balancing systematic approaches with human judgment and adaptation to specific contexts.
Profitability in This New Era
The landscape of competitive advantage has evolved dramatically across poker, financial markets, and irregular warfare. While each domain maintains unique characteristics, common systematic edge identification and exploitation principles emerge. In poker, the path to profitability traditionally split between cash games and tournaments mirrors similar dichotomies in other competitive domains—the choice between steady, exploitable edges and high-impact opportunities.
Modern poker professionals utilize GTO solvers and extensive databases to identify and exploit mathematical edges - similar to how quantitative traders employ algorithmic analysis to find market inefficiencies. In irregular warfare, strategists must likewise balance persistent presence operations against decisive engagements, each requiring different resource allocation and risk management approaches.
Players can achieve profitability in today's landscape through the systematic application of GTO principles. Cash games offer consistent opportunities for edge exploitation against less-studied opponents. At blind levels $1/2 and $2/5, properly trained players can maintain profitable win rates through careful game selection and solid fundamentals. However, just as market edges erode through competition, poker edges require constant adaptation as player pools evolve.
Tournaments present a different challenge, more akin to asymmetric warfare operations or event-driven trading strategies. While the upside potential is higher, consistency is more difficult to achieve. Even the most skilled tournament players only cash about 30% of the time in live environments. This parallels success rates in special operations missions or discretionary trading strategies, where high potential reward comes with increased variance.
The key to sustainable profitability is understanding where true edges come from and how they deteriorate. Just as poker players must constantly adapt their strategies as player pools become more sophisticated, traders face evolving market efficiency, and military strategists confront adaptive adversaries. Success requires identifying current advantages and building systems that can evolve as competitors adapt.
This evolution has made traditional exploitative strategies less reliable. In poker, exploiting opponent tendencies, while potentially more profitable in specific situations, leaves one vulnerable to counter-adaptation. Similarly, in markets and military operations, overly predictable strategies invite exploitation. The solution increasingly lies in balanced approaches that combine unexploitable baseline strategies with targeted exploitation when clear advantages present themselves.
Managing Risk
Risk management in competitive domains extends far beyond simple position sizing or resource protection. Modern game theory optimal (GTO) approaches teach us that effective strategy requires systematically balancing three fundamental types of risk: risk to force (preservation of resources), risk to mission (ability to achieve objectives), and risk of inaction (cost of missed opportunities).
In poker, these risks manifest as:
Risk to Force: Bankroll preservation and sustainability
Risk to Mission: Ability to maintain profitable win rates
Risk of Inaction: Missing value betting opportunities or becoming exploitably passive
Financial markets demonstrate the same framework:
Risk to Force: Capital preservation and drawdown management
Risk to Mission: Ability to meet return objectives
Risk of Inaction: Opportunity cost of unutilized capital or missed trades
In irregular warfare, these risks are explicitly considered:
Risk to Force: Personnel and asset preservation
Risk to Mission: Ability to achieve operational objectives
Risk of Inaction: Loss of initiative or allowing adversary freedom of action
GTO solutions across these domains reveal a crucial insight: optimal strategy requires constantly balancing these three risks. Over-emphasis on any one type creates exploitable weaknesses:
Excessive focus on force preservation leads to missed opportunities and cedes initiative
Overemphasis on mission accomplishment can deplete critical resources
Overcompensating for inaction risk can lead to poor position selection and unnecessary exposure
The implementation of risk management frameworks requires sophisticated measurement and monitoring systems. Each domain has developed specific tools for this purpose:
In poker:
Position sizing based on stack-to-pot ratios
Range construction balancing value betting against protection
Bankroll management rules for different game types
Session stop-loss and win goals
Game selection criteria based on edge assessment
In markets:
Value-at-Risk models for position sizing
Portfolio optimization for risk-adjusted returns
Systematic rebalancing protocols
Drawdown management systems
Correlation analysis for diversification
In irregular warfare:
Force allocation models
Risk-adjusted operational planning
Resource optimization frameworks
Intelligence-driven threat assessment
Multi-domain contingency planning
The evolution from intuitive to quantitative risk management parallels the broader development of GTO approaches. Success in modern competitive environments requires sophisticated systems for measuring, monitoring, and managing these interrelated risks while maintaining strategic flexibility. Yet managing one's own risks represents only half the strategic equation - equally important is understanding how to impose costs on opponents.
Measuring Strategic Success Through Imposed Cost
In competitive domains, success often lies in achieving objectives and efficiently imposing costs on adversaries while minimizing our own expenditures. Irregular warfare strategists have long recognized that traditional metrics of success fall short when facing asymmetric adversaries. Similarly, poker players and market traders understand that victory comes from winning individual hands or trades and systematically forcing opponents into suboptimal positions that drain their resources over time.
Recent work in irregular warfare theory has developed more sophisticated frameworks for measuring strategic success in competitive environments. Maurice "Duc" DuClos's (2021) Time, Space, and Material (TSM) equation stands out for its applicability across domains. Originally developed to measure imposed costs in strategic competition, the framework provides valuable insights for analyzing strategic advantages in poker and financial markets.
DuClos's TSM equation provides a framework for understanding and measuring these imposed costs across competitive domains. By examining how actions force adversaries to expend time, sacrifice positional advantage, and consume material resources, practitioners can better evaluate strategic success in ambiguous environments.
Time represents both a resource and a constraint across all domains. In poker, a skilled player forces opponents into increasingly complex decision trees, creating pressure through timing and positioning that compounds with each street of play. Market traders impose temporal costs by forcing reactive rather than proactive decisions, creating urgency that leads to suboptimal execution. In irregular warfare, disrupting enemy decision cycles and forcing reactive operations creates cascading disadvantages that extend beyond any single engagement.
Space encompasses both physical and conceptual positioning. Poker players control space by denying profitable positions and forcing opponents out of their preferred ranges, much like how market makers control price levels and deny optimal entry points. In irregular warfare, space extends physical terrain to include virtual domains and areas of influence, where denying adversary freedom of movement imposes both direct and indirect costs.
Material costs transcend simple resource expenditure. When a poker player forces inefficient stack utilization or uncomfortable bet sizing decisions, they impose material costs that affect future hands even if they lose the current one. Traders who create capital inefficiency or adverse selection costs generate advantages that compound over time. In irregular warfare, forcing unsustainable operational tempos or depleting critical capabilities achieves strategic effects beyond tactical outcomes.
The power of the TSM framework lies in understanding how these elements interact. A poker player who controls the timing of decisions while dominating position and forcing inefficient resource use creates multiplicative disadvantages that far exceed the sum of individual costs. Market traders who can simultaneously pressure timing, positioning, and capital efficiency generate compound advantages that transform into sustainable edges. In irregular warfare, synchronizing temporal, spatial, and material pressure creates strategic effects that persist beyond individual engagements.
Understanding how to measure and impose costs across time, space, and material dimensions provides practitioners with concrete metrics for strategic success. Combined with the broader evolution of poker strategy, these frameworks offer several key lessons for practitioners across competitive domains.
Lessons for Strategic Competition
The evolution of poker strategy offers several key lessons for practitioners across competitive domains:
1. Information Processing and Decision Support The transition from intuitive to quantitative decision-making in poker mirrors necessary evolutions in military planning and financial trading. Modern competition requires sophisticated systems for processing incomplete information and making optimal decisions under uncertainty. Just as poker players use HUDs (Heads Up Displays) and database analysis to track opponent tendencies, traders employ market analytics to identify opportunities, and military planners utilize intelligence fusion systems to understand adversary patterns.
2. Adaptation Cycles As information becomes more widely available and competitors more sophisticated, the nature of edge exploitation must evolve. Sustainable advantage requires building systems that can identify and capitalize on new opportunities as old edges deteriorate. This principle applies whether tracking opponent tendencies in poker, market inefficiencies in trading, or adversary patterns in irregular warfare. The rate of adaptation has accelerated across all domains, requiring increasingly sophisticated response mechanisms.
3. Balance of Theory and Practice While GTO solutions provide theoretical optimal play, practical application requires understanding when and how to deviate based on specific circumstances and opponent tendencies. This balance between theoretical optimization and practical application remains crucial across all competitive domains. Pure GTO play may be unexploitable but could miss profitable exploitation opportunities against specific opponents or market conditions. The art lies in knowing when to deviate from theoretically optimal play to exploit specific weaknesses.
4. Edge Identification and Exploitation Success in modern competition requires systematic approaches to identifying, verifying, and exploiting advantages while maintaining security against exploitation by adaptive opponents. The rise of solver technology in poker demonstrates how computational power can help identify these edges, similar to how quantitative analysis identifies market opportunities or intelligence analysis reveals operational advantages. However, the human element remains crucial in interpreting and applying these insights.
5. Resource Optimization Success depends on optimal resource allocation across multiple opportunities and timeframes in all domains. Just as poker players must manage their bankrolls across different games and stakes, military planners must allocate forces across different operations, and traders must optimize capital deployment across various strategies and markets.
Integrating these lessons with domain-specific expertise creates powerful frameworks for strategic decision-making. The challenge lies in adapting these principles to specific contexts while maintaining their fundamental insights.
Conclusion
The transformation of poker from a game of chance and intuition to one of mathematical precision offers valuable insights for practitioners across competitive domains. Whether in card rooms, financial markets, or irregular warfare, success increasingly depends on sophisticated systems for processing information, making optimal decisions, and adapting to evolving conditions.
GTO concepts have revolutionized strategic decision-making under uncertainty. The balance between exploitation and unexploitability, the importance of position and initiative, and the critical role of resource management apply universally across competitive domains. Understanding how poker theory has evolved to address these challenges provides valuable insights for practitioners in all fields.
The resources available today - from poker solvers to market analytics to operational planning tools - allow practitioners to build robust strategies before committing resources. From the mathematical foundations laid by pioneers like Doyle Brunson to modern GTO theorists like Michael Acevedo, the evolution of poker strategy demonstrates how systematic approaches can transform competitive practices.
Moreover, the three fundamental risks - to force, mission, and inaction - provide a framework for evaluating strategic decisions across domains. Understanding how these risks interact and developing systems to manage them effectively is crucial for sustained success in any competitive environment.
The challenge now is to adapt these lessons to specific domains while maintaining a balance between theoretical optimization and practical application. As competition in all domains becomes increasingly sophisticated, the principles developed through poker theory become increasingly relevant. The future belongs to those who can effectively combine quantitative analysis with practical judgment, systematic processes with tactical flexibility, and strategic patience with decisive action.
References
Acevedo, M. (2019). Modern Poker Theory: Building an unbeatable strategy based on GTO principles. D&B Publishing.
Chen, B., & Ankenman, J. (2006). The Mathematics of Poker. ConJelCo LLC.
Brunson, D. (1979). Doyle Brunson's Super System: A Course in Power Poker. Cardoza Publishing.
Brunson, D. (2004). Doyle Brunson's Super System 2: A Course in Power Poker. Cardoza Publishing.
DuClos, D. (2021). Measuring Imposed Cost in Strategic Competition: The TSM (Time, Space, Material) Equation. Online lecture presented to the Donovan Group, February 10, 2021.
History.com Editors. (2018). Where did poker originate from? Retrieved from https://www.history.com/news/where-did-poker-originate
The Irregular Warfare Initiative. (2022). Time, Space, And Material: Metrics For Assessing Irregular Warfare. Irregular Warfare Podcast. Retrieved from https://irregularwarfare.org/podcasts/time-space-and-material-metrics-for-assessing-irregular-warfare/
Lo, A. W. (2017). Adaptive Markets: Financial Evolution at the Speed of Thought. Princeton University Press.
Schelling, T. C. (1960). The Strategy of Conflict. Harvard University Press.
Spulak Jr, R. G. (2007). Innovate or Die: Innovation and Technology for Special Operations. Joint Special Operations University.
Waldman, T. (2018). Special Operations and Strategy: From World War II to the War on Terrorism. Routledge.
Additional Thanks
The author would like to thank Maurice “Duc” DuClos from the Naval Post Graduate School (NPS) for his input on the connections with Irregular Warfare and the integration of the connection between GTO and Poker to IW. Duc continues to be one of the leading thinkers in the IW field and sees connections across others as well. His TSM Equation and 3 Risks framework were especially useful in this article.
About the author
Micah Smith is a seasoned professional with a diverse background spanning military service, professional poker, trading, and sales. After serving six years in the United States Air Force, specializing in avionics engineering and technology, Micah transitioned into the world of trading and poker, where he developed quantitative strategies for the S&P 500 and NASDAQ 100 markets while maintaining profitability as a professional poker player.
With experience in roles such as Sales Development Representative at FIS, Account Executive at Paysafe and Relationship Banker at Bank of America, Micah brings a unique blend of analytical, technical, and client-facing expertise. Currently focused on transitioning into a quantitative trading role, he combines his disciplined military foundation, strategic problem-solving skills, and a passion for data-driven decision-making to tackle complex challenges in dynamic environments.
Excellent article and approach. I look forward to more from this author!