DOWNLOAD ARTICLEThe advertisements are everywhere now. Between innings, during timeouts, scrolling through your social feed: the constant drumbeat of sports betting promotions has become the background noise of American life. Download the app. Place your bet. Feel the rush.
What we're witnessing isn't just a cultural shift in how Americans engage with sports. It's a large-scale behavioral experiment playing out in real time, one that reveals uncomfortable truths about human psychology, risk perception, and the very nature of what we call “investing.”
And here's what concerns us most: the same cognitive machinery driving this betting explosion operates identically in the listed equity markets. The dopamine. The overconfidence. The narrative-driven decision-making. The inability to distinguish between being smart and being lucky.
The listed markets are built on vague and ambiguous information. Investors believe they're making informed choices, but they're often gambling with educated guesses.
The numbers behind the noise
Let's be clear-eyed about what's happening.
U.S. sports betting advertising expenditure has surpassed $1.9 billion annually, fueled by legalization across 39 states and aggressive digital marketing campaigns. The industry has recruited athletes, celebrities, and influencers to normalize what was, until recently, an activity confined to Las Vegas and underground bookies.
But the advertising deluge tells only part of the story. The more troubling data sits beneath the surface.
A 2026 Common Sense Media report found that over one-third of adolescent boys are now gambling, primarily through sports betting and gambling-like mechanisms embedded in video games. Loot boxes. Skins betting. In-game currencies that blur the line between play and wagering. Nearly half of these young people encounter gambling content online without seeking it out.
Among 18-to-22-year-olds, 58% have tried sports betting at least once. On college campuses, 67% of male students report being active bettors. This isn't a fringe behavior. It's becoming a generational norm.
The consequences are predictable. At least 2 million American adults meet criteria for severe problem gambling. Another 4-6 million show mild to moderate problems. Nearly one in five problem gamblers attempts suicide, with young men representing the most vulnerable demographic.
In Maryland, the adult rate of persistent problematic gambling jumped 42%—from 4% to 5.7%—in under two years following legalization. The pattern repeats in state after state.
This is what happens when you combine sophisticated marketing, frictionless technology, and the basic architecture of human cognition.
The regulatory vacuum
What makes this moment particularly striking is the regulatory landscape—or rather, its absence.
The American Gaming Association has issued a voluntary Responsible Marketing Code. Most state regulations restrict only “false” advertising and require minimal responsible gaming disclosures. Time-based ad restrictions or comprehensive bans face First Amendment challenges that make meaningful reform unlikely in the near term.
Contrast this with the gambling itself, where the odds are at least transparent and known. When you place a bet on a football game, the probability structure is explicit. The house edge is calculable. You may lose, but you can understand precisely how the game is rigged against you.
Now consider the listed equity markets.
Here, the odds are opaque. Risk is often unpriced and unacknowledged. The vague and ambiguous information that drives stock prices creates exposures that investors cannot see, let alone calculate. They take on risk hoping for outsized rewards without understanding whether they're being compensated for the chances they're taking.
At least the casino tells you the rules.
The neuroscience of the bet
To understand why this matters for investors, we need to understand what's happening in the brain.
Behavioral research demonstrates that both investors and gamblers are driven by identical psychological impulses—the seeking of reward and excitement from risk itself. The dopamine surge occurs not only when winning but in anticipation of a potential win. Risk feels good regardless of outcome.
This is why sports betting apps are designed around continuous engagement. Micro-bets during games. On-demand odds that shift in real time. The constant promise that the next wager could be the one that pays off.
It's also why turbulent markets amplify speculative behavior. When uncertainty rises, the anticipation of potential gains becomes more intense, not less. People don't retreat from risk in volatile environments. They become more likely to behave like gamblers because the emotional reward—the feeling of possibility—intensifies with uncertainty.
The same mechanisms operate when an investor reads a compelling narrative about a growth stock, studies a chart pattern that “confirms” their thesis, or convinces themselves that this time is different. The dopamine doesn't distinguish between information and noise. It responds to the story, the possibility, the bet.
What You See Is All There Is. WYSIATI, is a behavioral phenomenon first described by Daniel Kahneman, Nobel Prize winner in Economics. The behavioral finance concept captures a fundamental truth: humans construct coherent narratives from incomplete information and then act as if those narratives represent reality. In gambling, this manifests as the “hot hand” fallacy. In investing, it manifests as confidence in growth stories that have no connection to sustainable value creation.
Behavioral risk: The risk you don't get paid for
Here's where the gambling analogy breaks down in a useful way. When you gamble, you know you're gambling. The environment signals risk. The house edge is disclosed. You enter with your eyes open, even if your behavior ignores the odds.
When you invest in listed equities, you often don't know you're gambling. The environment signals sophistication, analysis, informed decision-making. You receive research reports, earnings calls, analyst ratings—a veneer of information that suggests the market has priced risk appropriately.
But here's what's been missing: in gambling, the odds are known. In equity markets, they've been impossible to calculate—until now. Casinos can tell you the house edge is 5.26%. Equity research has only been able to offer forecasts and narratives about an unknowable future. That's not calculating odds. That's guessing.
The h-factor changes this. It calculates the probability a company will fail to deliver the growth already priced into its stock—using only known information. No forecasts. No narratives. Just the measurable gap between what the price implies and what the fundamentals support.
But humans overprice stocks by incorporating vague and ambiguous information into prices. They respond to narratives, momentum, and the behavior of other investors. They pay premiums for growth stories without understanding the probability that promised growth will materialize.
This creates what we call behavioral risk—risk that emerges not from company fundamentals but from human cognitive biases operating at scale. And here's the critical insight: this risk is uncompensated.
You do not get paid to take behavioral risk. It cannot be diversified away because human biases are correlated and systemic. When overpricing occurs across a sector or market segment, it doesn't matter how many positions you hold. You're exposed to the same underlying phenomenon: people collectively paying more than the fundamentals justify.
The market's biggest risk isn't the company—it's us.
The visibility problem
A professional gambler—and they do exist—understands something that most investors never grasp: the objective is not to predict outcomes but to identify mispriced odds.
If a sportsbook offers +150 on an outcome that should be priced at +120, the professional bets regardless of whether they expect to win that particular wager. They're betting on the edge, not the result. Over thousands of bets, that edge compounds.
The challenge in listed markets is that the “odds” are invisible. What should a stock be worth? What is the probability that projected earnings growth will materialize? What premium, if any, is justified for the narrative driving current enthusiasm?
Traditional analysis attempts to answer these questions through forecasting—projecting cash flows, estimating terminal values, building models that extend indefinitely into an unknowable future. But forecasting introduces precisely the vague and ambiguous information that creates behavioral risk in the first place.
You cannot eliminate human bias by deploying more human judgment.
This is why we approach the problem differently. Rather than asking “which stocks will win,” we ask “which stocks carry uncompensated risk that their price cannot justify.” We use only known, quantifiable information—data that exists in the present, not projections about the future. We measure the probability that current prices already incorporate growth expectations that are unlikely to be met.
The h-factor quantifies this behavioral risk. It allows us to see which stocks carry the highest probability of failing to deliver the growth their price indicates. We remove them systematically. We aim to avoid losses that other investors accept unknowingly.
It's not about outsmarting the market. It's about protecting what matters—by being less wrong, more often.
What the betting boom teaches us
The explosion in sports betting reveals several truths that serious investors cannot ignore.
First, human beings are poorly equipped to evaluate risk in the presence of compelling narratives. The betting apps understand this. They wrap every wager in storylines, statistics, and the promise of insight. They make you feel like a participant, not a mark. The listed markets do the same thing, just with more sophisticated packaging.
Second, ease of access dramatically amplifies behavioral vulnerabilities. Frictionless betting through mobile apps has transformed casual sports fans into regular gamblers. Similarly, zero-commission trading platforms and fractional shares have made it trivially easy to act on impulse in equity markets. The barriers that once forced a pause—the time to call a broker, the minimum investment thresholds—have vanished.
Third, regulatory frameworks lag technological and behavioral change by years, sometimes decades. The betting industry has moved faster than regulators can respond. The same pattern played out with meme stocks, SPACs, and the crypto speculation that wiped out billions in retail wealth. By the time protections emerge, the damage is done.
Fourth, the populations most at risk are those with the least experience and the highest exposure to marketing. Young men dominate both problem gambling statistics and speculative trading losses. They're targeted precisely because they're susceptible.
A different kind of discipline
We are not anti-gambling in any moralistic sense. Adults make choices about how to spend their money and time. What concerns us is the category confusion—the belief that gambling behaviors, dressed in the language of analysis and information, constitute investing.
New Age Alpha isn't here to pick winners. It's here to help you avoid the losers—systematically, transparently, and without prediction.
This distinction matters because it fundamentally changes the objective. We're not trying to identify the next breakout growth story. We're not chasing momentum or timing entries. We're measuring the probability that human behavior has created uncompensated risk and then removing the stocks where that probability is highest.
The uncomfortable question
The betting boom forces an uncomfortable question for anyone with capital at risk in listed markets: How much of what you call “investing” is actually gambling dressed in better clothes?
When you buy a stock because the growth story resonates, because the product seems innovative, because the CEO speaks compellingly about the future—are you making an informed decision based on quantifiable information? Or are you responding to a narrative, seeking the dopamine reward of possibility, taking risk that feels smart but carries no actual compensation?
The result is a portfolio that doesn't rely on being right about the future. It relies on avoiding the mistakes that humans make when they believe they know the future.
Our research has shown that, within the S&P 500 from 12/31/01 through 12/31/25, stocks in the lowest quartile of h-factor scores outperformed those in the highest quartile in approximately 70% of quarterly periods. This isn't a prediction. It's a probability edge, observed consistently across market conditions, arising from a disciplined process of risk removal.
The uncomfortable mirror
Here's what makes this parallel so uncomfortable for the investment industry: the same psychological mechanisms driving the betting boom are present in how many people approach the stock market.
Consider how modern retail investing has evolved. Commission-free trading apps with gamified interfaces. Push notifications about “trending” stocks. Social media communities where anonymous users tout their latest picks. The dopamine hit of watching positions move in real time. The fear of missing out on the next meme stock rally.
The packaging is different, but the underlying psychology is remarkably similar to what's happening in sports betting. Both involve:
- Uncertain outcomes presented as solvable puzzles. Sports bettors believe they can find an edge through superior knowledge of teams and matchups. Stock pickers believe they can identify winners through superior analysis. Both vastly overestimate their ability to predict outcomes in complex, dynamic systems.
- The illusion of control. Placing a bet or executing a trade creates a false sense of agency over inherently uncertain outcomes. The act of making a decision feels like influencing the result.
- Selective memory and narrative construction. Winners remember their successful picks vividly. Losses get attributed to bad luck or external factors. Over time, this creates a distorted sense of skill that keeps people engaged.
- The conflation of entertainment with strategy. The excitement of watching your positions—whether a parlay or a portfolio—creates emotional engagement that gets confused with informed decision-making.
This isn't a critique of individual intelligence. It's a recognition that human beings are wired in ways that make us vulnerable to these patterns. The dopamine response doesn't distinguish between a sports bet and a stock trade. Both trigger the same reward pathways, especially when outcomes are uncertain and stakes are meaningful.
Oversight in a rapidly expanding market
What's striking about the current betting landscape is how quickly commercialization has outpaced protection. According to the American Gaming Association, sports betting is now legal in 39 states, with over $1.9 billion spent on advertising in recent years to capture market share. Yet regulatory frameworks remain fragmented and largely reactive.
Most state regulations only address “false” advertising and mandate responsible gaming disclosures—the financial equivalent of putting “past performance is not indicative of future results” at the bottom of a mutual fund advertisement. These warnings are technically present but practically invisible to the target audience.
The industry's voluntary Responsible Marketing Code offers guidelines, but self-regulation has an inherent conflict of interest. When customer acquisition costs are high and competition is fierce, the incentive is to push boundaries, not reinforce them.
Meanwhile, the populations most vulnerable to gambling-related harm are precisely those most exposed to aggressive marketing. According to research from McGill University and the National Council on Problem Gambling, young people—especially young men—face elevated risk, as do those with prior mental health challenges or family histories of addiction. The Common Sense Media 2026 report found that over one-third of adolescent boys are already gambling, many through sports betting or gambling-like mechanisms in video games.
This isn't just a policy concern for betting regulators. It's a warning signal for anyone who cares about financial literacy and the long-term health of capital markets. If a generation is being conditioned to view risk-taking through the lens of sports betting entertainment, what assumptions will they bring to investment decisions?
The problem with “picking winners”
At New Age Alpha, we've spent years studying a particular form of risk that doesn't appear in standard financial models: the risk created by human behavior itself.
Traditional finance assumes that markets efficiently incorporate all available information into prices. If this were true, there would be no systematic way to identify mispriced securities. Some academics still defend this view.
Behavioral finance emerged as a correction, documenting the many ways human cognition deviates from pure rationality. Anchoring, confirmation bias, loss aversion, overconfidence—the catalog of cognitive errors is now well-established.
But identifying biases isn't the same as building a systematic approach to managing them. Most behavioral finance remains descriptive rather than prescriptive. It tells us why people make mistakes without providing a reliable method for avoiding them.
Our approach starts from a different premise: rather than trying to identify which stocks will win, we focus on identifying which stocks carry the highest probability of disappointing relative to the expectations embedded in their current prices.
This may sound like a subtle distinction, but it represents a fundamentally different philosophy. The winner-picking mentality assumes you can see what others cannot—that your analysis, your insight, your edge will reveal undervalued opportunities. This is the sports bettor's mindset applied to securities. It feels empowering but is statistically unreliable.
The loser-avoiding mentality accepts the limits of prediction. It acknowledges that markets are complex systems where outcomes depend on countless variables, many of which are unknowable in advance. Rather than pretending we can see the future, we ask a simpler question: which stocks are priced in ways that require events to unfold exactly as consensus expects?
Vague and ambiguous information
Here's where the betting analogy becomes particularly instructive.
In a casino, the odds are transparent. You know the house edge on blackjack, the expected return on a slot machine, the probability distribution of roulette. You may still choose to play, but you do so with full knowledge of the underlying mathematics.
In sports betting, the odds are less transparent but still calculable. Bookmakers set lines based on sophisticated models. Skilled bettors can identify situations where the posted odds diverge from their own probability estimates. There's genuine information in the marketplace, even if most bettors lack the expertise to exploit it.
In equity markets, the situation is fundamentally different. Stock prices incorporate not just known, quantifiable information but also what we call “vague and ambiguous information”—expectations about future growth, narrative-driven enthusiasm, fear of missing out on transformative trends.
When a company's stock price implies years of above-average growth to justify its current valuation, investors are effectively betting on a specific future unfolding. But unlike casino odds or sports betting lines, the probability of that future is genuinely unknowable. It depends on competitive dynamics, technological evolution, macroeconomic conditions, regulatory changes, management decisions, and countless other variables that cannot be reliably forecast.
This creates what we consider uncompensated risk—risk that investors bear without being paid for taking it. In traditional risk/return frameworks, higher risk should mean higher expected returns. But when stocks are overpriced due to behavioral factors, investors may be taking substantial risk with negative expected excess returns.
The investor who buys an overpriced stock isn't necessarily wrong in their fundamental thesis. The company may indeed have excellent products, talented management, and favorable market position. The problem is that all of this may already be reflected—and then some—in the current price. You can be right about the company and still lose money on the stock.
The h-factor® approach
Our response to this challenge is the h-factor: a systematic, quantitative measure designed to identify stocks with the highest probability of failing to deliver the growth their prices imply.
The methodology draws on actuarial science rather than traditional security analysis. Actuaries don't try to predict when any individual will die. They quantify probabilities across large populations based on observable, measurable characteristics. This approach acknowledges uncertainty while still providing useful, actionable information.
Similarly, the h-factor doesn't predict which specific companies will disappoint. It identifies which stocks carry characteristics associated with higher failure probability. By systematically removing high h-factor stocks from a portfolio, investors can reduce their exposure to behavioral risk without claiming any forecasting ability.
The evidence suggests this approach works as our research has shown that within the S&P 500 from 12/31/01 through 12/31/25, stocks in the lowest quartile of h-factor scores outperformed those in the highest quartile in approximately 70% of quarterly periods. We believe that this gives us a consistent probability edge that compounds over time.
This isn't about being smarter than other investors. It's about being more systematic in acknowledging what we can and cannot know. We don't try to pick the winners. We aim to avoid the losers.
What the betting boom should teach investors
As I watch the sports betting industry evolve, several observations seem relevant for investors:
First, marketing is not education. The billions spent on betting advertising are designed to drive customer acquisition, not to help people make informed decisions. The same is often true in investment marketing. Glossy materials, confident forecasts, and compelling narratives are tools of persuasion, not analysis.
Second, entertainment and strategy are different things. There's nothing wrong with enjoying the excitement of watching markets or following your positions. But mistaking that emotional engagement for informed decision-making is a recipe for disappointment. The gambler who “loves the action” and the investor who checks positions compulsively may be experiencing the same psychological phenomenon.
Third, transparency about odds matters. The betting industry's lack of clear communication about actual expected returns contributes to problematic behavior. Investors deserve similar transparency about the probability-weighted outcomes of their strategies, not just best-case scenarios or selective historical returns.
Fourth, the most vulnerable populations often receive the least protection. Young people being marketed sports betting today will become investors tomorrow. The habits and assumptions they form now will shape their financial decisions for decades.
Fifth, self-regulation has limits. Both the betting and investment industries have powerful incentives to maximize customer engagement. External oversight and clear standards are necessary complements to voluntary codes of conduct.
Discipline in the face of human bias
The betting boom reveals something important about human psychology: we are drawn to uncertainty in ways that aren't always rational. The prospect of reward activates powerful neural circuits that evolved for survival, not statistical analysis.
This isn't a character flaw. It's a feature of how our brains work. But features can become bugs when the environment changes faster than our cognitive adaptations.
The investment industry faces a choice. We can exploit these tendencies, designing products and experiences that maximize engagement regardless of outcomes. Or we can build approaches that work with human psychology rather than against it—approaches that acknowledge our limitations and create systematic protections against our own worst impulses.
At New Age Alpha, we've chosen the second path. Not because we're immune to behavioral biases—no one is—but because we believe sustainable investment success requires humility about what can and cannot be predicted.
The listed markets are built on vague and ambiguous information. Investors believe they're making informed choices, but they're often gambling with educated guesses. The difference between intentional gambling and accidental gambling is that the former at least involves a conscious decision about risk.
It's not about outsmarting the market. It's about protecting what matters—by being less wrong, more often.
Sources:
- American Gaming Association, Responsible Marketing Code and industry data
- Common Sense Media, 2026 report on adolescent gambling behavior
- Gitnux Marketing, sports betting advertising and demographic trends
- Harvard Law Journal of Sports and Entertainment Law, regulatory analysis
- McGill University Youth Gambling Research Program
- National Council on Problem Gambling, prevalence and risk factor research
- STAT News and USC Center for Health Journalism, public health reporting on problem gambling
- U.S. state regulatory frameworks for sports betting advertising
