Search headlines

The States Try to Topple WarnerMount…Thus Begins the Local Antitrust Era

(Welcome to the “Most Important Story of the Week”, my bi-weekly strategy column analyzing the most important (but often not buzziest) news story of the last two weeks. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. Please subscribe.) Well, it looks like it’s time for another strategy column. Can I finally avoid writing about M&A? No, it seems I cannot. Admittedly, I’m a week early with this column, since I usually put it out every other week. But this news couldn’t wait. This will make three “Most Important Stories” in a row with a merger or acquisition as its centerpiece. First, Roku-Fox (an acquisition), then Comcast-NBCUniversal (a divestment!), and now the State AGs and the WGA’s lawsuits against Paramount’s pursuit of Warner Bros. Discovery (antitrust). M&A is usually the “most important” topic any given week, simply because a giant company merging or breaking up (or preventing those outcomes) can have the biggest impact on the streaming board. If you think about these companies as players in a game, changing the number of players is one of the biggest changes you can make. I shouldn’t really complain, either, since this lawsuit is very good news for customers and suppliers (econ speak for talent, workers and indie studios in Hollywood). So let me answer some questions about this potential trial, along with (shudder) making some heavily caveated predictions. I’ll also look at whether Hollywood must consolidate, whether or not the states can win, trouble at X-Box, Netflix’s YouTube binge, and more. Plus, I have five images that visualize this merger and the harm, including three brand new data looks you’ve never seen before. Subscribe Most Important Story of the Week - Can The States and the WGA Stop Hollywood’s Consolidation (Crisis)? If every other newsletter and news outlet is writing about the same story, I try to avoid writing about it as well, but I can’t ignore a story this consequential. The story of the last year was the fate of Warner Bros. Discovery, and this development potentially extends that saga into 2027. As I tried to figure out my angle, I realized, like my last column, I’m again faced with a series of questions. These questions, though, are much more forward-looking. Will the states win? Will the WGA win? If so, what happens to Warner Bros. Discovery? Either way, will this chill the market for future mergers? So you know what that means: predictions. About the future, no less, the hardest thing to predict.1 Just remember: nothing here comes with a guarantee. And the more confident someone is in their predictions, the less you should trust them. This situation is incredibly fluid, nuanced, uncertain and tenuous. So let’s try to explain what may happen. Question: Why File this Lawsuit? I’ll admit, a few months back, I was fairly pessimistic about the fate of this lawsuit. Rumors had started bubbling up that the state Attorneys General (in particular California) wanted to settle with either some minor divestments (usually CNN) or behavioral remedies. And that tracked for me: the states usually settle lawsuits, like the recent John Deere right-to-repair suit. Yet, they plan to fight this. (As they did the LiveNation-Ticketmaster monopolization trial and the Nexstar-Tegna merger.) Honestly, that also makes a ton of sense. Frankly, this move is just good politics for these State AGs. Most are still running for higher and higher office in blue states—some folks have emphasized that only Democratic AGs joined this suit, but given the Ellison/Trump ties, and fears of retribution, that tracks—and a high profile case like this will help them move up the electoral ladder, especially since Paramount and its leadership (the Ellisons, father and heir) have sided with the other side of the political aisle. That makes them unsympathetic to Democratic voters and Hollywood workers in particular. Why did this lawsuit happen? In addition to the very real concerns about industry consolidation, this is why. That said, I don’t think we would have seen this lawsuit for Netflix and Warner Bros., simply because they’re more sympathetic and aligned with Democrats. But those consolidation concerns are real. The “town”—meaning Hollywood and such—really is seeing the damage of mergers on this industry. That’s why the WGA also filed its own lawsuit in defense of workers as well. (Wildcard: What about Europe? Will they try to stop the deal, too? There have been some rumors out of the UK they may try to fight the deal, and UK enforcers just stopped a Getty Images-Shutterstock tie up, so there is precedence. This argument could go either way, though. On one hand, the EU doesn’t need to step in, cause they states are handling it. On the other hand, this could make the EU’s case easier. Just imagine if both sides coordinated. I’ll simply say, “We’ll see!”) Question: Will The State AGs or the WGA Win? Can the state AGs play David to Paramount-Skydance’s Goliath here? That’s really the whole thing, isn’t it? If you know this result, you could make a lot of money. When things are uncertain, it’s tempting to shrug and say, “Eh” meaning it’s a 50/50 proposition. I wouldn’t, though. When in doubt, you should expect that the merging parties succeed. AT&T did successfully buy Warner Bros., after all, and Disney bought Fox without any challenges. Many judges are extremely sympathetic to mergers, and I’d bet the state AGs get a judge who will allow the merger. (Even Obama-appointed judges often allow mergers.) As I understand it, we’ll see two main attacks. First, theatrical films. The AGs are arguing that, when it comes to share of box office and the number of both “wide releases” and blockbuster (or “tentpole”) films, the merging parties will have over 27% market share. Now, the Supreme Court once ruled from on high that any merger that exceeds 30% is presumptively illegal, but that’s guidance, not an ironclad bar. Still, the states will have to argue that this is close to having too much power, and with that power, this will likely further worsen the theater/studio splits in particular. Indeed, as Matthew Stoller pointed out, “just five studios are responsible for 95% of all blockbusters; if this merger goes through, then Paramount and Disney will control 60% of that.” So yes, movie studios will be very concentrated after this merger. Want me to visualize some of that? Well, here’s the share of films that grossed over $200 million at the domestic box office since 2022. (Note: this isn’t all films released in over 3,000 screens, but it is a good look at market power.) First, here are the 43 films by studio: Notice all the blue (Disney), orange (Universal), and purple (Warner Bros)? Yeah, those studios are powerful, and this combines Paramount with one of them. Here’s the look by studio and share of the films that grossed over $200 million: Now, if you look at that and also think, “Huh, should we break up Disney?” I’m with you. I’ve seen some folks poo-poo this idea that this is a real category, but it is! For an upcoming article, I’ve been pulling data on the share of top 100 films at the box office as a share of total box office, and it’s massive. Here’s the chart: (This analysis looks at The-Number’s top 100 films and total domestic box office each year.) To be clear, tentpoles make up 80.7% of the box office each year, so I do think it’s a genuine market. (To be clear, films grossing over $50 million make up 80% of the domestic box office, and films grossing over $100 million make up 64.1%.) I mean, the top 100 films at the box office make up 95% of each year’s grosses. Worse, the combined studios will likely cut output to flex that market power. Everyone can just look at what happened to Disney and Fox to see the precedent. (With fewer films, the remaining theaters have to give more for those few films that remain.) Here’s an image I’ve used a lot, the share of wide-release films from Disney and Fox over time: The AGs will also argue that this consolidation will also impact the cable industry. In this case, the consolidation is actually worse, but that environment is…complicated. Paramount will argue that the cable industry is shrinking. That said, predictions that cable will “go to zero” also don’t look very well supported by the data, as the declines are shrinking, meaning “cable” or “vMVPDs” will likely stabilize at some point. Can the state Attorneys General win on those two main arguments? I honestly don’t know. Again, I’d bet no, since history in general supports that, but it depends on the judge/jury and how they interpret the arguments. Notably, Paramount won’t face accusations about monopoly power in other areas, like streaming, news, sports rights, or vertical integration. I tend to disagree with leaving out sports rights, but I also see the appeal for a simpler case. The states also aren’t really pushing novel theories about labor harm either, which should help. (By the way, Sean McNulty at The Ankler wrote a great run through of potential options, and Capitol Forum also wrote a great paper on theatrical consolidation. Both these pieces predated the lawsuit. Matthew Stoller is also out with his analysis of the pros and cons of the case too.) In some ways, the WGA’s case is even stronger. Quoting Sean McNulty’s summary: “The WGA is citing WARNAMOUNT as crossing a 30% market share in multiple sectors, a number that the Supreme Court has precedent for deeming “presumptively anticompetitive” in a market. According to the WGA numbers, WARNAMOUNT would have represented: - 35% of film writing jobs between 2021 and 2024 - 36% of TV writing projects between 2022 and 2025 - 38% of overall deals between 2021 and 2024” Notably, antitrust enforcers did win recently in the Penguin-Simon & Schuster merger by focusing on labor impact, so don’t count this thinking out. (Wildcard: Will the states try to get a jury trial? Most likely no, they’ll let a judge handle it. If I’m them, though, I’d try to put this in front of a jury. Juries tend to understand monopoly power in a more realistic way than judges faced with legions of economists.) Question: What if They Win? What if They Lose?

Jul 15 • 4:48 PM EDT • Entertainment • entertainment.substack.com

How Burry’s Prediction-Market Bet and New Products Will Impact Flutter Entertainment (FLUT) Investors

Recently, reports emerged that Michael Burry has taken positions in DraftKings and Flutter Entertainment, framing them as a regulatory-focused investment amid growing attention on prediction markets as competitors to traditional sportsbooks. Flutter Entertainment’s work on its own prediction-market products highlights how the company is actively preparing for possible shifts in how sports-related wagering and forecasting are regulated and offered. We’ll now examine how Flutter’s...

Jul 11 • 10:18 PM EDT • Entertainment • simplywall.st

'Win-Now' 49ers Trend for Blockbuster Trade in Bold Prediction

Jul 11 • 9:03 PM EDT • Sports • sports.yahoo.com

Barkley Makes Blunt Playoff Prediction for Kings

Charles Barkley said the Kings need “a miracle” to return to playoff contention, despite praising Sacramento’s loyal fan base and acknowledging rookie Darius Acuff Jr.’s bright future.

Jul 11 • 7:03 AM EDT • Sports • sports.yahoo.com

2026 FIFA World Cup - Watch and Stream Live Matches

Stream live Men's FIFA World Cup 2026 matches and view the latest news, analysis, schedule, groups, odds, predictions, where to watch and more at FOX Sports.

Jul 10 • 7:38 PM EDT • Sports • foxsports.com

Federal judge denies Kalshi's request to override N.Y.'s gambling laws

The prediction market company is pushing back.

Jul 8 • 9:01 PM EDT • Politics • ny1.com

Prediction market betting would be authorized in NC’s new budget. What it means for sports betting

Tucked into the state budget is a proposal that could have massive implications for how prediction markets operate in North Carolina. Some lawmakers say it’ll create a new revenue stream. Others worry it’ll cost the state millions.

Jul 5 • 5:30 AM EDT • Sports • wral.com

Eagles 53-man roster prediction: Updated after spring practices

Here’s a look at how Philadelphia’s 2026 team could be shaping up.

Jun 29 • 4:36 PM EDT • Sports • sports.yahoo.com

UNC, NC State to get millions from sports betting; gambling deductions allowed in budget proposal

Not only would the tax on sports betting operators rise to 23%, but North Carolina would levy taxes on prediction market operators as well under proposals expected to be included in the state budget.

Jun 28 • 5:30 AM EDT • Sports • wral.com

Making Our Own Luck

We are cross-posting a piece that former NIH official Kris Willis wrote for Macroscience. Kris is now the President and Founder of the Woodley Park Institute, for which I’m a board member. Picking winners or hedging bets? Federal science agencies have long wrestled with the question of how to ensure their billions of dollars of grants and contracts result in maximum benefits for Americans. On the surface, it might seem that a goal-oriented, interventionist style of management would be the best policy: prioritize our most pressing problems and distribute funding accordingly.This top-down strategy creates a unique hazard, though: bad choices can send resources in the wrong direction, resulting in slow progress that impedes the delivery of tangible benefits to citizens. Moreover, if decision makers pursue an applied advance when the underlying scientific principles remain poorly understood, they risk costly failures and a loss of support for the research enterprise at large. Examples include Nixon’s 1971 War on Cancer, undertaken on the premise that a cure could be achieved in less than a decade, the drive to build an operational commercial fusion plant by the mid-1990s, and the National Plan to Address Alzheimer’s Disease, which failed to produce the effective treatments and prevention strategies promised by 2025. The contrasting laissez-faire approach is to hedge your bets. If the path to an advance is impossible to predict, then the wisest choice might be to distribute funding to as widely as possible. The main risk of this strategy is that spreading funding thinly may limit the resources available to the most promising research, resulting in the same negative outcomes as the interventionist approach: limited support for the most promising topics, slow progress, and delayed returns. In reality, at science agencies like the National Science Foundation and National Institutes of Health, program managers navigate between these two extremes, setting some funds aside to target high-priority areas and using the rest to cover the widest possible range of meritorious proposals. This middle path seems like the most rational way to proceed, but it still requires making choices. How much should be set aside for high priority topics? What should those topics be? How should we define merit? Expert opinion can provide a helpful guide, but leading experts can have remarkably different opinions about what matters and what should be prioritized. Moreover, experts and administrators alike can be risk averse, giving an edge to high-profile, well-established concepts. What’s really needed is a data-driven framework to help guide decision-making, one that doesn’t simply repackage prestige or incumbency. Recognizing breakthroughs years in advance Many breakthroughs fail to attract funding or recognition at the earliest stages of development. Katalin Karikó, for example, spent years struggling to win grants for work on mRNA that would eventually win her and Drew Weissman a Nobel Prize. Similar stories can be told about Jim Allison’s groundbreaking studies leading to the development of cancer immunotherapy, Stan Pruisner’s demonstration that prions can self-replicate without DNA, or Robin Warren and Barry Marshall’s proof that Helicobacter pylori, not stress, causes ulcers. Yet at some point, the scientific community recognizes and responds to transformative breakthroughs like these. How does that change happen? And what if science funders could identify the areas that are on the cusp of a breakthrough? Those questions led my collaborators and me to study how scientists responded to past breakthroughs. Based on patterns in that data, we developed a means of predicting future breakthroughs, using biomedicine as a proof of concept. It’s worth taking a moment to describe how our approach works. Briefly, our prediction process begins by grouping the 18 million or so peer-reviewed papers in PubMed, the authoritative database of biomedical research, into roughly 50,000 unique topics. A small subset of these topics are so widely acclaimed as breakthroughs that they have been recognized with a major prize like a Nobel or a Lasker Award. We theorized that studying the development of these outliers over time, especially before they gained acclaim, was the key to identifying future instances of them. After defining topics, we chose 21 representative breakthroughs and asked what they looked like before they won prestigious prizes. To answer that question, we re-ran our topic-mapping algorithm repeatedly, winding back the clock one year each time, stringing together the years to follow the progress of each field as it grew and advanced. We found that in each case, the years leading up to a discovery followed a pattern: a burst of papers on a new, rapidly evolving topic, many of which quickly became influential. These characteristics—the percent of papers that are new, the percentage of papers that are brought in from other topics, and the influence of each individual paper—can all be measured separately for any given topic. Together, they act as a predictive signal that is detectable an average of five years before a transformative discovery is made, and up to thirty years before the discovery receives a major prize. Scanning the current research landscape for topics that display this signal allows us to predict what work will likely produce a future breakthrough. Each year we analyzed includes four or five signals, a number that appears to have remained constant across a twenty year time frame. In their classic work on the sociology of science, Bruno Latour and Steve Woolgar established that the desire to participate in a major discovery is an important motivator for scientists as they consider whether they should take up (or abandon) a research problem. Although further work is needed, the simplest explanation for our results is that this behavior is widespread enough to detect at scale. A foundational advance, or something like it, draws the attention of scientists and causes them to change the direction of their research. They vote with their feet, staking their own reputation and careers by publishing on and citing the new idea. That upswell of interest is the foundation of our breakthrough signal. What kind of research does our model identify as a breakthrough? After building a model based on the patterns in our 21 preselected breakthroughs, we tested it by identifying all early signals of discovery from 1994 through 1997. Of the 18 signals we found in that time period, 17 can be traced forward in time to a breakthrough. Examples include super-resolution fluorescence microscopy (see the image above), the directed evolution of proteins and enzymes (Chemistry Nobel, 2018), and sequencing the human genome (National Medal of Science, 2008). The discovery of the role of leptin signaling in obesity is a particularly interesting case study. Around 1950, scientists noticed the existence of a type of lab mouse that suffered from a unique inherited form of obesity. When given the freedom to choose their own diet, these mice ate more than normal and preferred food that was high in fat. Researchers had few clues as to why the animals overate; early experiments pointed to the existence of a soluble ob factor found circulating in the bloodstream that regulated appetite, but its identity was unknown. In 1994, Jeffrey Friedman and colleagues identified and sequenced the ob gene, noting that the protein it encoded appeared to fit the profile of a circulating factor. A year later, a trio of high-profile publications demonstrated that ob was a hormone that regulated body weight and fat deposition by regulating appetite. One of these was co-authored by Friedman, who christened it leptin from the ancient Greek word for thin. Using our model, the data from 1996 make it clear this advance would become a breakthrough. Scientists had flocked to study the biology of the new hormone, generating the flurry of new papers and citations required to produce a signal. One of these demonstrated that serum leptin concentrations reflected the amount of adipose tissue in the human body, providing clinical validation of the earlier mouse studies. Before the identification of leptin, scientists were unable to point to a specific molecule that controlled appetite and adiposity, so that it was impossible to rule out non-physiological causes of obesity; its characterization fundamentally changed our concept of weight gain. In 2010, Friedman and fellow pioneer Douglas Coleman were awarded a Lasker for the discovery. Our work also identifies breakthroughs in clinical practice and behavioral and social sciences, even though these areas are less likely to draw the attention of major prize committees. One example that falls into this category is the introduction of endovascular aneurysm repair, a minimally invasive surgical procedure for the treatment of abdominal aortic aneurysm, a leading cause of death among Americans over the age of 65. Relative to the previous standard of care, it reduces in-hospital mortality by almost four-fold. In 2017, Timothy Chuter received the American College of Surgeons’ prestigious Jacobsen Innovation award for his multiple refinements to the technique. Another under-recognized breakthrough identified by our model is the development of standardized survey instruments to assess the quality of life for HIV+ patients. The antiretroviral cocktails introduced in the mid-1990s reduced AIDS mortality, but treatment came with serious side effects. The new evaluations showed that patients whose disease progressed had worse physical functioning than Americans with other chronic diseases, while those who were asymptomatic maintained a health-related quality of life on par with the overall US population. This evidence made it possible for patients and activists to argue that even in the absence of a total cure, and in spite of the side effects, alleviation of symptoms was a worthwhile priority for clinicians. My colleagues and I have failed to identify any significant recognition for the physicians and health policy experts who pioneered this advance, although in 2016, researchers called for the World Health Organization to set targets for good health-related quality of life as part of its framework to end the AIDS pandemic. From forecasting to funding How should science funders use our predictions? Any serious discussion of what we should do with this new capability needs to begin with an understanding of its limitations. We can’t (and shouldn’t) invest all of our resources in the small number of topics predicted to produce breakthroughs. Innovative new fields are born from existing ones; they rarely arise de novo. If funders don’t maintain a diverse portfolio, the breakthroughs of tomorrow will have no antecedents. Think of this as eating the seed corn, or killing the goose that lays the golden egg. There are also multiple goals of funding beyond basic scientific discovery, including translating discoveries into clinical practice, developing new technologies, supporting economic development, and training new scientists. The investments needed to accomplish these goals are likely different from those required to support emerging breakthroughs. Finally, we must be aware that we may not capture every instance of a breakthrough. The concept is fuzzy, and not every significant discovery is recognized with a major award. Further, breakthroughs are rare, meaning that our dataset is, by necessity, small. This makes formal estimates of accuracy challenging. Although our overall success rate appears to be high, any one signal may turn out to be a false positive. We found one apparent example: the development of the third generation COX-2 inhibitors, Vioxx and Celebrex, which were much celebrated in the early 2000s as effective but non-addictive pain relievers, meets all the algorithmic criteria of a breakthrough. Five years after it received FDA approval, researchers demonstrated that Vioxx was associated with serious cardiovascular complications, and the manufacturer voluntarily pulled the drug from the market. Celebrex remains available, although like other NSAIDs, it carries an FDA warning for increased cardiovascular risk. Decision makers who were overly focused on the breakthrough potential of this research might have wasted substantial resources nurturing an area that ultimately proved to be a failure—but so would those who relied on expert opinion at the time. That said, the potential benefits of funding the next mRNA vaccine or cancer immunotherapy years earlier than we might have are large. When we can’t assume the outcome of an action, it’s worth conducting an experiment. Can targeted support for areas that are poised to produce a breakthrough increase the return on scientific investment without cannibalizing future advances? With the necessary administrative infrastructure in place, conducting this experiment would be straightforward. First, identify all the breakthrough signals between 2018 and 2023, select half at random, and commit to a decade of investment. For biomedicine, a six year window should yield about 30 topics with the potential to produce a breakthrough. Providing strong support to half of these might be accomplished for $300 million a year. That’s roughly half of the recent annual budget of the NIH Common Fund or around 20% of the fiscal year 2025 budget for ARPA-H. After five years, then again at ten, compare to see which group — the one that was actively managed, or the control — produced more breakthroughs, and on what timescale. Although we used biomedicine as an example, the same experiment could just as well be run for physics, materials science, or any other discipline. Any attempt to undertake such an experiment should keep three points top of mind. First, we can predict the topic of future breakthroughs, but the people and vision for how to move the work forward are still important. In practice, this means success requires active program managers with the expertise to develop the science and the authority to do so, including by recruiting investigators. Second, we would be wise to learn from the failures of past attempts to fund transformative research. High among these are funding modestly repackaged work, confusing the genuinely novel with the merely unfamiliar, and relying too much on incumbent investigators. All of these risks can be mitigated by thoroughly and intelligently integrating high quality data into portfolio management. Finally, we need to have patience. Even with strong funding support, producing a breakthrough takes time. If supporting breakthroughs is the best way to nurture the birth of new fields, we also need to accurately describe and properly manage the other two stages, so that we invest wisely throughout the productive lifetime of ideas and divest once they reach the point of diminishing returns. We would benefit from more study of all of these phases, especially the transition from one to another. More research could answer questions like: When does a breakthrough become an established field? How do the availability of funding, the size and characteristics of the available workforce, and the accumulation of evidence that disagrees with prevailing models affect a field’s decline? Exactly how do old ideas give birth to new ones, and can we speed up the process? The more we understand about the dynamics of scientific progress, the better we can maximize the odds that our curiosity leads to results. I’d call that finding a way to make our own luck.

Jun 25 • 4:48 PM EDT • Science • goodscience.substack.com