Fantasy Football 2026: AI Model Flags David Montgomery, James Cook as Top Bust Risks

With the 2026 NFL regular season just days away, fantasy football enthusiasts worldwide are deep into their draft preparations, meticulously strategizing to build championship-contending rosters. The stakes are high, and the difference between triumph and disappointment often hinges on identifying players who will exceed expectations and, critically, avoiding those who will fall short. In this high-pressure environment, a sophisticated computer model from SportsLine has emerged with its latest projections, pinpointing several high-profile players as significant bust candidates for the upcoming season, challenging many prevailing assumptions.

Quick summary

• A proven computer model from SportsLine has identified Houston Texans running back David Montgomery and Buffalo Bills running back James Cook as major bust risks for the 2026 fantasy football season.
• Despite carrying high average draft positions (ADPs), both Montgomery and Cook are projected to deliver significantly lower returns than their current market value.
• The model also issues a stark warning against one of the top six wide receivers currently being drafted, predicting a substantial underperformance relative to their cost.
• These predictions come from a system with a track record of accurately forecasting player performance, including Terry McLaurin's unexpectedly poor 2025 season.

Why it matters

For millions of fantasy football players, the annual draft is more than just a game—it's a significant investment of time, strategy, and often, money. A single 'bust' player, especially one taken in the early rounds, can derail an entire season, creating insurmountable gaps in team production and leading to frustration. Predictive models like the one from SportsLine offer a crucial advantage by providing data-backed insights that cut through media hype and conventional wisdom. Understanding which players are genuinely overvalued can help managers avoid catastrophic early-round mistakes, optimize their draft capital, and build more resilient rosters. In an increasingly competitive landscape, leveraging advanced analytics can be the difference between a championship run and a season spent languishing at the bottom of the standings. This shift towards data-driven drafting also reflects a broader trend in sports, where statistical analysis and algorithmic predictions are becoming indispensable tools for decision-making.

Background

Fantasy football has evolved dramatically since its early days, transforming from a niche pastime into a cultural phenomenon with millions of participants globally. Initially, managers relied heavily on personal intuition, sports commentary, and general team knowledge to make draft picks. However, the proliferation of data, advanced statistics, and computational power has ushered in an era of sophisticated predictive analytics. Tools like the SportsLine model represent the pinnacle of this evolution, leveraging extensive historical data and complex algorithms to simulate NFL seasons thousands of times over, generating projections for individual player performance.

This particular model has built a formidable reputation through its consistent accuracy. Last year, for the 2025 season, it notably predicted that Commanders receiver Terry McLaurin would fall significantly short of his top-50 ADP. McLaurin subsequently experienced career lows in receiving yards (582) and touchdowns (3), validating the model's warning and saving many fantasy managers from a costly mistake. Beyond McLaurin, the model successfully identified A.J. Brown as a sleeper in 2020, accurately projected Jonathan Taylor's breakout 2021 season, and foretold a step back for C.J. Stroud in 2024. Its track record also includes spotting past fantasy football sleepers such as Derrick Henry in 2019, Christian McCaffrey and Alvin Kamara in 2018, and Davante Adams in 2017. These successes underscore the growing reliability and impact of advanced analytical tools in fantasy sports, setting the stage for its 2026 predictions.

Identifying High-Profile Risks: Montgomery and Cook

David Montgomery: A Change of Scenery, a Drop in Value?

One of the most prominent names flagged by the SportsLine model as a bust for 2026 is Houston Texans running back David Montgomery. At 29 years old, Montgomery is transitioning to a new team after a productive stint in Detroit, where he was a significant touchdown scorer. Many fantasy analysts view his move positively, speculating that without sharing the backfield with a dynamic player like Jahmyr Gibbs, Montgomery might see an increased workload. However, the model paints a different picture, citing his integration into a 'less explosive offense' in Houston and the expectation of splitting snaps with rookie Woody Marks, who impressed with over 900 yards from scrimmage in his inaugural season.

Current ADP data places Montgomery around pick No. 51, typically a fourth or fifth-round selection. Yet, the SportsLine model places him in the same tier as much later-round picks such as Jaylen Warren, Jadarian Price, and even tenth-rounder Kenneth Gainwell. This stark discrepancy suggests that managers reaching for Montgomery at his current ADP are taking on considerable risk, potentially overpaying for a player whose new environment and competition may cap his fantasy upside significantly.

James Cook: Fumbling Concerns and Touchdown Vultures

Another running back drawing a 'bust' designation from the model is the Buffalo Bills' James Cook. Cook is currently being drafted with an average ADP around No. 10 overall, making him the fifth running back typically selected. This high valuation comes after two impressive seasons, including finishing as RB6 last year, understandably leading many to consider him a first-round talent. However, the SportsLine model presents a counter-narrative, ranking him as the RB10, placing him behind players like Derrick Henry and Chase Brown, and suggesting he should be a late-second or even third-round pick at best.

The model's concerns stem from several factors. Despite his impressive yardage totals, Cook's fumbling rate increased last season, a critical liability for high-volume players. Furthermore, he isn't considered an elite pass-catching threat out of the backfield, limiting his PPR (point-per-reception) ceiling. Perhaps most significantly, the omnipresent 'touchdown vulture' risk posed by quarterback Josh Allen, who frequently converts red-zone opportunities with his legs, consistently siphons potential rushing touchdowns away from Cook. These combined elements suggest Cook's high ADP is not justified by his projected output, making him a risky proposition at his current draft cost.

The Unnamed Wide Receiver: A Top Target to Avoid?

Beyond the specific running back predictions, the SportsLine model has issued a broad warning concerning one of the first six wide receivers typically selected in early 2026 fantasy drafts. While the specific player remains unnamed in the publicly released details, the model ranks this receiver barely within the top 10 at the position and anticipates them being one of the biggest busts in the league this year. This type of prediction is particularly impactful, as early-round wide receivers are often foundational pieces for fantasy rosters, commanding significant draft capital.

Missing on a top-tier wide receiver can be devastating for a fantasy team, forcing managers to scramble for replacements and potentially undermining their entire offensive strategy. The model's insight suggests that even among the presumed elite, there are hidden risks that human evaluators might overlook, influenced by name recognition, past performance, or media narratives. Identifying this unnamed bust would provide a monumental advantage, allowing managers to pivot to other high-value receivers or invest in different positions with greater certainty.

Qnews24h insight

The increasing sophistication of predictive analytics in sports, exemplified by models like SportsLine's, marks a pivotal moment in how we engage with and understand competitive events. These algorithms are not infallible, nor do they claim to be; rather, they offer a probabilistic framework that minimizes human biases and accounts for a broader array of data points than any single individual could process. The identification of players like David Montgomery and James Cook as potential busts underscores a crucial insight: historical performance and perceived talent, while important, must be critically re-evaluated against changing team dynamics, offensive schemes, and emerging talent. In a zero-sum game like fantasy football, where an edge is constantly sought, the cautious analytical perspective offered by these models serves as an invaluable counterpoint to hype, reminding us that past success doesn't guarantee future returns, and that calculated risk assessment, driven by data, is the most reliable path to sustained competitive advantage. The trend suggests that ignoring such data-driven warnings will only become riskier in the evolving landscape of sports analysis.

Sources

• CBS Sports

Frequently Asked Questions

What is a 'bust' in fantasy football?

In fantasy football, a 'bust' refers to a player who significantly underperforms relative to their average draft position (ADP) or the expectations set by their perceived talent and cost. For example, if a player is drafted in the second round but produces like a seventh-round player, they would be considered a bust. Identifying and avoiding busts is crucial for fantasy managers to maximize their team's potential.

How do predictive models identify fantasy football busts?

Predictive models, like the one used by SportsLine, analyze vast amounts of historical data, including player statistics, team performance, coaching changes, strength of schedule, injury histories, and more. They use complex algorithms, often incorporating machine learning, to simulate future outcomes thousands of times. By comparing a player's projected performance against their current average draft position (ADP), these models can flag players who are likely to be overvalued and thus represent a 'bust' risk.

Should I completely avoid players identified as busts?

Not necessarily. While a player identified as a bust carries significant risk at their current ADP, it doesn't mean they will have zero fantasy value. The model's warning suggests they are overvalued relative to where they are being drafted. Savvy fantasy managers might still consider them if they fall significantly lower than their ADP, or if they have a strong understanding of specific situational factors that the model might not fully account for. The key is to understand the risk and adjust your draft strategy accordingly, rather than blindly following consensus rankings.

What is the significance of a player's ADP?

Average Draft Position (ADP) is a critical metric in fantasy football, representing the average pick number at which a player is selected across various drafts. It reflects the collective market value and consensus expectation for a player. A high ADP means a player is expected to perform well and is drafted early. Understanding ADP helps managers gauge when to target players, identify value (players whose actual production is expected to exceed their ADP), and, conversely, spot potential busts (players whose projected production is below their ADP).