Over the last several months, the AB Formula has undergone a significant transformation, assigning different weights to variables that were previously unaccounted for in calculating an individual score. That said, the overall premise of AB remains the same- identify undervalued contributors who help their clubs by working harder, making better decisions, and elevating their teammates by putting them in better positions to succeed (more on the methodology, formulas, and rationale can be found here The Intersection of Data Analytics and Managerial Philosophy in Professional Hockey – hockey free for all.com (HOME OF THE ADVANCED BRACTON)). As the metric has evolved and I’ve developed as a young professional seeking an opportunity to begin a career in the hockey industry, I’ve identified the agency sector of the business as the area where my research can be most practically applied and have the greatest immediate impact. The outline below serves as a tailored presentation to the agents of hockey players around the world, as implementing the AB Score and its corresponding family of metrics into your firm has serious earnings potential, in addition to the innovation opportunity that comes from being on the cutting edge in a relatively untapped market using hockey analytics at levels of the game below the NHL. I believe there’s substantial room for growth as an industry to leverage statistics to identify talented players at any age, then develop them through a coordinated system towards successful NHL careers.

I want to reiterate, as I have in many studies on this website, that my work isn’t intended to replace traditional scouting methods that have historically been the industry’s foundation. Instead, it aims to complement and modernize these methods by optimizing time allocation, giving us direction for concentrating our attention on specific areas and projects. As a Ph.D. candidate at Concordia University Chicago, my research into this field is ongoing; however, the underlying findings present a framework ready for application, and one I’m prepared to implement for your firm if you see the benefit in the description below. Please feel free to email me at bractonabellahockey@gmail.com with any interest. Thank you in advance for your consideration.

Why Identifying Decision-Makers Earlier Matters

As mentioned in the previous section, the AB managerial philosophy framework for scouting and player development is built on a simple belief: decision-making is the most transferable skill in hockey. Regardless of age, league, role, or level of competition, players face choices every game that directly influence the outcome. Every shift is a new experience and presents an opportunity for players to process information, evaluate risk, and make decisions. It’s no different than being an analyst; we take data, process it, and generate conclusions based on how we view the game. The cumulative effect of these decisions, on and off the ice, determines which players (and people) separate themselves from the pack and outperform expectations.

Traditional hockey evaluation has long prioritized observable, available statistics such as goals, assists, and shots. While these examples certainly provide valuable information, they measure the result of a decision rather than the process that went into it. If a goal was scored on the powerplay, the player who drew the penalty that provided an opportunity for possibly more skilled players to enter the game on a man-advantage. If a goal was scored as a result of a giveaway in the defensive zone, some pre-NHL and junior leagues don’t even track +/- numbers or giveaway/takeaway numbers. In speaking to various industry professionals over the last few months, I’ve learned that there’s a distinct gap between the statistics available to the public and those the clubs possess internally. If analysts like me can leverage the vast array of resources at an agency’s disposal to minimize this information gap, then a plan can be implemented to identify decision-making prototypes that may not be receiving the national attention they deserve. I’m of the opinion that good, productive players exist anywhere in the world, and it’s our job to discover them. In many cases, players who outperform their AB expectations are not necessarily the most physically gifted players, but are the ones who consistently make good decisions over time.

Everyone knows what everyone else knows. It doesn’t take a genius to determine that Connor McDavid at age 15 was different from his peers and was destined for NHL stardom. However, where systems like AB are valuable is that they can point talent evaluators in the direction of players like MacKenzie Weegar- the player with the highest recorded Pre-NHL TAB Score in my dataset (more on TAB Scores in a later section). Weegar was selected in the 7th round of the 2013 NHL Draft and has gone from a dart throw to a steady NHL defenseman, with multiple seasons registering above-replacement AB Scores, an estimated earnings of $34 million through 6 NHL contracts, and a career spanning 629 games and counting. Weegar is exactly the kind of player the TAB Score and AB were designed for. If my theory that decision-making is a transferable skill is true, then players who exhibit those characteristics before reaching the NHL can be identified by generating scores, conducting retrospective analysis, and determining the prototypical AB player. These steps can enhance the process and help your firm find the MacKenzie Weegar’s of the world who weren’t on anyone’s radar.

Tentative AB Scores (TAB)- How to Enhance The Process

I mentioned before the sizable gap between public and private data at the Pre-NHL level. As an outsider, I developed the TAB Score, a developmental precursor to the AB Framework, designed to evaluate draft-eligible players using the limited information available to me, but within the AB framework.

The existence of TAB should not be interpreted as a separate philosophy from AB. It is nowhere near as statistically rigorous a calculation as the actual AB Score, but it is certainly capable of providing direction, such as in the case of Weegar. Ideally, I would prefer to calculate a true AB Score for every player in every league, at every level, around the world from 2007-Present, giving me a retrospective analysis of the projections to determine whether they hold any merit. Such an undertaking, without statistics or game sheets being available from coaches, parents, or clubs themselves, would be extremely difficult. However, with the backing of an agency with resources and the ability to acquire the statistics necessary to build true scores, the opportunity arises to create a repository of information unique to only your firm, and conduct recruitment exercises based on a calculated philosophy rather than merely an “eye test”.

I generated TAB Scores for every NHL draft dating back to 2007 and compared them against actual NHL outcomes. My goal was to determine whether positive TAB players consistently outperformed their peers in a large enough sample to indicate that the framework could identify meaningful characteristics in young players. The graphic below is the first piece of evidence illustrating an initial success.

The results of the graphic above are incredibly encouraging. Across every draft round studied, players with positive TAB Scores reached the NHL at rates significantly higher than their negative TAB counterparts selected in those same rounds. The relationship also remained consistent regardless of draft slot, with substantial ratios in rounds 5-7.

This finding is particularly important for agencies because the best chance to create real value for your firm usually does not come from pinpointing the obvious first-round talent everyone in the industry has known about for a long time. Instead, the real opportunity lies in discovering players like Mackenzie Weegar before the market fully recognizes their true value. If every team, scout, and agency is evaluating the same publicly available information, then competitive advantages arise from uncovering characteristics that may not be reflected in the traditional statistics previously discussed, potentially affecting draft position. The TAB results of players drafted in rounds 5-7 are astonishing. Historically, only a small percentage of players selected in these rounds ever reach the NHL. However, among the select group who did, the vast majority of them had positive TAB Scores as pre-NHL prospects. Again, TAB is in no way a replacement for scouting, but these findings suggest that it could be an effective tool for directing an experienced eye toward a specific player who deserves a closer look.

It’s also important to note that I excluded the 2023, 2024, and 2025 drafts from the primary historical analysis because most of these players have not had sufficient time to complete their development paths. Nevertheless, an interesting trend has already emerged. 9 players from the 2025 NHL Draft (Matthew Schaefer, Michael Misa, Anton Frondell, Brady Martin, Porter Martone, James Hagens, Ben Kindel, Braeden Cootes, and Victor Eklund) all made their NHL debuts this season, a year removed from their selection. Of those 9 players, only Cootes had a negative TAB Score, meaning 89% of the group were positive. While the sample is small, it’s indicative that teams were willing to trust their recent draft picks somewhat quickly- perhaps due to their intelligence and decision-making capabilities relative to their peers. Martone, Kindel, and Hagens even recorded meaningful playoff minutes.

The significance of these findings extends beyond simply identifying future NHL players.  They suggest evidence that decision-making capabilities can be measured before a player reaches the NHL, and those characteristics translate across various levels of competition. For agencies like yours, this discovery presents an opportunity to identify and recruit players earlier in their development while also creating a framework to evaluate prospects with the underlying traits associated with long-term NHL success.  Reaching the NHL is the first step, as once these players arrive, we can generate full scores and properly evaluate whether the same characteristics associated with NHL entry are also correlated with career longevity.

AB Scores and Career Longevity

From an agency perspective, simply getting a player to the NHL is rarely the end goal. You’ve spent years of time, resources, and energy preparing these kids for the future with little financial benefit. Similar to a stock or asset, you’re investing in their potential. The true measure of success for a player is to build a long-lasting career that earns them multiple contracts, creates generational wealth for themselves and their families, and maximizes their lifetime earnings both during and after their playing days (and ensures you get paid too!). Every year, certain players appear in a handful of NHL games before returning to the minors, retiring, or joining other professional leagues around the world. Others remain in the league for a decade or longer. Understanding the characteristics that separate these two groups is where the AB framework becomes especially valuable.

Unlike TAB, which was created out of necessity due to the lack of publicly available information, AB uses a much more comprehensive decision-intelligence and mistake-minimization statistical analysis to generate an NHL-caliber score. This raises the question: Does good decision-making simply help a player get to the NHL, or does it help them stay there?

To answer this, I conducted a historical analysis comparing players who recorded at least one above-replacement AB Season to those who never reached above-replacement status during their careers. For context, the replacement-level number used for this analysis was a score of 1.17, which was the 2025-26 benchmark. Instead of just focusing on point production or games played, my goal was to determine whether players remained in the league long enough to earn a second contract, a milestone that serves as a reasonable proxy for career sustainability and organizational trust. The graphic below reveals the findings.

The results were some of the strongest produced by the AB framework thus far in my research. According to the graphic, players who recorded at least one above-replacement AB season reached the second-contract window 87.4% of the time, compared to 30.9% for players who never crossed this threshold. Players who demonstrated above-replacement decision-making characteristics were 2.8 times more likely to remain in the NHL long enough to secure a post-ELC second contract.

Like the TAB findings, this relationship was consistent across all rounds of the NHL Draft. While a draft slot ultimately creates opportunities for prospects, these findings suggest that prototypical intelligent decision-makers play significant roles once they enter the NHL. The sixth-round results are especially revealing, with 92.6% of above-replacement players debuting in that class reaching the second-contract window compared to just 29% of their below-average counterparts.

For agencies, this distinction matters enormously. Recruiting players’ services when they’re 14-15 years old is already a crapshoot as is, and their likelihood of earning a second contract can vary based on a variety of factors, including lack of transferable skill, injuries, or stunted development. Implementing a system that could provide a competitive edge and a greater likelihood of capitalizing on investments when millions of dollars are at stake is a prime example of why AB intelligence could be a worthwhile gamble for your firm. If career longevity is one of the primary drivers behind financial success in professional hockey, the next logical question becomes whether the market ultimately rewards these same players with lucrative post-ELC deals. Based on the historical earnings data represented in the next section, the answer appears to be a resounding yes.

AB Scores and Career Earnings

If the relationship between AB Scores and career longevity is as strong as the previous section suggests, then it’s reasonable to examine whether those same decision-making characteristics are recognized and rewarded by the marketplace.

I analyzed salary data accumulated between the 2007-08 season and May 2026 for every player included in the historical AB database (over 14,000 unique individual seasons). The objective was straightforward: determine whether players who demonstrated above-replacement AB performance earned more money throughout their careers than players who never reached above-replacement status. While the second-contract analysis demonstrated that AB players tend to remain in the NHL longer, this study examines whether that longevity ultimately translates into financial outcomes.

The median earnings data offer a valuable starting point because they reflect the typical outcome for players in each group. Unlike averages, which can be skewed by superstars and outliers, median earnings show what a “normal” career looks like for players with different AB profiles. The findings are notable: players with at least one above-replacement AB season earned significantly higher median career earnings than those who never reached above-replacement status. Again, this pattern holds across all draft rounds, indicating that decision-making traits consistently add value regardless of the player’s original pick.

From an agency standpoint, this may be one of the most practical findings presented in this study. The median player is not Connor McDavid, Nathan MacKinnon, or Cale Makar. The median player represents the type of client most agencies work with on a daily basis. If above-replacement AB players consistently generate stronger financial outcomes than their peers, then identifying those players earlier creates a significant opportunity to improve recruitment, development, and long-term client strategy.

While median earnings help us understand the typical outcome, average earnings provide a different perspective. They allow us to examine how the market rewards decision-making at the highest levels of the profession and whether exceptional AB performance translates into exceptional financial value.

The average earnings results reinforce the findings from the median analysis. Players who recorded at least one above-replacement AB season earned an average of $27.4 million between 2007-08 and May 2026, compared with just $3.4 million for players who never reached above-replacement status. In other words, above-replacement AB players generated nearly eight times more career earnings than their counterparts.

Perhaps even more interesting is the relationship between earnings and AB performance tiers. As AB performance increases, average earnings rise accordingly. Players in the highest AB quartile dramatically outperformed those in the lower quartiles, creating a staircase-like progression that suggests the marketplace consistently rewards the characteristics measured by the AB framework. This pattern is difficult to ignore because it goes beyond a simple comparison between good and bad players. Instead, it indicates that incremental improvements in decision-making and overall AB performance are associated with progressively greater financial outcomes.

The draft-round analysis further strengthens the case. Regardless of draft position, above-replacement AB players consistently earned more than players who never achieved above-replacement status. This finding aligns closely with the earlier TAB and second-contract studies. Draft position may create opportunities, but long-term earnings appear to be heavily influenced by what players do after they arrive. Organizations ultimately invest in players who help them win, and the evidence suggests that the decision-making characteristics measured by AB are associated with outcomes that teams are willing to reward financially.

Taken together, the career longevity and earnings studies suggest that AB is measuring more than short-term performance. The framework appears to identify characteristics associated with sustainability, trust, and long-term value creation. For agencies, these findings provide the foundation for a much broader application of the AB philosophy, extending beyond recruitment into comparable generation, contract valuation, arbitration preparation, and long-term career planning.

Conclusion

At its core, this entire study began with a simple question: if decision-making is truly the most transferable skill in hockey, can we measure it and use it to create a competitive advantage?

The findings presented throughout this article suggest that the answer may be yes. Players with positive TAB Scores reached the NHL at substantially higher rates than their negative TAB counterparts across every draft round studied. Once those players reached the NHL and full AB Scores became available, the relationship continued. Players who recorded at least one above-replacement AB season were 2.8 times more likely to reach the second-contract window than players who never achieved above-replacement status. The financial implications were equally compelling. Above-replacement AB players earned significantly more throughout their careers, generating nearly eight times the average earnings of players who never reached above-replacement AB.

Each of these findings is interesting individually. Collectively, they suggest something much more significant. The same decision-making characteristics associated with NHL entry also appear to be associated with career longevity and long-term financial success. In other words, the AB philosophy may be measuring something that organizations consistently reward over time.

What excites me most is not what has already been accomplished, but what remains possible. Every TAB Score presented in this study was generated using publicly available information. Every retrospective analysis was conducted without access to the proprietary tracking data, internal reports, video databases, and organizational resources available to professional hockey clubs and agencies. If these relationships can be identified using imperfect information, imagine what could be accomplished with a complete dataset.

That is where I believe the greatest opportunity exists. My long-term vision is to build the most comprehensive hockey decision-intelligence database in the world: a repository containing historical and current AB profiles for players across junior, collegiate, European, and professional leagues. Such a resource would allow agencies to identify prospects earlier, evaluate players more accurately, generate stronger comparables, support arbitration and contract negotiations, and create a sustainable competitive advantage that few firms could replicate.

Most importantly, this project is not finished. The AB framework continues to evolve, and my research does as well. As a Ph.D. candidate and lifelong student of the game, I remain committed to refining the methodology, expanding the dataset, and testing new applications. I am passionate about hockey, analytics, and helping organizations make better decisions.

If your agency sees value in these findings and shares the vision of building something truly unique within the industry, I would welcome the opportunity to work together. The players are out there. The information is out there. The challenge is building a system capable of finding them before everyone else does. Again, please feel free to contact me at bractonabellahockey@gmail.com. Thank you for reading!