The Utah Mammoth, in their second year after relocating, seems set to qualify for the Stanley Cup playoffs in the final stretch of the 2025-26 season. Through 71 games, the club has a record of 37-28-6 for 80 points. They currently hold a 5-point lead on the Nashville Predators for the top wild card spot in the Western Conference, as well as a 7-point lead over the Los Angeles Kings, who are just shy of the playoff picture with 73 points. It’s been an unusually weak Western Conference compared to previous years, but the Mammoth are one of only six teams to post a positive goal differential. Their +25 is good for 4th in the entire conference as of today, trailing only the Colorado Avalanche (+82), Dallas Stars (+50), and Minnesota Wild (+31).
When conducting a deeper dive into the team and its roster construction, the AB data suggests that we should consider the Mammoth a more legitimate threat not only to qualify for the playoffs but also to make a postseason run this spring. The article below will analyze Utah’s AB performance over 71 games as a team and compare it to Stanley Cup Championship teams, starting with the 2007-08 Detroit Red Wings. Additionally, changes in the Hockeyfreeforall.com system’s Arbitration Analyzer metric have indicated positive outcomes in major decisions by Mammoth GM Bill Armstrong and his management team. Lastly, I’ll discuss how several young prospects within the Mammoth’s system are well-positioned to make the jump to the NHL and contribute sooner rather than later.
Through 71 games, the Utah Mammoth have a team AB Score of 26.81, a very respectable mark given the substantial changes in the AB Score formula discussed in the Morgan Reilly article here, The Toronto Maple Leafs Failed Morgan Rielly- And It’s Time for Both Sides to Move On – hockey free for all.com (HOME OF THE ADVANCED BRACTON). The graphic below illustrates the exact player numbers with only 11 games remaining.
This is an incredibly interesting team composition, as the Mammoth have 17 of their 24 roster players performing above replacement level, which is defined as 0.28 AB in the new format. Since the trade deadline move to Utah, MacKenzie Weegar has looked like the quality player he’s always been over the course of his career, playing over 21 minutes per game in his 9-game stint so far with the club. In that span, he’s only recorded 1 assist, but is +3 and has an almost even giveaway-takeaway ratio. Even with his disastrous start in Calgary, he’s still performing slightly below-replacement for the year, with time to improve the rest of the way.
What’s important to note about this graph, however, is that Utah’s core is performing like the elite players management thought they would be. Clayton Keller is having a stellar individual season, leading the Mammoth with 68 points in 71 games, while also winning a Gold Medal with Team USA at the 2026 Winter Olympics in Italy last month. Nick Schmaltz earned himself a new contract extension (more on this later) with 63 points in 71 games, needing 4 goals in the remaining 11 games to eclipse the 30-goal plateau for the first time in his 11-year career. Dylan Guenther has exploded by scoring 34 goals and 59 points in 69 games, while posting the third-highest AB behind Keller and Schmaltz, respectively. Even Logan Cooley, who unfortunately has missed 28 games with injury, still recorded 30 points in his 43 games played while posting a +1.42 AB Score. The Mammoth are also getting positive contributions from almost all of their defensemen, which is critical for postseason success.
The negative values are very limited, and Kerfoot, Simashev, and Maatta have each played 25 or fewer games. This kind of AB distribution gives reason for optimism because Utah appears to have the makeup of a serious Stanley Cup contender with clear top-end talent (Keller, Schmaltz, Gunther, Sergachev, Cooley), significantly above-average secondary support (Peterka, Crouse, Marino, Schmidt, Hayton), and an overall balanced roster with no extremely detrimental players. This analysis raises the question of whether Utah’s roster construction compares to that of previous champions, as the next part of the article will discuss.
The graph below illustrates the comparison between the 25-26 Utah Mammoth and the eighteen previous Stanley Cup Champions (07-08 Red Wings, 08-09 Penguins, 09-10 Blackhawks, 10-11 Bruins, 11-12 Kings, 12-13 Blackhawks, 13-14 Kings, 14-15 Blackhawks, 15-16 Penguins, 16-17 Penguins, 17-18 Capitals, 18-19 Blues, 19-20 Lightning, 20-21 Lightning, 21-22 Avalanche, 22-23 Golden Knights, 23-24 Panthers, and 24-25 Panthers).
As the graph illustrates, the 25-26 Utah Mammoth do not meet the average commonalities of the last 18 Stanley Cup champions. While the team can still improve during the season’s final stretch, the Mammoth’s Team AB total of 26.8 is 6.05 below the average champion’s average, and they also fall beneath the average in total positive and negative AB players, Roster Positive Percentage, and elite +3 or higher AB players. When looking at this graph, you’d think that the Mammoth would be considered a tier below the true contenders in the NHL. However, this assumption alone misses the point of why this roster is so interesting.
The 25-26 Utah Mammoth aren’t built exactly like the average Stanley Cup champion. They’re built like a team, with structural attributes that ALL champions consistently possess. The graph below shows how the 25-26 Mammoth compares to similarities that are not typical of the average winner, but that all winners actually had.
Utah exceeds 7 of the 8 characteristics under this criterion. The difference between this graph and the other highlights the main point of this research: the roster, as currently built, has potential for deep playoff runs. It’s clear that they are a playoff-caliber team, barring a ridiculous collapse during the final 11 games, but according to these insights, the team may need an additional leap from one of its younger stars or supporting cast to reach the thresholds defined by the two graphs. When analyzing the roster, it’s evident who those players may be. When the Mammoth traded for JJ Peterka from the Buffalo Sabres during the 2025 offseason, they thought they were getting a dynamic, money-in-the-bank 30-goal scorer who would be a powerplay force. However, early results on that move haven’t been promising, as Peterka has scored only 22 goals in 71 games, and Utah’s power play is an abysmal 16.6%, tied with the Washington Capitals and New York Islanders for 27th in the NHL this season. The second answer is in the 2022 3rd overall pick, Logan Cooley. While both Peterka and Cooley are performing substantially above replacement according to AB, Peterka’s scoring and Cooley’s health this season are the limiting factors behind them taking the next step Utah Management is hoping for. Cooley, however, signed an $80 million ($10 million AAV) contract extension with the team just after the start of the season, keeping him in Utah for the next 8 years after this one.
When analyzing Cooley’s new deal, as well as teammate Nick Schmaltz’s 8-year, $64 million ($8 million AAV) through the Arbitration Analyzer tool, the results were promising. However, to effectively explain how we arrived at that point, it’s important to outline the fundamental changes to the Arbitration Analyzer and its role within the Hockeyfreeforall.com family of metrics. The new Arbitration analyzer departs from the old model’s comparable-based structure in favor of a projection framework built around cap percentage. As opposed to the old method of estimating a salary by averaging comparable salaries, the new version develops a complete 20-point statistical framework that factors in performance, age, years of experience, and multi-year indicators such as career averages and a prime-year definition. These variables, along with others, are combined using machine learning frameworks such as ridge regression, gradient boosting, and random forests to estimate the percentage of the salary cap a player should command in the target season.
The shift in structure also matters statistically, because each model type captures a different kind of relationship. Ridge helps stabilize broad linear effects, while Gradient Boosting and Random Forest are better at capturing nonlinear interactions and threshold behavior that simpler systems may miss. In perhaps the biggest change, the model includes star-tier logic so elite and franchise-level players are not systematically undervalued. The old arbitration analyzer tool model was essentially a historical salary-matching tool. While valuable, the new analyzer will be substantially better, as it’s a hybrid forecasting model that uses a player’s full statistical profile to estimate the level of financial commitment he deserves, given today’s market and the rapidly increasing salary cap. With that being said, let’s discuss the two massive contract extensions given by the Mammoth over the past few months.
Logan Cooley’s projection drastically improved due to changes in the model, as his production this year, even with his injuries, has allowed him to be considered differently than a typical young RFA. The past issue wasn’t that he had weak numbers, but that his statistical profile didn’t match that of a true high-end, franchise star. When we accounted for his 25-26 season, the star-growth-curve valuation immediately looked like a legitimate cornerstone. The graph below depicts how the model project’s Cooley’s salary will age as he gains more NHL experience and enters his professional prime.
As shown above, the path starts at $7.85 million, then rises, settling just above $10 million in the contract’s second half. The model states, and I concur, that initially a contract of this size is a gamble for the Mammoth to have taken, since they are clearly betting on Cooley to not only stay healthy but also to make a leap similar to that of 2022 first overall pick Juraj Slafkovsky with the Montreal Canadiens this year. The new model reflects Cooley for what he is, a premium growth asset with more developmental potential, rather than his teammate Schmaltz, who is more of a known commodity because of his decade of prior experience.
Nick Schmaltz’s projection is relevant because the model begins by evaluating him at the veteran replacement level and then accounts for his production and trajectory. Again, this is a new feature to the Arbitration Analyzer tool, as the graph below details his formal chart.
While the model classifies the new Nick Schmaltz contract as a slight overpay, the slight decline rather than a steadfast one is a compliment to Schmaltz’s career and current ability as a player. Previous studies on Hockeyfreeforall.com have shown a significant dip in performance after a player turns 30, yet the model suggests that Schmaltz will remain an above-average player well into the new deal. It’s worth noting that the 8-year contracts for both Schmaltz and Cooley were intended to retain talent within the organization, as Utah isn’t exactly a prime free-agent destination in either the NHL or the NBA, despite the brilliance of the Smith Entertainment Group, its world-renowned facilities, and the surrounding area.
When looking back at the AB makeup of the 25-26 roster, you’ll notice that 2023 6th and 12th overall picks, Dmitry Simashev and Daniil But, have officially played NHL games since coming over from Russia. They’re the first of Utah’s elite prospects to make the jump to the pros; however, yesterday the club signed 2025 4th overall pick Caleb Desnoyers to his entry-level contract, indicating that the youth movement is in full effect. Desnoyers, in particular, is a very intriguing prospect because he had the second-highest TAB Score (+13.25) in his entire draft class. TAB is essentially a metric applied to lower levels of hockey to evaluate a prospect’s draft year, with conditional AB ranking forming 80% of what a normal AB Score would look like. More information on TAB and its relation to the research of this website can be found here: Dissecting The NHL Draft Through TAB, How does this affect the 2022 Class? – hockey free for all.com (HOME OF THE ADVANCED BRACTON).
If the season were to end today, the Mammoth would face the Anaheim Ducks in the first round of the Stanley Cup Playoffs. The Ducks were also featured in last month’s HFFA article here: Joel Quenneville Has Altered the Trajectory of the Anaheim Ducks — The League Shouldn’t Make the Same Mistake with Peter DeBoer – hockey free for all.com (HOME OF THE ADVANCED BRACTON). In my analysis of both teams, the data suggests that the Mammoth would have the edge in this potential matchup, as it would be a great one between two up-and-coming Western Conference franchises. If they advance from that series, they will face the winner of the Vegas/Edmonton matchup, and they have outperformed both teams this season in the standings thus far.
Based on the research presented in this article, if the playoff matchups hold, it’s not completely unrealistic to think that the Utah Mammoth could advance to the Western Conference Finals this year. Given that their core is under contract for the foreseeable future and their prospects are becoming more NHL-ready by the day, the idea that this season is the worst the club will be over the next few years is a scary thought. There’s something special brewing in Utah, and it’s time the league starts taking notice.
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