If you’ve been following my work here at Broad Street Breakout, you know I love digging into the numbers to see what’s really happening on the ice. Today, I’m pulling back the curtain on something I’ve been working on: a comprehensive ranking system that evaluates every Flyers player against their peers across the entire NHL.
Before we dive in, let me be clear about something—this isn’t the definitive way to evaluate hockey players. It’s one tool in the toolbox, and like any tool, it has its strengths and limitations. But what it does offer is a consistent, data-driven framework for understanding player impact beyond just goals and assists.
How the Rankings Work
The model evaluates players across three main categories, with different weightings for forwards and defensemen:
For Forwards:
- Offensive Performance (50%)
- Defensive Performance (30%)
- Possession/Two-Way Play (20%)
For Defensemen:
- Offensive Performance (40%)
- Defensive Performance (35%)
- Transition/Possession (25%)
Within each category, we’re tracking several key metrics. Let me break down what these actually mean:
The Offensive Metrics
Goals/60 and Primary Assists/60 – These are pretty straightforward. How many goals or primary assists does a player record per 60 minutes of ice time? We use per-60 rates because it levels the playing field between top-line players getting 20 minutes a night and fourth-liners getting 10.
Expected Goals (xGoals/60) – This is where it gets interesting. Expected goals measure the quality of scoring chances a player generates based on shot location, type, and other factors. A player with high xGoals is consistently getting to dangerous areas and creating quality opportunities.
High Danger Shots/60 – Not all shots are created equal. A shot from the slot is way more likely to go in than one from the blue line. This metric tracks how often players are getting those prime scoring chances.
The Defensive Metrics
On-Ice Goals Against/60 – How many goals does the opposing team score when this player is on the ice? It’s not perfect (teammates matter), but over a full season, patterns emerge.
Takeaways and Blocked Shots – These show defensive engagement. Are you actively disrupting plays and getting in shooting lanes?
The Possession Game
Corsi% and Expected Goals For% – These tell us who’s controlling play. When you’re on the ice, does your team have the puck more often than not? Are they generating more quality chances than they’re giving up?
Giveaways/60 – This one’s tricky. Elite players often have more giveaways because they have the puck more and try to make plays. But there’s a balance—you can’t be coughing it up constantly.
Where the New Guys Would Fit
Since we’ve made some significant moves this offseason, I wanted to see where our new additions would have ranked if they were on last year’s team.
Trevor Zegras would have slotted in as our #2 forward with a 60.8% overall rating, just behind Michkov. His offensive metrics (79.2%) are elite, but like many young skilled players, his defensive game (41.3%) needs work. Sound familiar? It’s almost the exact same profile as Michkov—elite offense carrying below-average defense.
Christian Dvorak is fascinating. He would have ranked as our #4 forward at 57.2%, ahead of Tyson Foerster. Unlike our other top forwards, Dvorak brings defensive responsibility (64.8%) while still contributing offensively (52.1%). He’s the two-way center this lineup desperately needed.
The Konecny Conundrum
Here’s where this model really shows its value. Travis Konecny led the team with 76 points but ranks 7th in our system. How is that possible?
His defensive metrics (29.2%) are among the worst on the team. When Konecny’s on the ice at 5v5, opposing teams score at a higher rate. His possession numbers are middling. The points are there, but they’re masking some real issues in his overall game.
Does this mean Konecny is bad? Absolutely not. It means he’s a one-dimensional scorer on a team that often gets hemmed in its own zone. Put him on a better team with more puck possession, and those defensive numbers likely improve.
What These Rankings Don’t Tell Us
This system doesn’t capture everything. It doesn’t measure:
- Leadership and locker room presence
- Clutch scoring ability
- Penalty killing excellence
- Power play specialization
- The ability to elevate teammates
Nick Seeler, for example, ranks middle-of-the-pack in our system but is arguably the team’s most reliable defensive defenseman in crucial moments. His willingness to block shots and make the simple play has value beyond what these metrics capture.
Similarly, Sean Couturier’s veteran presence and faceoff ability aren’t fully reflected in his 59.4% rating. He’s still learning to adapt his game post-injuries, and his leadership value goes beyond the numbers.
The Bigger Picture
What these rankings do show is why the Flyers are where they are—a rebuilding team with some exciting pieces but significant holes:
- We lack elite talent. Only Michkov (61.6%) and Tippett (61.1%) crack 61%. Compare that to true contenders who have multiple players above 70%.
- The defense needs an overhaul. Our best defenseman (Drysdale at 57.8%) would be a #3 or #4 on a good team.
- The bottom six is rough. Having multiple forwards ranking 400+ in the NHL is a problem.
- There’s hope in the youth. Michkov, Foerster, and Drysdale are all young with room to grow. Their rankings should improve as they develop.
Using This as a Tool
These rankings aren’t gospel. They’re a starting point for deeper conversations. When someone says “Player X is better than Player Y,” we can now look at specific areas:
- Is it offense driving that opinion?
- Are we overvaluing points and undervaluing defense?
- Is a player’s true impact being hidden by their linemates?
The model also highlights players who might be undervalued. Bobby Brink’s possession numbers suggest he drives play better than his point totals indicate. Maybe he deserves a longer look with better linemates?
Moving Forward
As the season progresses, these rankings will shift. Young players like Michkov should improve their defensive awareness. Veterans like Konecny might benefit from Rick Tocchet’s structure. The additions of Zegras and Dvorak change the dynamics.
What excites me most is having a framework to track that progress. Are players improving in specific areas? Is the team’s overall rating trending upward? These are the questions that will define whether this rebuild is heading in the right direction.
The data tells a story, but it’s not the only story. Use these rankings as one piece of the puzzle when evaluating players. Hockey is still a game played by humans, not spreadsheets. But when the humans and the spreadsheets align? That’s when you know you’re onto something special.
All data courtesy of MoneyPuck.com, with rankings based on players with 500+ minutes of ice time. The model will be updated throughout the season as games are played.