From Shot Quality to Synergy Forecasting
Expected goals (xG) have revolutionized how we analyze hockey performance. By quantifying shot quality based on location, angle, shot type, and pre-shot movement, xG offers a clearer look beyond goals and assists. But while it tells us how likely a player is to score in a given situation, it doesn’t tell us who will unlock each other’s potential before the puck even drops.
We’re entering a new frontier: chemistry prediction modeling — the attempt to forecast line synergy using data from movement patterns, pass types, decision windows, and hockey IQ compatibility.
And yes, it’s coming faster than we think.
🧬 What Is Chemistry Forecasting?
While xG focuses on isolated chances, chemistry forecasting asks:
“How well will Player A and Player B amplify each other over time?”
That means combining:
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Zone entry overlap (who carries, who supports)
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Shot/pass tendencies under pressure
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Off-puck movement synergy
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Time-to-decision correlation
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Puck touch distribution per cycle
It’s not just “does this guy pass?” or “does this guy shoot?” It’s:
Can this guy think one second ahead on the same wavelength as his linemate?
Five Experimental Pairings That Could Shine — Or Clash
Let’s break down five intriguing (and hypothetical) pairings that test this concept — combining playstyle archetypes, data tendencies, and mental tempo compatibility.
1. Auston Matthews & Matias Maccelli
Projection Type: Finish-first sniper + east-west facilitator
Why it’s fascinating:
Maccelli is an elite puck controller in small areas, ranking top 10 league-wide in controlled zone entries and passes into the slot per 60. Matthews, meanwhile, has refined his release into one of the most deceptive in the league — but he thrives when someone else handles the puck load in transition.
Chemistry Outlook:
Their shot/pass tension is perfect, but the real test is pace. Maccelli tends to delay and shift pace through deception, while Matthews wants quick-touch tempo in the slot. If synced, Matthews could become the NHL’s most efficient high-danger shooter.
xChem Score: 8.4 / 10
Comparable model pairing: Barkov & Huberdeau (2021)
2. Nikolaj Ehlers & Sebastian Aho
Projection Type: Dual-zone dynamos with elite tempo IQ
Why it’s fascinating:
Both are possession monsters who drive play with or without the puck. Aho is a cerebral, puck-stealing center who thrives off quick lateral support — and Ehlers is one of the league’s best at shifting speed in the neutral zone and beating defenders off the rush.
Chemistry Outlook:
High ceiling, high risk. These two think the game fast and act even faster. But they might be too similar — if neither wants to play behind the puck, who sets the rhythm? If they find spacing and trust, this duo could be the most fluid cycle-to-slot partnership in the NHL.
xChem Score: 9.2 / 10
Comparable model pairing: Jake Guentzel and Brayden Point (early overlap period)
3. Andrew Mangiapane & Ryan Nugent-Hopkins
Projection Type: Scrappy goal-scorer + deceptive connector
Why it’s fascinating:
Mangiapane is relentless below the dots, excelling in dirty goal areas. RNH has transformed into one of the NHL’s best quiet connectors — soft passes, perfect weight, calm under pressure.
Chemistry Outlook:
They complement each other on paper — but the worry is overlap in pace. Neither is a strong entry driver, so a third-line puck mover would be needed. However, once in the offensive zone, the vision-to-grit combo could create long possession sequences that wear teams down.
xChem Score: 7.6 / 10
Comparable model pairing: J.T. Miller & Tanner Pearson (in their peak Canucks phase)
4. Mitch Marner & Jack Eichel
Projection Type: Vision wizard + power-skating playmaker
Why it’s fascinating:
On paper, this feels like a dream. Marner is the league’s most efficient play connector below the dots, while Eichel thrives when given north-south lanes with space. The pass timing potential is scary — Marner buys time in tight spaces, Eichel feasts on acceleration gaps.
Chemistry Outlook:
The issue is both are dominant with the puck. Can Marner be equally effective as a secondary option? If he can adjust to being a hybrid support player (à la Nikita Kucherov), the result could be a point-per-game storm.
xChem Score: 8.9 / 10
Comparable model pairing: Kucherov & Point (Tampa core years)
5. Trevor Zegras & Matvei Michkov
Projection Type: Chaos creator + sniper ghost
Why it’s fascinating:
Zegras sees lanes no one else does, and Michkov is an elite off-puck ghost — finding quiet ice and striking with precision. Michkov’s shot is as deceptive as Matthews’, but his ability to find open space without alerting defenders is next-level.
Chemistry Outlook:
Unreal upside — if Zegras matures into a play-driver who also protects the puck. Michkov needs stability from his setup man. The combo would feast on creative chaos, but the risk is defensive hemorrhaging and puck-loss loops if they get too fancy.
xChem Score: 9.0 / 10
Comparable model pairing: Panarin & Strome (high-skill chaos version)
The Future of xG Is Pair-Based Modeling
Within five years, expect NHL front offices to use models like:
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xChem (Expected Chemistry Score)
Based on shared decision windows, puck-touch preferences, tempo compatibility -
xSupport
Measures how much a player improves teammates' shot quality over time -
xDisrupt
Gauges how a player’s tendencies clash with others in possession patterns
These new layers would predict line effectiveness before ever hitting the ice, saving teams from costly trial-and-error deployments.
Final Thought: GMs Will Need to Be Gamers
The next generation of GMs won’t just scout speed or size — they’ll scout mental cadence. Do these players read the ice at the same frame rate? Do they trust in the same moments? Do they orbit naturally?
Chemistry prediction is the next edge.
And like expected goals a decade ago, it’ll separate teams that guess from teams that know.
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