Red Wings’ Best of All-Time: Where Did They Come From?

Over the last few weeks, I’ve been putting together my projections for 2022 Winter Olympic rosters – if the NHL allows its players to participate in the tournament. Sometime during that process—possibly while adding Filip Zadina and Filip Hronek to Czech Republic’s team—I wondered, which region has produced the best Detroit Red Wings players?

Is it Sweden? Could it be Russia with the Russian Five? Or maybe a Canadian province supplied Detroit’s best?

It’s an interesting question that I didn’t have the answer to. So I figured it out.

Using Sean McIndoe’s roster-building creativity and Dom Luszczyszyn’s playoff simulations as inspiration, I put together teams from 16 regions around the world to find which produced the best Red Wings of all-time.

Before getting to the 16 teams and which triumphed over the rest, let me explain my process.

Methodology

In order to determine which region was best, I pitted them against one another. Consider this your playoffs for the spring.

I chose three forwards and two defensemen for each region. Then I objectively determined their best season as a Red Wing and grabbed their goals per game rate from that particular campaign to use as their scoring probability. For example, Henrik Zetterberg’s best season in Detroit resulted in a 0.573 goals per game rate, so I used that number as his scoring probability.

Next, I split the teams into two divisions and ran them through a playoff, with one game per round. For each game, I used a random number generator (between 0 and 1) to determine if each player scored.¹ If the number was less than their scoring probability, they scored. If it was greater, they did not score. Using Zetterberg as the example again, if the random number generator produced 0.111, then he scored in that matchup. 

Finally, I tallied up goals for both teams. The region with the highest total won.² 

With that out of the way, let’s move onto the regions competing for world domination.

Red Wings Regions

The 16 teams were split into two divisions: Dominion and World. Here’s how the regions were divided up, with a random number assigned to determine their playoff seed.

As you probably noticed, four of the teams are composed of multiple regions. Unfortunately, I ran into instances where a region did not have the requisite three forwards and two defensemen, so I had to be diplomatic and expand borders:

• Eastern Canada: Newfoundland, Prince Edward Island & New Brunswick
• Western Europe: France, Switzerland, Austria & Germany
• Eastern Europe: Slovakia & Belarus
• Scandinavia: Finland, Denmark & Norway

Now, let’s get to the playoffs and determine our winner.

First Round

Heading into the first round, Ontario, Alberta, and Sweden were clear favorites to advance. But did they?

Dominion: (1) Alberta vs. (8) Saskatchewan

Alberta	Probability	Rand	Goal?	Goal?	Rand	Probability	Saskatchewan
Norm Ullman	0.600	0.376	Y	Y	0.132	0.700	Gordie Howe
John Ogrodnick	0.696	0.759	N	Y	0.185	0.493	Sid Abel
Herbie Lewis	0.455	0.196	Y	Y	0.287	0.323	Metro Prystai
Mike Green	0.194	0.523	N	N	0.202	0.169	Darren Veitch
Bill Gadsby	0.100	0.573	N	N	0.089	0.089	Brad McCrimmon

Saskatchewan wins 3-2.

Unsurprisingly, Gordie Howe came through in the clutch to seal the victory for his team. Saskatchewan also received contributions from Sid Abel and Metro Prystai as they downed Alberta in the opening game of the tournament.

Dominion: (4) Ontario vs. (5) British Columbia

Ontario	Probability	Rand	Goal?	Goal?	Rand	Probability	British Columbia
Ted Lindsay	0.550	0.233	Y	Y	0.416	0.813	Steve Yzerman
Alex Delvecchio	0.443	0.075	Y	Y	0.266	0.279	Darren McCarty
Brendan Shanahan	0.488	0.294	Y	Y	0.356	0.380	Danny Gare
Red Kelly	0.271	0.804	N	N	0.661	0.179	Jeff Sharples
Ebbie Goodfellow	0.568	0.264	Y	N	0.766	0.057	Bob Rouse

Ontario wins 4-3.

The matchup between Ontario and British Columbia resulted in the highest-scoring game of the first round. Led by Ted Lindsay, Ontario boasts arguably the strongest roster of the 16 regions, and it certainly showed when the province potted four goals against Steve Yzerman’s British Columbia team.

Dominion: (2) Quebec vs. (7) Manitoba

Quebec	Probability	Rand	Goal?	Goal?	Rand	Probability	Manitoba
Marcel Dionne	0.588	0.879	N	Y	0.080	0.897	Mud Bruneteau
Anthony Mantha	0.373	0.031	Y	N	0.706	0.286	Darren Helm
Martin Lapointe	0.329	0.588	N	N	0.782	0.329	Pete Stemkowski
Marcel Pronovost	0.159	0.258	N	N	0.760	0.091	Jack Stewart
Mathieu Dandenault	0.137	0.629	N	N	0.648	0.057	Madison Bowey

Manitoba wins 2-1 in overtime.

In thrilling fashion, Manitoba downed a powerful Quebec team in overtime. Tied at one after regulation, Mud Bruneteau scored the game-winning goal, much like he did in the sixth overtime of Game 1 of the 1936 Stanley Cup Final. One of the weaker regions entering the tournament, Manitoba moves onto the second round.

Dominion: (3) United Kingdom vs. (6) Eastern Canada

United Kingdom	Probability	Rand	Goal?	Goal?	Rand	Probability	Eastern Canada
Adam Brown	0.480	0.047	Y	Y	0.174	0.382	Danny Cleary
Jim McFadden	0.400	0.735	N	Y	0.437	0.513	Gerard Gallant
Steve Thomas	0.227	0.506	N	Y	0.343	0.625	Danny Grant
Fred Robertson	0.042	0.736	N	N	0.708	0.400	Flash Hollett
Tommy Anderson	0.185	0.059	Y	N	0.651	0.222	Rollie McLenahan

Eastern Canada wins 3-2.

Thanks to Danny Grant’s tally, Eastern Canada overthrew the crown and defeated the United Kingdom in their opening round matchup. Danny Cleary and Gerard Gallant also scored for Eastern Canada in the victory. 

World: (1) Western Europe vs. (8) Scandinavia

Western Europe	Probability	Rand	Goal?	Goal?	Rand	Probability	Scandinavia
Paul McLean	0.474	0.809	N	Y	0.010	0.288	Valtteri Filppula
Damien Brunner	0.273	0.440	N	N	0.929	0.215	Frans Nielsen
Thomas Vanek	0.313	0.935	N	Y	0.137	0.265	Tomas Sandstrom
Willie Huber	0.224	0.122	Y	N	0.148	0.032	Poul Popial
Uwe Krupp	0.136	0.853	N	N	0.281	0.029	Anders Myrvold

Scandinavia wins 2-1.

Despite having one of the weakest rosters in the tournament, Scandinavia upset Western Europe 2-1 as first round action for the World Division kicked off. Valtteri Filppula scored first and Tomas Sandstrom finished Western Europe off once and for all. Scandinavia’s victory also marked the second time that an eighth seed knocked off the top-ranked region.

World: (4) Eastern Europe vs. (5) Czech Republic

Eastern Europe	Probability	Rand	Goal?	Goal?	Rand	Probability	Czech Republic
Marian Hossa	0.541	0.210	Y	Y	0.152	0.309	Jiri Hudler
Tomas Tatar	0.354	0.060	Y	N	0.699	0.475	Vaclav Nedomansky
Tomas Jurco	0.222	0.950	N	Y	0.096	0.474	Petr Klima
Ruslan Salei	0.027	0.254	N	N	0.396	0.138	Filip Hronek
Sergei Bautin	0.036	0.510	N	Y	0.061	0.143	Jakub Kindl

Czech Republic wins 3-2.

During the second game of the World Division’s first round, Czech Republic established their dominance over all of Eastern Europe with a 3-2 victory. Much to my surprise, it was actually Jakub Kindl who scored the game-winning goal for his country. Jiri Hudler and Petr Klima also tallied for Czech Republic.

World: (2) Sweden vs. (7) Michigan

Sweden	Probability	Rand	Goal?	Goal?	Rand	Probability	Michigan
Johan Franzen	0.479	0.607	N	Y	0.002	0.481	Jimmy Carson
Henrik Zetterberg	0.573	0.197	Y	N	0.978	0.421	Dylan Larkin
Tomas Holmstrom	0.390	0.522	N	N	0.592	0.324	Justin Abdelkader
Nicklas Lidstrom	0.247	0.358	N	Y	0.006	0.091	Mark Howe
Niklas Kronwall	0.183	0.911	N	N	0.795	0.178	Brian Rafalski

Michigan wins 2-1.

Another upset on the world stage – Michigan downed powerhouse Sweden in their opening-round matchup. Sweden entered the tournament with high scoring probabilities across the board and plenty of leadership to go around, but Jimmy Carson and the state of Michigan had other plans. Mark Howe also scored for his birth state.

Related: Detroit Red Wings: A Tribute to Nicklas Lidstrom

World: (3) USA vs. (6) Russia

USA	Probability	Rand	Goal?	Goal?	Rand	Probability	Russia
Doug Brown	0.238	0.355	N	Y	0.225	0.439	Slava Kozlov
Drew Miller	0.175	0.015	Y	N	0.935	0.683	Sergei Fedorov
Brett Hull	0.451	0.881	N	Y	0.230	0.395	Pavel Datsyuk
Reed Larson	0.346	0.381	N	N	0.637	0.101	Slava Fetisov
Chris Chelios	0.076	0.519	N	N	0.231	0.173	Vladimir Konstantinov

Russia wins 2-1.

Unfortunately for Team USA, there was no Miracle on Ice repeat in this tournament. The Russians proved to be superior with a 2-1 win over the United States. Slava Kozlov and Pavel Datsyuk scored for Russia in the victory, with Igor Larionov supervising from the bench.

Second Round

The first round had a few shocking upsets. Could the second round produce even more drama?

Dominion: (4) Ontario vs. (8) Saskatchewan

Ontario	Probability	Rand	Goal?	Goal?	Rand	Probability	Saskatchewan
Ted Lindsay	0.550	0.922	N	N	0.864	0.700	Gordie Howe
Alex Delvecchio	0.443	0.056	Y	N	0.661	0.493	Sid Abel
Brendan Shanahan	0.488	0.529	N	N	0.832	0.323	Metro Prystai
Red Kelly	0.271	0.246	Y	Y	0.000	0.169	Darren Veitch
Ebbie Goodfellow	0.568	0.408	Y	N	0.517	0.089	Brad McCrimmon

Ontario wins 3-1.

It took until the second round, but we finally had our first non-one-goal game. Alex Delvecchio, Red Kelly, and Ebbie Goodfellow all scored for Ontario as they knocked off Howe’s Saskatchewan team. With the win, Ontario moves on to the Dominion Division Final.

Dominion: (6) Eastern Canada vs. (7) Manitoba

Eastern Canada	Probability	Rand	Goal?	Goal?	Rand	Probability	Manitoba
Danny Cleary	0.382	0.936	N	Y	0.487	0.897	Mud Bruneteau
Gerard Gallant	0.513	0.185	Y	N	0.789	0.286	Darren Helm
Danny Grant	0.625	0.901	N	Y	0.083	0.329	Pete Stemkowski
Flash Hollett	0.400	0.528	N	N	0.227	0.091	Jack Stewart
Rollie McLenahan	0.222	0.207	Y	N	0.554	0.057	Madison Bowey

Eastern Canada wins 3-2 in overtime.

Upstart Manitoba forced overtime once again, but could not stave off Eastern Canada this time. Gallant scored the overtime goal to send his region to the Dominion Division Final against Ontario. Defenseman Rollie McLenahan also scored for Eastern Canada, who entered overtime with a 56.4 percent chance of winning in the extra frame.

World: (5) Czech Republic vs. (8) Scandinavia

Czech Republic	Probability	Rand	Goal?	Goal?	Rand	Probability	Scandinavia
Jiri Hudler	0.309	0.963	N	N	0.537	0.288	Valtteri Filppula
Vaclav Nedomansky	0.475	0.609	N	N	0.623	0.215	Frans Nielsen
Petr Klima	0.474	0.429	Y	N	0.623	0.265	Tomas Sandstrom
Filip Hronek	0.138	0.420	N	N	0.380	0.032	Poul Popial
Jakub Kindl	0.143	0.020	Y	Y	0.001	0.029	Anders Myrvold

Czech Republic wins 2-1.

Scandinavia’s underdog run came to an end at the hands of Czech Republic, who received goals from Klima and Kindl. Through two games, the two Czech skaters lead their region with two goals apiece. With the victory, Czech Republic advances to the World Division Final.

World: (6) Russia vs. (7) Michigan

Russia	Probability	Rand	Goal?	Goal?	Rand	Probability	Michigan
Slava Kozlov	0.439	0.263	Y	N	0.985	0.481	Jimmy Carson
Sergei Fedorov	0.683	0.488	Y	N	0.525	0.421	Dylan Larkin
Pavel Datsyuk	0.395	0.416	N	N	0.366	0.324	Justin Abdelkader
Slava Fetisov	0.101	0.409	N	N	0.571	0.091	Mark Howe
Vladimir Konstantinov	0.173	0.421	N	N	0.610	0.178	Brian Rafalski

Russia wins 2-0.

Russia’s dominance over the United States continued with a 2-0 victory over Michigan, who could not avenge Team USA after they fell to the Russians in the opening round. Kozlov scored his second goal of the tournament and Sergei Fedorov also got on the board for Russia after going scoreless in their first game. Russia has only allowed one goal in two games entering the World Division Final.

Third Round

We’re down to the final four regions. Which will take home division titles and advance to the championship game?

Dominion: (4) Ontario vs. (6) Eastern Canada

Ontario	Probability	Rand	Goal?	Goal?	Rand	Probability	Eastern Canada
Ted Lindsay	0.550	0.038	Y	Y	0.133	0.382	Danny Cleary
Alex Delvecchio	0.443	0.712	N	N	0.921	0.513	Gerard Gallant
Brendan Shanahan	0.488	0.376	Y	Y	0.603	0.625	Danny Grant
Red Kelly	0.271	0.150	Y	Y	0.246	0.400	Flash Hollett
Ebbie Goodfellow	0.568	0.279	Y	N	0.659	0.222	Rollie McLenahan

Ontario wins 4-3.

In one of the highest-scoring games of the tournament, Ontario came away with a 4-3 victory, sending the province to the championship game. Lindsay, Kelly, Goodfellow, and Brendan Shanahan all scored for Ontario. Goodfellow has tallied in every game for his region so far. 

World: (5) Czech Republic vs. (6) Russia

Czech Republic	Probability	Rand	Goal?	Goal?	Rand	Probability	Russia
Jiri Hudler	0.309	0.264	Y	Y	0.043	0.439	Slava Kozlov
Vaclav Nedomansky	0.475	0.895	N	Y	0.501	0.683	Sergei Fedorov
Petr Klima	0.474	0.513	N	N	0.577	0.395	Pavel Datsyuk
Filip Hronek	0.138	0.990	N	N	0.440	0.101	Slava Fetisov
Jakub Kindl	0.143	0.308	N	N	0.358	0.173	Vladimir Konstantinov

Russia wins 2-1.

Kindl’s run had to come to an end at some point. The defenseman failed to score for the first time in the tournament as Russia defeated Czech Republic 2-1. Kozlov and the Russians will face Ontario in the championship game having only allowed two goals through three contests.

Red Wings World Championship: Ontario vs. Russia

Ontario	Probability	Rand	Goal?	Goal?	Rand	Probability	Russia
Ted Lindsay	0.550	0.599	N	N	0.896	0.439	Slava Kozlov
Alex Delvecchio	0.443	0.914	N	N	0.820	0.683	Sergei Fedorov
Brendan Shanahan	0.488	0.760	N	Y	0.173	0.395	Pavel Datsyuk
Red Kelly	0.271	0.957	N	N	0.161	0.101	Slava Fetisov
Ebbie Goodfellow	0.568	0.096	Y	Y	0.028	0.173	Vladimir Konstantinov

Russia wins 2-1.

And with that, Russia takes home the championship and answers which region around the world produced the best Red Wings players. The Russian Five, Datsyuk, Danny Markov, Alexey Marchenko, Dmitri Mironov, Yan Golubovsky, Maxim Kuznetsov, Yuri Butsayev, Dmitry Bykov, and Evgeny Svechnikov reign supreme.

Final Word

After four playoff rounds and 13 simulations, Russia proved to be the dominant region for Red Wings players. This shouldn’t be a complete shock given the Russian Five’s dominance, but it was odd that they averaged only two goals per game while others scored more and still lost.

In fact, four regions had higher cumulative scoring probabilities than Russia, including Sweden, who was eliminated in the first round. Talk about puck luck. But then again, the Russian Five’s game plan was all about maximizing puck possession and creating the best—not the most—scoring opportunities. Seems fitting that they won in such a manner, doesn’t it?

Related: Red Wings Rebuild: Complete Offseason Blueprint

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¹I had to bend the scoring probability rules a little bit for two players: Anders Myrvold and Sergei Bautin, who did not score in a Red Wings uniform, but were critical components for forming their region’s team. Essentially, I took Detroit’s average goals per game for the season they played in Hockeytown, divided it by 18 skaters, and estimated they were on the ice for 20 percent of the time in a given game, resulting in scoring probabilities of 0.029 and 0.036 for Myrvold and Bautin, respectively.

²In case of a tie, I summed the cumulative scoring probabilities for both teams, determined the percentage share for both teams, and generated a random number to determine who won in “overtime”. For example, the cumulative total of Ontario’s scoring probabilities is 2.32. For Saskatchewan, it’s 1.77. If the two were tied after the simulation, I’d add 2.32 and 1.77 together and determine their share of the grand total (4.09). Ontario has a 56.7 percent chance of winning (2.32/4.09), so a randomly generated number less than 0.567 would give them the win. Anything higher would equal a win for Saskatchewan.