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.

Red Wings' Best of All-Time: Where Did They Come From? Gordie Howe, Steve Yzerman, Nicklas Lidstrom
Which region is best? (The Hockey Writers)

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.


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.

Henrik Zetterberg of the Detroit Red Wings.
Henrik Zetterberg’s 2007-08 season was his best in Hockeytown. (Amy Irvin / The Hockey Writers)

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.

Red Wings' Best of All-Time: Where Did They Come From? Gordie Howe, Steve Yzerman, Nicklas Lidstrom Bracket
Sixteen regions, one champion. Who’s going to triumph over the rest? (The Hockey Writers)

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.

Darren Helm Detroit Red Wings
Darren Helm and Manitoba move on to the second round. (Amy Irvin / The Hockey Writers)

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.

Jakub Kindl of the Detroit Red Wings.
Remember Jakub Kindl? (Rick Osentoski-US PRESSWIRE)

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.

Alex Delvecchio of the Detroit Red Wings.
Alex Delvecchio and Ontario are on a roll. (THW Archives)

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.

Sergei Fedorov of the Detroit Red Wings
Sergei Fedorov and the Russian Five have dominated so far. (Tom Pigeon/Allsport)

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.

Pavel Datsyuk of the Detroit Red Wings.
It’s official: Russia has produced the best Red Wings players. (Photo Credit: Andy Martin Jr)

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

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.