Update: Predicting the 2019 NHL Stanley Cup Playoff Results

Oof. Not even close.

First Round
  • Calgary Flames vs Colorado Avalanche
  • San Jose Sharks vs Vegas Golden Knights
  • Nashville Predators vs Dallas Stars
  • Winnipeg Jets vs St. Louis Blues
  • Tampa Bay Lightning vs Columbus Blue Jackets
  • Boston Bruins vs Toronto Maple Leafs
  • Washington Capitals vs Carolina Hurricanes
  • New York Islanders vs Pittsburgh Penguins

Sharks made it to the Conference Finals. That’s pretty much as far as I got correct.

Random coinflips predicted the First Round better than I did at a 37.5% accuracy vs my 12.5%.

Congrats Blues on the cup win.

Predicting the 2019 NHL Stanley Cup Playoff Results

Here are my predictions for the 2019 Stanley Cup Playoffs. Winners in turquoise.

First round

  • Calgary Flames vs Colorado Avalanche
  • San Jose Sharks vs Vegas Golden Knights
  • Nashville Predators vs Dallas Stars
  • Winnipeg Jets vs St. Louis Blues
  • Tampa Bay Lightning vs Columbus Blue Jackets
  • Boston Bruins vs Toronto Maple Leafs
  • Washington Capitals vs Carolina Hurricanes
  • New York Islanders vs Pittsburgh Penguins

Second round

  • Calgary Flames vs San Jose Sharks
  • Nashville Predators vs Winnipeg Jets
  • Tampa Bay Lightning vs Toronto Maple Leafs
  • Washington Capitals vs Pittsburgh Penguins

Conference Finals

  • San Jose Sharks vs Winnipeg Jets
  • Tampa Bay Lightning vs Washington Capitals

Stanley Cup Final

  • San Jose Sharks vs Tampa Bay Lightning

The above was constructed by me, a human, using hockey knowledge. The following is another prediction for the NHL Stanley Cup Playoffs using best of seven random coin flips to determine the winner for each pair. Let’s see if I can predict the results with better accuracy than random coin flips. Will report back after the playoffs.

First round

  • Calgary Flames vs Colorado Avalanche
  • San Jose Sharks vs Vegas Golden Knights
  • Nashville Predators vs Dallas Stars
  • Winnipeg Jets vs St. Louis Blues
  • Tampa Bay Lightning vs Columbus Blue Jackets
  • Boston Bruins vs Toronto Maple Leafs
  • Washington Capitals vs Carolina Hurricanes
  • New York Islanders vs Pittsburgh Penguins

Second round

  • Colorado Avalanche vs San Jose Sharks
  • Nashville Predators vs Winnipeg Jets
  • Tampa Bay Lightning vs Boston Bruins
  • Carolina Hurricanes vs Pittsburgh Penguins

Conference Finals

  • Colorado Avalanche vs Nashville Predators
  • Tampa Bay Lightning vs Pittsburgh Penguins

Stanley Cup Final

  • Colorado Avalanche vs Pittsburgh Penguins

Frequency of Scores in the NHL 2017-2018 Regular Season

“How many goals are usually scored in a hockey game?”

I had this question the other day and wanted to find out. A quick google search gave me this list of all game results from the 2017-2018 season. I wanted to visualize this data so decided to use R to generate a heat map of score frequencies.

Eventually, I ditched using R because I couldn’t for the life of me get the graphs to look pretty. Meanwhile, a copy and paste of data into Google Sheets and a couple minutes of clicking gave me the output I wanted. Friendly reminder to all to use the appropriate tool for the task.

Here’s what I found:

This answers the original question–most hockey games will end around the neighborhood of a 2-1, 3-2, or 4-3 score. I posted this on Reddit and an interesting question was asked a few times. What would this graph look like if I adjusted scores in overtime and shootout wins? In the NHL, if a team ends in the 3rd period with a tied score, they go into a 3v3 5-minute sudden-death overtime period. If no goal is scored during that overtime, the teams go into a shootout. Ultimately, one team will win and will be award the extra point onto their score.

This could be inflating the frequency of “N to N-1” scores.

I found the easiest way to adjust for overtime and shootout wins was to simply take all games that ended with an OT or SO and subtract one point from the winning team–essentially turning the chart into the scores at the end of the third period of regulation. Here is that adjusted chart:

Now this is interesting. Updated observations: Most hockey games fall around the 3ish to 7ish total goals scored and there is a higher frequency of games ending in ties and games ending in 2-goal leads than there is of games ending in 1-goal leads. Notice that cells in the diagonal for 1-goal leads are lower in frequency than their neighbors to the right and to the bottom. e.g. a 1-0 score happened 15 times, but a 2-0 score happened 33 times and a 1-1 score happened 59 times. This continues until the sample sizes drop.

Why would this be? The simplest explanation would probably be the strategy of trailing teams pulling their goalie in the final moments of the third period.

In the NHL, the season is structured in the following way. All teams compete over the course of 82 games, each, and acquire points for each game win/loss/overtime or shootout. These accumulated points determine playoff seeding at the end of the season. The league awards 2 points for each win, 1 point for each overtime or shootout loss, and 0 points for each loss that doesn’t go into overtime. That means that a regulation loss is a loss, no matter what the score differential was by the end of the game.

In addition to the season structure, NHL rules allow for the goalie to be replaced with an extra skater at any point during play. Thus, it has become very common in the NHL for a team that is trailing by 1 in the final moments of the third period to replace their goalie with another skater in desperation. This makes sense. If our team is trailing by a goal, and it doesn’t matter in terms of playoff seeding points if we lose by another goal, it is worth the risk for us to do what we can to tie the game and send the game into overtime to maybe squeeze 1 point out of this game to affect our overall playoff standings.

Putting it all together, the NHL season structure + the rules for pulling a goalie could be contributing factors to inflation of frequencies of tied games (pulling the goalie worked) and games that ended in a 2 goal lead (pulling the goalie backfired and the other team scored on an empty net).

How Important is Height in Hockey?

During my last recreational league hockey season, my captain had me play center. My favorite part (aside from face-offs) was the increased defensive responsibilities. I think it would be a fun idea to switch to defense for a season. However, I’m a bit concerned that at 5’7″ (67 inches) tall, I would be seen as too small to effectively play defense. I decided to check NHL stats and throw something together in R. Data includes all players currently in the NHL as of June 20, 2018.

Based on my findings, it looks like there is a lot of variation across each position. Sure, the trend seems to be that players are taller the further back in the rink they are, but there is a lot of overlap in distributions of heights for each position.

  • Median heights across all players is only about 3-5 inches taller than average males
  • Roughly speaking, centers and wings are around the same height
  • Heights for defensemen closely resemble the spread of heights for forwards, but shifted up about an inch
  • Goalie is the one position where someone of my height playing the position would be a large outlier

After seeing the data, I don’t think that hockey has too much specialization based on height. Yeah, I’m not the tallest person, but especially for a rec league, I shouldn’t be discouraged from playing any position. I’ll sign myself up to play D next season.

Who are the Sharks’s Playmakers?

Similar to the last post, here is a visualization made with R of the players’ assists awarded over the last 5 seasons.  Graph only includes players with at least 5 full NHL seasons of data and is not adjusted for games missed due to injuries.

  • Note: Mikkel Boedker was traded this morning to the Ottawa Senators.
  • There weren’t any particularly notable exclusions from this list. Closest might be Kevin Labanc, who had a season high 29 assists last season, but only 2 full seasons of data to pull from.
  • I mentioned Patrick Marleau in the last post. If he were included in this post, he’d fall around where Mikkel Boedker or Logan Couture are listed: He has a median assists count of 23 with a 5-season high of 38 in 2014-2015.
  • John Tavares has a 5-season median of 42 assists with a high of 48 assists in 2014-205. If John Tavares were inserted into this graph, he’d fall right between Burns and Pavelski. Not bad!

Who are the Sharks’s Goal-Scorers?

There has been some off-season talk about the San Jose Sharks making a push to trade for John Tavares of the New York Islanders. Tavares has been a strong goal-scorer for the Islanders, having been in the top 3 on his team for goals scored every season since being drafted in 2009.

I wanted to better understand how goal scoring was distributed among the Sharks to make it easier to imagine Tavares being added to the line-up. I threw this visualization together using R to help out.

Data includes goals scored per San Jose Sharks player since the 2013-2014 NHL season. I only included current SJ Sharks players with at least 5 full NHL seasons of data. Data is not adjusted for games played, so games missed due to injuries are reflected in the graph. I think this is fair because a skilled goal scorer is useless if he isn’t also durable. Can’t put points on the board if you aren’t playing.

Thoughts:

  • Based on John Tavares’s last five seasons, the median for his goals scored would be 33 and his best was 38 in 2014-2015. If included on this graph, he’d be the 2nd strongest goal scorer, right after Pavelski.
  • Patrick Marleau was (sadly) traded to the Toronto Maple Leafs ahead of the 2017-2018 season. If he was never traded, he’d appear on this chart between Pavelski and Couture with a median goals scored of 27 and a season-high of 33 goals in 2013-2014.
  • Of the recent Sharks additions excluded from this list, the only skaters with decent goal counts for a single season are Timo Meier (21 goals in 2017), Chris Tierney (17 goals in 2017), Joonas Donskoi (14 goals in 2017), and Kevin Labanc (11 goals in 2017).  However, none of these are particularly impressive and these players will likely end up charted near the middle around Hertl or Boedker.
  • As expected, defensemen occupy the bottom of the list. The clear exception here, of course, is Brent Burns. Seeing him occupy the 3rd highest slot despite being a defenseman is impressive.
  • Admittedly, I didn’t realize Joe Pavelski’s production was that much higher than the rest of the team.
  • Washington Capitals’s Alexander Ovechkin’s 5-year running goal median is 50. Wow. The Sharks need one of those.

2018 Stanley Cup Playoff Conclusion

Capitals beat the Golden Knights 4-1. With the ongoing joke being that the Caps are just the Sharks of the Eastern Conference, I suppose I could say that my original pick for the winner was right all along, I just had the wrong conference. I’m very happy to see Washington finally get their win and I suppose the “Caps West” label for the Sharks can’t be applied anymore.

Highlights of this series for me:

  • Devante Smith-Pelly was a joy to watch. You could see him putting in max effort during every shift, and it paid off. In only 24 playoff games, Smith-Pelly matched his goal count of 7 goals that he scored during the regular season.
  • Braden Holtby’s “The Save” + nervous Ovi during the final moments of game 2. It gave Washington their first win may have very well been the source of the momentum that carried them through their next 3 wins.
  • The simple fact that we had a Las Vegas vs Washington D.C. match-up. I’m always in favor of anything that spreads awareness of of this sport that I enjoy watching and playing. Having a finals between a brand new hockey market (Vegas) and a team fighting for their very first championship (Washington) will likely bring in new fans.

Predictions/Hopes for next season

  • Healthy Joe Thornton at 1C and contributing as he did before his injuries
  • Sharks do not win any major trades or acquisitions (e.g. Tavares or Kovalchuk) but their 3rd and 4th forward lines and bottom defensive pairings blossom in the 2018-2019 season. Boedker has a breakout year.
  • Injury-free Evander Kane
  • Joe Pavelski evolves his playing style. As legendary as he is at fighting for space in front of the net and tipping shots, I worry this play style is diminishing in effectiveness. Pavelski’s goal counts have almost monotonically decreased since 2013-2014. With the projected 2018-2019 top line being Kane-Thornton-Pavelski, the Sharks run the risk of having a very slow top line. I’d like to see a bit more symmetry between Kane’s and Pavelski’s speed of movement so there’s always someone opening up for Thornton to feed.

2018 NHL Playoff Predictions Finals Update

See last post here.

Wowwwww. Vegas Golden Knights vs Washington Capitals in the NHL Stanley Cup finals. A team making it to the finals in its inaugural year + a team that has been in the finals 27 times since 1974 but has never won the Stanley Cup. A historic year for hockey and a treat for sport fans that value league parity (contrast with the NBA finals, where the Golden State Warriors have faced the Cleveland Cavaliers in the finals every year since 2015).

Anyway, let’s keep the prediction post organized like the previous ones.

What went right

Washington did beat Tampa Bay. Prediction accuracy for the last round was 1 of 2 (50%).

What went wrong

Winnipeg fell to Vegas after 5 games. My hope of a Jets sweep was far off.

Thoughts on the Finals

Las Vegas (1) vs Washington (1)

Capitals, take my ༼ つ ◕_◕ ༽つSHARKS FAN energy

Vegas’s depth > Caps’s depth. Also Fleury > Holtby. However, Caps in 4 because that’s what I want. Or 5. Or 6. Or 7. Pls

 

 

2018 NHL Playoffs Predictions 2nd Round Update

Ooof. Owie. First round predictions weren’t bad. Second round? Not good.

What went right

Really not a whole lot to say, here. Tampa Bay did end up beating Boston to fix that quadrant of my bracket, but that’s about all I got right. Prediction accuracy in this round was 1 for 4 (25%).

What went wrong

  • RIP Sharks. I knew the Golden Knights were going to be a tough team to beat and that if the Sharks were going to win, it would take a full 7 games. Sadly, San Jose didn’t make it that far; Vegas took the series in 6 games.
  • Caps beat the Penguins! I’m happy to have gotten this one wrong.
  • I thought that Nashville would dominate Winnipeg but Winnipeg ended up winning the series after 7 games. I know very little about Winnipeg but they must be doing something special to have survived against what I consider to be a very stacked team. I’m looking forward to using this as an opportunity to learn more about the Jets.

Thoughts on next matchups

Las Vegas (1) vs Winnipeg (2)

I’m on the Jets bandwagon. I can’t even name more than 3 players on the roster but I’d love to watch them eliminate Vegas. It would be educational to see what it finally took to knock out the Golden Knights. Jets in 4 because that’s what I want.

Tampa Bay (1) vs Washington (1)

Go Sharks East Capitals! Washington in 6.

2018 NHL Playoffs Predictions 1st Round Update

Update from my playoff predictions post now that the 1st Round has ended.

What went right

  • Correctly guessed the winner in 7 of 8 matchups (87.5%)
  • Sharks did end up beating the Ducks despite being the lower seed. Not only that, they swept.

What went wrong

  • Boston (2) vs Toronto (3). I wanted Toronto to win this one despite being the lower seed. Series ended up going 7 games and Toronto fell apart in the last period of game 7.
  • I was all over the place in my predictions for how short/long series would last. Some examples: In both the Kings vs Golden Knights and the Sharks vs Ducks series, I predicted they would last a full 7 games. In both cases, the winning team went undefeated and finished the series early at 4. My predictions for series length were only correct in 2 of the 8 matchups (25%)
  • Joe Thornton did not make an appearance as I predicted.

Thoughts on next matchups

Nashville (1) vs Winnipeg (2)

Again, I find Nashville to be the dominant team. I’d say Nashville in 4 but Colorado took 2 games from them in the previous round so I’ll adjust my prediction to Nashville in 6.

Las Vegas (1) vs San Jose (3)

Uhhh Las Vegas is spooky but I underestimated how San Jose would do in the last round. Scattered thoughts: San Jose never once beat the Golden Knights during the regular season. Sharks have more depth (IMO) than they have ever had in recent memory so if they are going to win this one, it might take 7 games.

Tampa Bay (1) vs Boston (2)

Boston knocked out my Round 1 prediction so I want Tampa Bay to win to fix my bracket. Boston looked like a strong playoff team against Toronto but Tampa Bay has had plenty of time to rest whereas Boston’s series went 7 games. Tampa Bay in 6.

Washington (1) vs Pittsburgh (2)

Oh boy! Big matchup. I’m not as familiar with the Capitals’s top lines/pairings as well as I am with the Penguins’s, but I know the Penguins’s top lines/pairings are scary. Pittsburgh in 6.