Skip to main content

Predators vs. Sharks, Round One Preview

Our first playoff preview digs into the eagerly awaited #4 vs. #5 matchup in the West, between the Nashville Predators and San Jose Sharks. Last year, these two teams met in the first round and the Sharks dispatched the Preds in five games, largely attributed to two factors; the first being Nashville's inability to stay out the penalty box, and secondly, the advantage the Sharks had at the center position. Since that time, the Predators have upgraded significantly at the center spot (a couple guys named Arnott and Forsberg come to mind), and they've done a better job at staying on the positive side of the special-teams equation as well. Both teams have ranked among the NHL elite all season long, and are slotted 1st and 3rd in mc79hockey's Adjusted Goal Differential. But what does my analysis say about how these two teams match up?


For table explanation, scroll down to the bottom of this post.

How Nashville can score: The Predators' strength seems to be in perimeter scoring - their shooting percentage from outside of 10 feet is above average in all the different range slots, especially from 50+ feet, where they score almost twice as much as the rest of the league. The Sharks goaltending might well have a weakness there, as their save percentage in the 50-59 foot range is second-worst among playoff teams. That could translate into key goals for skilled Nashville blueliners like Shea Weber and Kimmo Timonen.



How San Jose can score: The vast majority (3.22 out of 3.74 total) of San Jose's goals are expected to come in the 10-29 foot range, where the perfect combination comes into play. The Sharks generate more shots there than average, they score at a higher than average rate, the Preds give up a relatively high number of those shots, and their goaltenders fare poorly in stopping them. The 10-19 and 20-29 foot ranges are the only ones in which Nashville's goaltending is subpar, yet those are exactly the ones in which San Jose is the strongest. That, to me, spells trouble for the Predators.

Summary: This picture is pretty ugly for Nashville - it says that on neutral ice, the Sharks would be expected to outscore the Predators 3.74 to 3.01. If we use Jeff Sagarin's rule of thumb, giving the home team in each game a credit of 0.25 Goals, San Jose still leads 3.74/3.26 for the games in Nashville, and dominates 3.99/3.01 at home.

Outside the Numbers: There are some factors that aren't reflected in these numbers that might play a role in this series. Nashville winger Martin Erat may well return for the playoff opener, and Scott Hartnell came back for the final two games of the regular season. If they (along with newly returned Scott Nichol) are able to play at or near 100%, perhaps that 0.73 goals per game differential gets reduced, but I highly doubt they're enough to swing the balance of power in Nashville's favor, even presuming all three are able to contribute effectively.

The Prediction: In all honesty, as much as I would love to see the Preds make a deep run in this postseason, this matchup doesn't look good for them. Based on what I'm seeing, everything would have to go right for Nashville to make this a coin flip, so I'm going with San Jose in 6 games.
-----------
Table Key:
Shots For = average of shots per game by that team, from the range specified.
Shots Factor = a factor representing how many shots the opposing defense yields in that range (1.24 = 24% more than average, 0.89 = 11% less than average).
Exp. Shots = "Shots For" times "Shots Factor", how many shots are expected to occur within each range.
Sht % = The fraction of shots from within that range result in goals.
Sht % Factor = a measure reflecting how the opposing goaltender handles shots from a given range (0.74 = 26% fewer goals than average, 1.53 = 53% more than average)
Exp. Sht % = "Sht %" times "Sht % Factor", the expected shooting percentage for this matchup.
Exp. Goals = "Exp. Shots" times "Exp. Sht %", the number of goals per game expected from each range.
Values indicative of significantly higher goal-scoring are shaded green, values for lower goal-scoring shaded pink.
All figures represent exponential moving averages, giving greater weight to recent performance. Empty-net goals and Penalty Shots are excluded.

Popular posts from this blog

Celebrating a milestone month

I've been remiss in providing regular updates on my quest to turn this whole sports-blogging hobby into at least something of a significant side income, if not a career, but good news has a way of prompting action. That, and I've been heads-down busy working on a few different fronts to push things forward...

Social Media, Internet Marketing, and Real, Paying Customers - it really works!

Applying the basic tenets of internet marketing (SEO best practices and social media network building) have helped me grow the readership and engagement over at On The Forecheck tremendously in recent years, but lately I've been wondering if those same techniques could be applied to small- or medium-sized local businesses, to help them drive real, tangible business results. I'm talking about not just drawing idle hockey fans looking to a blog so they can muse over line combinations, but helping businesses connect with potential customers in ways that otherwise wouldn't occur. Recently, I was able to help make just such a thing happen, and it shows just how great the opportunities are for small, local businesses which may not have the resources or skills available to extend their brand effectively on the internet.

NHL Fake Trades, an idea worth pursuing further in 2013

As I wrote about a month ago , I decided to jump upon a short-term opportunity and set up a "hot topic" website for the 2012 NHL Trade Deadline. NHLFakeTrades.com was inspired by a column by Eric Duhatschek of the Globe & Mail, who looked at the frenzy with which hockey fans jump on even the sketchiest of information about potential hockey trades, and wondered if some cash could be made by simply and forthrightly writing about fictitious trade scenarios. This meshed nicely with an exercise I went through a few years ago to create a Random Trade Generator, so in the course of a few hours I went ahead and registered the domain, set up a WordPress site using ( as I do at Hockey Gear HQ ) the wonderful Genesis framework with the News theme , and freshened up the Trade Generator for 2012. So how did it do, in terms of traffic, revenue, and accuracy of the trade projections? Let's take a look...