Jun 302015
 

I am sure this post will rattle some feathers in the Hockey Analytics community but hey, it won’t be the first time I have accomplished that.

I have been looking through the list of potential free agents looking for players that are possibly under valued, possibly over valued, or otherwise interesting for one reason or another. There has been a fair bit of discussion around the three players that are the focus of this post. Justin Williams has been a favourite of the hockey analytics community posting outstanding Corsi numbers year after year. Alexander Semin, who was bought out by the Carolina Hurricanes is one of those guys that seems to be hated by coaches, scouts, general managers, and “traditional hockey people” but analytics people look at his numbers and, last season aside, they look outstanding. Matt Beleskey is an unrestricted free agent that hockey analytics people want to warn teams about because he is coming off a career year with 22 goals driven largely by a high, and unsustainable, shooting percentage. The hockey analytics community are predicting he will be one of those guys teams will over pay for and regret the decision a year from now. So, I figured it would be worth while taking a deep look at these players because from my observations the deeper you look the more interesting things become and the story potentially changes.

I am rushing a bit to put this post together so it may come across as just me throwing out some numbers and charts. I apologize for that but bear with me, there is an interesting story that will develop.

For this post all numbers will be 5v5close numbers to minimize the impact of score effects. I am also going to focus on my RelTM statistics which look at how each player influences his line mates. It is like a combined WOWY analysis where we can determine whether the players teammates perform better with him or apart from him.

Corsi

Let’s look at the corsi statistics first starting with the offensive and defensive components and then corsi percentage.

SeminWilliamsBeleskey_CF60RelTM

Here higher is better as it means teammates have a higher CF60 with them than apart from them. The 3-year average is their CF60RelTM over the past 3 seasons. For the most part Williams is the best, Beleskey is the worst and Semin bounces around a bit.

SeminWilliamsBeleskey_CA60RelTM

Here lower is better as it indicates there are fewer shots against when players are playing with them than apart from them. Things looked a little differently this past season but prior to that Williams was always better than Beleskey and Semin bounced around a bit. This past season both Beleskey and Semin were better than Williams.

SeminWilliamsBeleskey_CFPctRelTM

 

Higher is better on this chart. What we see is Beleskey is getting better, Williams is getting worse and Semin is relatively stagnant or maybe a slight drop off. Last season the three players were almost identical. One has to wonder if age effects are taking place here as Beleskey is 27 years old and has been entering his prime years and Williams is 33 years old and is starting to leave his prime years. Semin is 31 has been in his prime years and may just be starting his decline.

Goals

Corsi is a useful metric but I believe if you have multiple seasons worth of data you have to look at the goal data for trends as well because goals are what really matters. What is interesting is that with these three players it tells a somewhat different story.

SeminWilliamsBeleskey_GF60RelTM

Recall that for CF60 RelTM we saw Williams always better than Beleskey and Semin bouncing around a bit. Here we see Beleskey starting off below Semin and Williams but the past couple of seasons has surpasses both of them and has had the better GF60 RelTM. Once again Beleskey is improving, Williams and Semin have fallen off some.

SeminWilliamsBeleskey_GA60RelTM

Lower is better so this is pretty much a repeat of GF60 RelTM. Beleskey is improving and has easily had the better GA60 RelTM, particularly the past two seasons.

SeminWilliamsBeleskey_GFPctRelTM

As one would expect, Beleskey clearly has the better CF% RelTM the past couple seasons. What is interesting is hockey analytics favourite Justin Williams has had a negative GF%RelTM in 3 of the past 4 seasons despite having a CF%RelTM well above 0 in each of the last four seasons. Beleskey has had four straight seasons with a GF%RelTM above zero.

The Percentages

To summarize the above charts, Justin Williams looks far better when looking at Corsi than when looking at goals while for Beleskey it is almost the opposite. Furthermore Williams seems to be starting to show his age and starting to decline while the younger Beleskey appears to still be improving. To explain the divergence between Corsi and goals data lets have a look at two more charts: Sh%RelTM and Sv%RelTM.

SeminWilliamsBeleskey_ShPctRelTM

Higher is better on this chart. Williams has consistently been the worst on this list and has generally been at or below 0 meaning his team mates generally post better shooting percentages when not playing with Williams as opposed to playing with him. Beleskey on the other hand has always had a positive impact and Semin for the most part does as well (save for 2013-14).

SeminWilliamsBeleskey_SvPctRelTM

Beleskey’s Sv%Rel numbers are what really got me to investigate him far more deeply. He has posted positive Sv%RelTM numbers for five straight years (2010-11 not shown) and they seem to be improving as well.  Contrast that to Justin Williams who has had a negative Sv%RelTM in four of the past 5 seasons with only 2012-13 breaking that trend.

Aside: I get that people are skeptical that players can influence save percentage (I’ve seen and done the research) but I have also seen too many players show consistent trends to believe that it can’t and doesn’t happen. I have shown recently that coaches generally don’t dole out ice time based on defensive statistics which leads me to believe that it isn’t a trait that coaches emphasize. If coaches don’t emphasize it, it is understandable why not many players exhibit that skill. This would make it difficult to find league-wide correlations but it doesn’t mean that players with these skills don’t exist. It in fact could actually be a sign of untapped value.

Point Production

The last couple of charts I want to present are related to point production. First lets look at 5v5 close Points/60.

SeminWilliamsBeleskey_PtsPer60

What is interesting here is how much better Beleskey has been the past two seasons and how both Semin and Williams have experienced an equally significant drop off. Is aging a factor in these trends?

SeminWilliamsBeleskey_IPP

 

IPP is the percentage of goals that are scored when the player is on the ice that the player had a point (goal or an assist) on. This is an indication of how involved the player is in the offense that is being created when he is on the ice. Until this past season Williams numbers were pretty good while Semin went from OK to terrible this past season. It appears that both Semin and Williams had anomaly seasons but again, is aging a factor here. Conversely Beleskey appears to be improving and his last two seasons were very respectable, particular for a player who also seems to have good defensive numbers.

In Summary

  • There is ample evidence that Justin Williams possession (corsi) statistics are over inflating his value as he has fairly consistently had a poor influence on both shooting and save percentages.
  • There is also ample evidence that Justin Williams is already into his declining years and giving him a longer term contract may not be wise.
  • Beleskey on the other hand appears to be better overall than his possession statistics indicate and also appears to still be improving in all aspects of the game as he has entered his prime years.
  • Semin once had outstanding statistics no matter what you looked at. He has shown a decline the past two seasons and last season he fell off the cliff in a number of areas statistically. At only 31 if the price was reasonable he is worth the gamble on a shorter term contract because if he can get anywhere close to where he was he’d be outstanding value.

My final thought is likely to generate some buzz and controversy amongst the analytics crowd but of the three players I believe Matt Beleskey may be the best currently and almost certainly will be the best over the next several seasons as Williams and Semin age and Beleskey continues in his prime years. There, I said it. Discuss amongst yourselves.

 

Jul 232014
 

Tyler Dellow has an interesting post on differences between the Kings and Leafs offensive production. He comes at the problem from a slightly different angle than I have explored in my rush shot series so definitely go give it a read. These two paragraphs discuss a theory of Dellow’s that is interesting.

That’s the sort of thing that can affect a team’s shooting percentage. To take it to an extreme, teams shot 6.2% in the ten seconds after an OZ faceoff win this year; the league average shooting percentage at 5v5 is more like 8%. Of course, when you win an offensive zone draw, you start with the puck but the other team has five guys back and in front of you.

I wonder whether there isn’t something like that going on here that explains LA’s persistent struggles with shooting percentage (as well as those of New Jersey, another team that piles up Corsi but can’t score – solving this problem is one of the burning questions in hockey analytics at the moment). It’s a theory, but one that seems to fit with what Eric’s suggested about how LA generates the bulk of their extra shots. It’s hard for me to explain the Leafs scoring so many more goals in the first 11 seconds after a puck has been carried in, particularly given that I suspect that LA, by virtue of their possession edge, probably enjoyed many more carries into the offensive zone overall.

Earlier today I posted some team rush statistics for the past 7 and past 3 seasons. Let’s look in a little more detail how the Leafs, Kings and Devils performed over the past 3 seasons.

Team RushGF RushSF OtherGF OtherSF RushSh% OtherSh% Rush%
New Jersey 45 540 103 1675 8.33% 6.15% 24.4%
Toronto 66 523 128 1675 12.62% 7.64% 23.8%
Los Angeles 53 609 112 1978 8.70% 5.66% 23.5%

The Leafs scored the most goals on the rush despite the fewest rush shots due to a vastly better shooting percentage (nearly 50% better than the Devils and Kings) on the rush. They do not generate more shots on the rush, but do seem to generate higher quality shots.

The Kings generate by far the most shots in non-rush situations but have the poorest shooting percentage and thus do not score a ton of goals. The Devils don’t generate many non-rush shots and don’t have a great non-rush shooting percentage either and thus posted the fewest goals. The Leafs have had the same number of shots as the Devils but a significantly higher shooting percentage than the Devils and thus scored significantly more non-rush goals.

The Leafs scored 34% of their goals on the rush compared to 32% for the Kings and 30% for the Devils.

Are the Leafs a good rush team? Well, only Boston has scored more 5v5 road rush goals than the Leafs so probably yes but it is mostly because of finishing talent, not shot generating talent. They are 4th last in 5v5 road rush shots.

The Ducks have very similar offense to the Leafs. They don’t get many rush shots but post a really high rush shooting percentage. Anaheim generate a few more non-rush shots than the Leafs but they are very similar offense.

The Kings are a slightly better rush team than the Devils but neither are good and both are weak shooting percentage teams regardless of whether it is a rush or non-rush shot. The Kings make up for this though by generating a lot of shots from offensive zone play where as the Devil’s don’t.

 

Apr 052013
 

Yesterday HabsEyesOnThePrize.com had a post on the importance of fenwick come playoff time over the past 5 seasons. It is definitely worth a look so go check it out. In the post they look at FF% in 5v5close situations and see how well it translates into post season success. I wanted to take this a step further and take a look at PDO and GF% in 5v5close situations to see of they translate into post season success as well.  Here is what I found:

Group N Avg Playoff Avg Cup Winners Lost Cup Finals Lost Third Round Lost Second Round Lost First Round Missed Playoffs
GF% > 55 19 2.68 2.83 5 1 2 6 4 1
GF% 50-55 59 1.22 1.64 0 2 6 10 26 15
GF% 45-50 52 0.62 1.78 0 2 2 4 10 34
GF% <45 20 0.00 0 0 0 0 0 20
FF% > 53 23 2.35 2.35 3 2 4 5 9 0
FF% 50-53 55 1.15 1.70 2 2 1 10 22 18
FF% 47-50 46 0.52 1.85 0 0 4 3 6 33
FF% <47 26 0.54 2.00 0 1 1 2 3 19
PDO >1010 27 1.63 2.20 2 2 2 6 8 7
PDO 1000-1010 42 1.17 1.75 1 0 5 7 15 14
PDO 990-1000 47 0.91 1.95 2 1 3 4 12 25
PDO <990 34 0.56 1.90 0 2 0 3 5 24

I have grouped GF%, FF% and PDO into four categories each, the very good, the good, the mediocre and the bad and I have looked at how many teams made it to each round of the playoffs from each group. If we say that winning the cup is worth 5 points, getting to the finals is worth 4, getting to the 3rd round is worth 3, getting to the second round is worth 2, and making the playoffs is worth 1, then the Avg column is the average point total for the teams in that grouping.  The Playoff Avg is the average point total for teams that made the playoffs.

As HabsEyesOnThePrize.com found, 5v5close FF% is definitely an important factor in making the playoffs and enjoying success in the playoffs. That said, GF% seems to be slightly more significant. All 5 Stanley Cup winners came from the GF%>55 group while only 3 cup winners came from the FF%>53 group and both Avg and PlayoffAvg are higher in the GF%>55 group than the FF%>53 group. PDO only seems marginally important, though teams that have a very good PDO do have a slightly better chance to go deeper into the playoffs. Generally speaking though, if you are trying to predict a Stanley Cup winner, looking at 5v5close GF% is probably a better metric than looking at 5v5close FF% and certainly better than PDO. Now, considering this is a significantly shorter season than usual, this may not be the case as luck may be a bit more of a factor in GF% than usual but historically this has been the case.

So, who should we look at for playoff success this season?  Well, there are currently 9 teams with a 5v5close GF% > 55.  Those are Anaheim, Boston, Pittsburgh, Los Angeles, Montreal, Chicago, San Jose, Toronto and Vancouver. No other teams are above 52.3% so that is a list unlikely to get any new additions to it before seasons end though some could certainly fall out of the above 55% list. Now if we also only consider teams that have a 5v5close FF% >50% then Toronto and Anaheim drop off the list leaving you with Boston, Pittsburgh, Los Angeles, Montreal, Chicago, San Jose and Vancouver as your Stanley Cup favourites, but we all pretty much knew that already didn’t we?

 

Feb 232012
 

The Columbus Blue Jackets have traded Jeff Carter to the Los Angeles Kings for Jack Johnson and a first round pick.  When Johnson signed his current 7 year, $30.5M contract I wrote how I thought the Kings would regret the contract.  Now I think the Blue Jackets will.

Just how bad is Jack Johnson?  Well, lets take a look at the Kings defensemen’s goals against per 20 minutes of zone start adjusted 5v5 close ice time over the past 2 3/4 seasons.

Defenseman 11-12 GA20 Defenseman 10-11 GA20 Defenseman 09-10 GA20
Martinez 0.471 Martinez 0.465 Harrold 0.418
Voynov 0.473 Greene 0.580 Greene 0.451
Doughty 0.495 Drewiske 0.635 Doughty 0.499
Mitchell 0.504 Harrold 0.715 Scuderi 0.517
Scuderi 0.557 Mitchell 0.764 O’Donnell 0.543
Greene 0.571 Doughty 0.785 Drewiske 0.682
Johnson 0.727 Scuderi 0.831 Jones 0.755
Johnson 1.054 Johnson 0.906

Not only is Jack Johnson dead last in all three seasons, he is last by a sizeable margin.  Of the 7 Kings defensemen this year the spread between #1 Martinez and #6 Greene is smaller than the spread between #6 Greene and #7 Johnson.  The previous two seasons look no better.

But what is even more scary are Johnson’s offensive numbers.  Yeah, Johnson may be a question mark defensively but his offense helps offset some of that.  Well, so we thought.  Here are the goals for per 20 minutes of ice time numbers for Kings defensemen.

Defenseman 11-12 GF20 Defenseman 10-11 GF20 Defenseman 09-10 GF20
Voynov 1.014 Harrold 1.072 Scuderi 0.791
Martinez 0.848 Mitchell 1.030 Doughty 0.774
Greene 0.694 Doughty 0.999 O’Donnell 0.744
Doughty 0.637 Martinez 0.802 Drewiske 0.744
Mitchell 0.612 Drewiske 0.714 Greene 0.708
Scuderi 0.590 Scuderi 0.712 Johnson 0.647
Johnson 0.485 Greene 0.709 Jones 0.519
Johnson 0.671 Harrold 0.314

Dead last in 2 of the three seasons and only ahead of Randy Jones and Peter Harrold in 2009-10.  Certainly not something to write home about.  So, if Johnson isn’t helping his team score goals and isn’t helping his team limit goals against, he has to have a pretty terrible goals for percentage (goals for divided by goals for + goals against).  Let’s take a look.

Player Name GF% Player Name GF% Player Name GF%
Voynov 0.682 Martinez 0.633 Greene 0.611
Martinez 0.643 Harrold 0.600 Doughty 0.608
Doughty 0.562 Mitchell 0.574 Scuderi 0.605
Greene 0.548 Doughty 0.560 O’Donnell 0.578
Mitchell 0.548 Greene 0.550 Drewiske 0.522
Scuderi 0.514 Drewiske 0.529 Harrold 0.429
Johnson 0.400 Scuderi 0.462 Johnson 0.417
Johnson 0.389 Jones 0.407

It’s pretty sad when every other defenseman on your team has a goals for percentage above 50% and you sit at 40%.

It seems that Jack Johnson is a major drag on his team, especially defensively, but offensively as well.  The only redeeming quality of Jack Johnson on the ice is that he seems to be a good PP specialist.  I have often called Jack Johnson the $4.3M/yr version of Marc-Andre Bergeron but that might be unfair to Bergeron.  Getting rid of Johnson is addition by subtraction plus you are getting Jeff Carter for a mere first round pick which is a steal.

The Kings win this trade by a country mile while the Blue Jackets have set back their franchise years by the whole Carter fiasco which has seen them trade Jakub Voracek, Sean Couturier and Nick Cousins (3rd round pick in 2011) for a horrid Jack Johnson and a mid first round pick.  Pretty sad for any Blue Jacket fan.