Unfortunately I didn’t have as much time this week as I had hoped to do a full evaluation of unrestricted free agent centers like I did for wingers but it is free agent day and there was some big news regarding centers yesterday with the buy out of Grabovski so I thought I’d throw a little something together where I look at some offensive statistics of some of the top centers available. Let me start off by presenting you with the summary table.

 G/60 A/60 Pts/60 IPP GF20-TMGF20 FF20-TMFF20 OZBias Ribeiro 0.593 1.512 2.11 80.5 0.113 -0.025 102.6 Filppula 0.769 1.334 2.1 75 0.116 -0.878 104.7 Lecavalier 0.799 1.186 1.99 68.1 0.139 0.381 100.7 Grabovski 0.899 0.961 1.86 65.4 0.196 2.406 96 Roy 0.587 1.146 1.73 67.4 0.039 0.747 98.7 Weiss 0.652 0.821 1.47 65.6 0.07 -0.467 103.3 Bozak 0.566 0.775 1.34 54.2 -0.062 0.292 99.8

The numbers above are 5v5 numbers over the past 3 seasons and the players are sorted by Pts/60. I threw in Lecavalier because he was a UFA for a brief period of time and is at more or less the same level as the others. I included Bozak to highlight just how much he doesn’t fit in with the rest of the group.

• G/60 = Goals per 60 minutes of ice time.
• A/60 = Assists per 60 minutes of ice time
• Pts/60 = Points per 60 minutes of ice time.
• IPP = Individual Points Percentage, or the percentage of goals scored while on ice that the player had a point on.
• GF20-TMGF20 = How much better are his team mates on-ice goal stats when playing with him than without.
• FF20-TMFF20 = How much better are his team mates on-ice shot generation when playing with him than without.
• OZBias = OZ Starts*2 + NZStarts and gives an indication of the players usage.

List sorted by G/60: Grabovski, Lecavalier, Filppula, Weiss, Ribeiro, Roy, Bozak

List sorted by A/60: Ribeiro, Filppula, Lecavalier, Roy, Grabovski, Weiss, Bozak

List sorted by Pts/60: Ribeiro, Filppula, Lecavalier, Grabovski, Roy, Weiss, Bozak

List sorted by IPP: Ribeiro, Filppula, Lecavalier, Roy, Weiss, Grabovski, Bozak

List sorted by GF20-TMGF20:  Grabovski, Lecavalier, Filppula, Ribeiro, Weiss, Roy, Bozak

List sorted by FF20-TMFF20: Grabovski, Roy, Lecavalier, Bozak, Ribeiro, Weiss, Filppula

Mike Ribeiro: Easily the best play maker of the group and is most consistently involved in the play.

Valterri Filppula: Better goal scorer than Ribeiro but not as good as a play maker as Ribeiro but better than the rest.

Vincent Lecavalier: Similar to Filppula in value but better at the possession game.

Mikhail Grabovski: Not a great play maker but a good finisher and good at driving shot generation indicating he is probably good at puck retrieval.

Derek Roy: Kind of a poor mans Ribeiro but much less valuable.

Stephen Weiss: More of a poor mans Lecavalier. Easily had the worst line mates of the group and might do better in a different situation.

Tyler Bozak: Weak at goal scoring, bad at play making, not involved in the play and a drag on his team mates goal production. Not anywhere close to the same league as the others (and maybe be better suited for a different league too).

For me, Ribeiro is probably the best of the group in terms of pure offense because of his elite play making ability. Grabovski and Lecavalier are a little more balanced with better scoring and puck retrieval skills while Filppula is pretty solid all round as well and has the flexibility of being used as either a center or a winger (which is valuable if locking in long-term). It’s difficult to compare Weiss to the rest because he simply hasn’t had near as good of line mates but it is probably safe to say he’d be a bit of a step down from Grabovski, Lecavalier or Filppula. Roy, on the other hand, would definitely be a step back but still a decent consolation prize if on a lower priced contract with shorter term. Definitely not anything more than a #2 center though.

As for Bozak, well, you simply don’t want him on your team. Maybe not at any price no matter what the bargain basement price is. I have tried and tried but I just can’t find any redeeming qualities for him outside of his ability to win face offs which has limited value. There simply is no reason why you would want to play him on any of your top 3 lines. None.

Being a Leaf fan and unable to keep Grabovski, my preference would be Ribeiro or Filppula but might be willing to take a chance on Weiss if the contract was right. Ribeiro’s play making skills with the Leafs wingers should be a good combination and Filppula is a good all round player who could shift to wing down if needed. Weiss seems like a solid 2-way player who might be able to step up his game with better line mates which he’d get with the Leafs. If they sign Bozak, I am not sure what I’ll do. It’ll be a sad day.

I have been on a bit of a mission recently to push the idea that quality of competition (and zone starts) is not a huge factor in ones statistics and that most people in general over value its importance. I don’t know how often I hear arguments like “but he plays all the tough minutes” as an excuse as to why a player has poor statistics and pretty much every time I do I cringe because almost certainly the person making the argument has no clue how much those tough minutes impact a players statistics.

While thinking of how to do this study, and which players to look at, I was listening to a pod cast and the name Pavel Datsyuk was brought up so I decided I would take a look at him because in addition to being mentioned in a pod cast he is a really good 2-way player who plays against pretty tough quality of competition. For this study I looked at 2010-12 two year data and Datsyuk has the 10th highest HART QoC during that time in 5v5 zone start adjusted situations.

The next step was to look how Datsyuk performed against various types of opposition. To do this I took all of Datsyuk’s opponent forwards who had he played at least 10 minutes of 5v5 ZS adjusted ice time against (you can find these players here) and grouped them according to their HARO, HARD, CorHARO and CorHARD ratings and looked at how Datsyuk’s on-ice stats looked against each group.

 OppHARO TOI% GA20 >1.1 46.84% 0.918 0.9-1.1 34.37% 0.626 <0.9 18.79% 0.391

Lets go through a quick explanation of the above table. I have grouped Datsyuk’s opponents by their HARO ratings into three groups, those with a HARO >1.1, those with a HARO between 0.9 and 1.1 and those with a HARO rating below 0.9. These groups represent strong offensive players, average offensive players and weak offensive players. Datsyuk played 46.84% of his ice time against the strong offensive player group, 34.37% against the average offensive player group and 18.79% against the weak offensive player group. The GA20 column is Datsyuk’s goals against rate, or essentially the goals for rate of Datsyuk’s opponents when playing against Datsyuk. As you can see, the strong offensive players do significantly better than the average offensive players who in turn do significantly better than the weak offensive players.

Now, let’s look at how Datsyuk does offensively based on the defensive ability of his opponents.

 OppHARD TOI% GF20 >1.1 35.39% 1.171 0.9-1.1 35.36% 0.994 <0.9 29.25% 1.004

Interestingly, the defensive quality of Datsyuk’s opponents did not have a significant impact on Datsyuk’s ability to generate offense which is kind of an odd result.

Here are the same tables but for corsi stats.

 OppCorHARO TOI% CA20 >1.1 15.59% 15.44 0.9-1.1 77.79% 13.78 <0.9 6.63% 10.84

 OppCorHARD TOI% CF20 >1.1 18.39% 15.89 0.9-1.1 68.81% 18.49 <0.9 12.80% 22.69

I realize that I should have tightened up the ratings splits to get a more even distribution in TOI% but I think we see the effect of QoC fine. When looking at corsi we do see that CF20 varies across defensive quality of opponent which we didn’t see with GF20.

From the tables above, we do see that quality of opponent can have a significant impact on a players statistics. When you are playing against good offensive opponents you are bound to give up a lot more goals than you will against weaker offensive opponents. The question remains is whether players can and do play a significantly greater amount of time against good opponents compared to other players. To take a look at this I looked at the same tables above but for Valtteri Filppula, a player who rarely gets to play with Datsyuk so in theory could have a significantly different set of opponents to Datsyuk. Here are the same tables above for Filppula.

 OppHARO TOI% GA20 >1.1 42.52% 1.096 0.9-1.1 35.35% 0.716 <0.9 22.12% 0.838

 OppHARD TOI% GF20 >1.1 32.79% 0.841 0.9-1.1 35.53% 1.197 <0.9 31.68% 1.370

 OppCorHARO TOI% GA20 >1.1 12.88% 19.03 0.9-1.1 78.20% 16.16 <0.9 8.92% 14.40

 OppCorHARD TOI% GF20 >1.1 20.89% 15.48 0.9-1.1 64.94% 17.16 <0.9 14.17% 19.09

Nothing too exciting or unexpected in those tables. What is more important is how the ice times differ from Datsyuk’s across groups and how those differences might affect Filppula’s statistics.

We see that Datsyuk plays a little bit more against good offensive players and a little bit less against weak offensive players and he also plays a little bit more against good defensive players and a little bit less against weak defensive players. If we assume that Filppula played Datsyuk’s and that Datsyuk’s within group QoC ratings was the same as Filppula’s we can calculate what Filppula’s stats will be against similar QoC.

 Actual w/ DatsyukTOI GF20 1.135 1.122 GA20 0.905 0.917 GF% 55.65% 55.02% CF20 17.08 17.09 CA20 16.37 16.49 CF% 51.05% 50.90%

As you can see, that is not a huge difference. If we gave Filppula the same QoC as Datsyuk instead of being a 55.65% GF% player he’d be a 55.02% GF% player. That is hardly enough to worry about and the difference in CF% is even less.

From this an any other study I have looked at I have found very little evidence that QoC has a significant impact on a players statistics. The argument that a player can have bad stats because he plays the ‘tough minutes’ is, in my opinion, a bogus argument. Player usage can have a small impact on a players statistics but it is not anything to be concerned with for the vast majority of players and it will never make a good player have bad statistics or a bad player have good statistics. Player usage charts (such as those found here or those found here) are interesting and pretty neat and do give you an idea of how a coach uses his players but as a tool for justifying a players good, or poor, performance they are not. The notion of ‘tough minutes’ exists, but are not all that important over the long haul.