Friday 29 August 2014

Puckerings archive: Search for Meaning in RTSS (22 Oct 2001)

What follows is a post from my old hockey analysis site puckerings.com (later hockeythink.com). It is reproduced here for posterity; bear in mind this writing is over a decade old and I may not even agree with it myself anymore. This post was originally published on October 22, 2001 and was updated on April 10, 2002.
 

The Search for Meaning in RTSS:Hits and Takeaways
Copyright Iain Fyffe, 2002
Many thanks to Marc Foster


In 1997-98, the NHL introduced its Real-Time Scoring System (RTSS). This computerized system allows the tracking of many new official statistics, such as ice time, blocked shots and hits. This has given a wealth of new data to perform statistical analysis with. But there is a serious question: do the new statistics really mean anything?

Ice time is obviously a meaningful stat. The amount of time a player spends on the ice is a direct comment on his value, relative to his teammates. But do stats like hits or takeaways really indicate anything, or are they just numbers? In this essay, I will show that, indeed, hits and takeaways do have value.

If a statistic is to have value, it must indicate something about a player or team. Hits and takeaways would seem to indicate how aggressive a player is, by either making physical contact with the opponent, or by pressuring him and taking the puck away. But is this good thing? The best way to answer this question is to determine if the actions represented by these stats contribute to winning. After all, the point of hockey is to win the game. If hits and takeaways contribute to winning, then they are meaningful stats.

I will examine these statistics by using correlation to team winning percentage. If the stat has a positive coefficient of correlation, we know that as the value of the stat increases, so does the team's winning percentage. The stat would therefore contribute to winning to some degree.
The raw stats of hits (H) and takeaways (TK) themselves have little value. Here are their correlations to winning percentage, as well as the correlation of the sum of hits and takeaways (H+TK):

 97/98  98/99  99/00  00/01  Average
 H  -.04  -.01  -.30  .20  -.04
 TK  n/a  .02  -.04  .19  .06
 H+TK  n/a  .01  -.25  .26  .01

So the raw numbers themselves have absolutely no relationship to winning or losing. By themselves, these stats are just numbers. Faced with this fact, we can try to develop a new stat using these raw data, to see if we can find any meaning.

My thought process for developing this new stat (called the Disciplined Aggression Proxy, or DAP, for reasons which will become apparent) was as follows. Perhaps the reason that hits and takeaways did not correlate highly with winning was because the aggressive play represented by these stats can often lead to taking penalties. Perhaps if a team were able to play in this aggressive manner while taking relatively few penalties, they would be more successful. At first, I used only hits in the formulae, not adding takeaways until it this was suggested by Marc Foster. There are two ways to represent penalties on a team level: penalty minutes (PIM) and times short handed (TSH). TSH is theoretically superior, since it represents actual short-handed situations, but as we will see, there is little difference between the two. The original DAP formulae were as follows:

Version 1: H / PIM
Version 2: H / TSH

I then tested the correlations for these formulae, with the following results:

 97/98  98/99  99/00  00/01  Average
 Version 1  .30  .26  .01  .39  .24
 Version 2  .18  .26  -.02  .47  .22

As you can see, the DAP formulae added much meaning to the stats. The correlations were now out of the range of having no meaning, into a range (.20 and thereabouts) where we cannot simply write the relationship off as a fluke. The 1999/2000 season seems to be a fluke; without it the average correlation would be higher still. To further test the validity of the DAP, I reasoned the following. A team that kills penalties well will suffer less from taking penalties. Therefore, I calculated a new index for each team, to represent both their relative aggression and their relative penalty-killing ability. To do this I took the team's DAP divided by the league DAP, and added the team's penalty-killing percentage (PK), divided by the league average PK. This number is only used as a rough test, as it has no real meaning. The results of this are as follows:

 97/98  98/99  99/00  00/01  Average
 V.1 + PK  .36  .30  .10  .43  .30
 V.2 + PK  .25  .30  .10  .47  .43

The correlations are even higher, which lends more validity to the value of the DAP. Again, note the apparent flukiness of the 1999/2000 season.

But the development of the DAP did not end there. Marc Foster suggested the inclusion of takeaways along with hits to represent aggressive play, and this change is a good one. I therefore defined two new versions of the DAP:

Version 1A: (H + TK) / PIM
Version 2A: (H + TK) / TSH

The correlations for these are as follows:

 97/98  98/99  99/00  00/01  Average
 Version 1A  n/a  .27  .03  .42  .24
 Version 2A  n/a  .26  .02  .50  .26

Note that the averages here is misleading; we should only compare them against averages for the same three-year period. These averages are .22 for Version 1 and .24 for Version 2. The improvement is small, but still there. I also ran correlations including the teams' PK, as before:

 97/98  98/99  99/00  00/01  Average
 V.1A + PK  n/a  .31  .13  .47  .30
 V.2A + PK  n/a  .30  .14  .57  .34

These are the highest correlations we've seen. The averages for Versions 1 and 2 over this period are .28 and .31 respectively.

Therefore, by transforming hits and takeaways into the Disciplined Aggression Proxy, we have found meaning in two of the NHL's new statistics. Now let's apply our new stat.

When applying the DAP to players, I recommend using Version 1A. This is because there is no player-level stat for the number of times shorthanded. The number of minor penalties taken by a player would be a fair approximation, but this data is rarely available. And since Version 1A is only marginally worse than Version 2A, there is no great loss. I will now discuss some players who have the best ranking in DAP (Version 1A) over the past two years. The new stat will shed some new light on the value of some of these players.

1. John Madden
Madden has ranked 2nd in the NHL in DAP each of the past two years. This is remarkable consistency. He is known as perhaps the best checking forward in the game, and this reputation is well-deserved.

2. Curtis Leschyshyn
Due to his pitiful offence, Leschyshyn is not given the respect he deserves. He placed 8th in DAP in 1999/2000, and 4th last year. He is truly an elite player when it comes to aggressive yet disciplined play, and he deserves much more respect than he gets.

3. Ulf Dahlen
Dahlen was 11th two years ago and 7th last year; he's another remarkably consistent performer. He gets credit as good defensive forward, but perhaps not enough.

4. Jeff Nielsen
This defenceman was 15th in 1999/2000, and 8th in 2000/01. He's basically an unknown, but hopefully not for long. His aggressive play deserves respect.

5. Steve Rucchin
He was 18th in 1999/2000, and would have placed very highly last year had he not been injured. He has significant offensive skill to complement his aggressive play.

6. Jay Pandolfo
Pandolfo led the NHL in DAP in 1999/2000, but slipped to 27th the following year. Still, that's a very good ranking, and he deserves kudos for it. With Pandolfo and Madden, the Devils have been loaded with good, aggressive, talent.

7. Sami Kapanen
Another player whose reputation is as a strong two-way forward, Kapanen ranked 13th in 1999/2000 and 16th in 2000/01. He deserves his reputation.

8. Josef Stumpel
The first surprising player on the list, Stumpel is known as a high-skill forward who often does not give his all. But he ranked 10th in DAP in 1999/2000, and 20th last year. You may not notice his aggressive play, but it's there. Don't call this guy a floater anymore.

9. Juha Lind
Lind was in the top 30 in 1999/2000, and rose to 3rd last year. His unfortunate lack of offensive skill has hurt his playing time, but he is a good grinder.

10. Sergei Berezin
Another surprise, Berezin is regarded as a skilled, soft player. But he was 6th in 1999/2000, and in the top 30 last year.

Other noteworthy players

Viktor Kozlov, Jody Hull, James Black, Andrew Cassels, Patrick Poulin, Don Sweeney, Robert Kron, Sergei Brylin, Jonas Hoglund and Mike York all deserve credit for their aggressive yet disciplined play over the last two years. Some are already known as two-way players, some are not but probably deserve to be. Also worth noting are two rookies from last year, Stephane Robidas (5th in DAP) and Brent Sopel (6th). Keep an eye on these players. They are solid contributors to their teams.

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