From "CMMI: Guidelines for Process Integration and Product Improvement" by Chrissis, Konrad, and Shrum (btw, I would not recommend to ANYONE that they read this unless they have to):
"The purpose of Measurement and Analysis (MA) is to develop and sustain a measurement capability that is used to support management information needs....
Specifying the objectives of M&A such that they are aligned with identified information needs and objectives...
Providing objective results that can be used in making informed decisions, and taking appropriate corrective actions."
Translation: take measurements of something useful that you can do something about.
The best parts about stats are that they're objective and can be used to aid in decision-making, both individual (making better choices with the disc) and team (allocating playing time or determining strategies).
The easiest way to improve with stats is to identify strong negatives (or to use them to prove their existence to doubters). Player A is 1 for 10 on his hucks. Player B throws away 2 break marks a game. The team has not forced a break when playing zone D all year. These things will stand out on their own without any additional analysis needed. The corrective action will require some analysis, but you know that you have a problem. For Player A, you need to decide whether to improve his throws, tweak his decisions, or get him to stop hucking.
The next thing to do is to establish baselines, which won't be the same for everyone, owing to skill level, role, and reward-level of their throws. 88% completion might be borderline acceptable for an aggressive thrower who racks up a lot of goals and big yards, but cause for action for someone who only dumps it or who takes risky but not useful throws.
Now, at this point I'm not expecting anyone to actually establish numerical baselines. Besides being too much work, there are probably too many other confounders that your limits wouldn't be legitimate. But you can, as a captain or coach or even as an individual, establish goals for each player. Be aware, though, that a player might overcompensate on the risk/reward decision in order to improve that completion percentage. (In the earlier stat entry, gambler asked whether anyone played to the stats by making suboptimal decisions. I commented at the time that stat-padding (going for fantasy league stats instead of smart, solid play) was limited to blowout games, but I neglected the other side of suboptimal play.)
Maybe the largest benefit of stat-keeping as we know it is that it forces introspection. Although a player may deceive himself, he is also the one who is most aware of each of his plays. Stats can force a player to look at each of his miscues and reevaluate whether he made a good decision.
Finally, recognize that a Holy Grail of stats is not going to be available for a long time. There will not be any reliable way to roll up all of a player's offensive contributions into a single number. Accept this, and accept that any stat you keep is going to be just one aspect of production that is linked to the other aspects, and you might just find that you can learn something.
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In the same vein of high-level ideas that stats can be used for:
Stats can offer evidence to support or counter a theory.
Ultimate example: let's say I think two players play well together. I can track the team results when they are not in, both in, or just one of them is in. I can use the results to decide whether I should try to play them together or whether it really doesn't matter.
Similar example: I think a given player is more useful on offense (or going upwind). Track the team results with and without this player, when they are or are not on offense. Use the results to decide whether this player should be an O player or not.
A problem we face in our sport, though, is putting too much weight on statistically insignificant data. That is, in how many tournaments (or points, or touches) will a player have to participate so that we can be reasonably sure his or her statistics aren't an aberration? Granted, if a player's statistics aren't impressively good or bad, it probably seems insignifant. But it's not insignifant if that player performs statistically well over 2 or 3 tournaments, but over the long run will put up very poor numbers. You could be setting the team up to rely on a liability.
Related to what both of you said, ultimate stats can be used as a springboard to study some questions. If you find a player performing above expectations or perception, then take a detailed look at whether the statistical improvement is a fluke, a measure of the incompleteness of the stat system (maybe the 100% completion rate was due to being saved a few times and throwing nothing but dumps), or a real improvement.
Good statistical analysis tries to answer questions to get at underlying truths. Although you may have to slice and dice data, it's not about the numbers.
But it's not insignifant if that player performs statistically well over 2 or 3 tournaments, but over the long run will put up very poor numbers. You could be setting the team up to rely on a liability.
A buddy of mine had the idea to take stats during practice as well to get a bigger sample size...
It may be that practice is the best time to take stats since the quality of opponent varies little. (You'll still get variability due to wind, fatigue, incomplete attendance, mixing the teams up, etc., but it will be less than at a tournament where you'll win some games 15-2 while losing others.)
(Aside: I got "ortizd" for my word verification. Ironic, since Ortiz plays less D than Alex, whose name has occasionally been spelled "e Frondeville."
Jim: This thread begs the question, "what stats do you use?" I suspect the answer is different for measuring O vs. D players.
Care to share that info?
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