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Post by coachklee on Dec 26, 2015 8:20:27 GMT -6
I'm not going to argue that different forms of data analysis is highly applicable, especially if it is correlated to film and broken down in terms of specific plays.
The big difference though as alluded to earlier in the thread between what was done in baseball & made famous in Moneyball is that the use of stays was much more oriented towards acquiring the best player value for the lowest possible value. Additionally, there are way less variables in each play of a baseball game then there is in each play of a football game causing the baseball statistics to be more "normalized". Additionally, we don't really have the option to get different players, but instead have to develop those incoming 7th graders or 9th graders in the weight room and out on the field.
Lastly, statistics can only tell you trends that have already happened. And while everything can be described by math, if you are waiting for some statistic to tell you a DB is too aggressive & play-action will score the next play or your DL is getting reached causing your LBs pursuit to be too long which keeps giving them 4-5 yard gains you are never going to be able to make any adjustments to change the outcome of the game.
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Post by fantom on Dec 26, 2015 8:49:09 GMT -6
I'm sure it's shocking that a young QB coach who isn't an OL guy and doesn't watch the OL on video wouldn't recognize that. But then you've probably forgotten more football than I know (which is why none of this seems necessary to you). Thankfully, when I crank out a Hudl report based on run direction and DL alignment, and I see that we're not gaining yards running to the 1-tech, it gives me reasons to look closer at that video to figure out why. Without the data, I wouldn't have seen that. That same data showed us that our gap runs were great to the 1-tech, so we made adjustments and started flipping our back to attack him. On the pass concepts, we didn't really know what the problem was, but when we are getting 1.2 YPA on a downfield throw, they had to go. Looking over the video now (when there's more time), it's clear that I sucked at teaching the progressions and our WRs didn't run a couple of routes very well. Fortunately, rather than stubbornly insisting that they're good schemes, we trusted the data and adjusted. That data helped me focus on things that probably seem like second nature to you. In a nutshell, the "metrics" just seem to quantify what your years of experience have taught you. They also provide specific, measurable goals for coaches and players to aim for in our process to achieve the ultimate goal of winning. As Bill Walsh said, if you focus on the right things, the score takes care of itself. GOOD data can show us what those things are. Yes. The problem is I don't think you guys are implementing a successful blue print if you need to "crank out a HUDL report based on run direction and DL alignment" to recognize that your center was not doing his job correctly. There is a breakdown in this process. I certainly think there is a breakdown in the process if the person who is making those adjustments/decisions is not a part of recognizing it on film. The things you are describing should have been taken care of after a Saturday Morning (or friday night) film review. If the person who has the authority to make those changes doesn't watch the OL, then they better have supreme confidence that the OL coach would bring that to his attention-- "Hey, OC, we are having problems with OZ because Johnny just can't block a shade. He is stepping with the correct foot, he is bringing his hips, he just isn't strong enough, but he is the best we have. So lets go ahead and scrap that and just GAP block" IF the OL coach isn't doing that, then the OC needs to watch ALL the positions. THAT is how the process should be handled. Of course, I am sure you will now say how you guys have won 3 state titles, and this works for you.. so whatever. Whether it's scouting opponents or self-scouting, I think that a lot of staffs are so preoccupied with inputting data that they forget to WATCH the film.
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Post by silkyice on Dec 26, 2015 9:06:42 GMT -6
Yes. The problem is I don't think you guys are implementing a successful blue print if you need to "crank out a HUDL report based on run direction and DL alignment" to recognize that your center was not doing his job correctly. There is a breakdown in this process. I certainly think there is a breakdown in the process if the person who is making those adjustments/decisions is not a part of recognizing it on film. The things you are describing should have been taken care of after a Saturday Morning (or friday night) film review. If the person who has the authority to make those changes doesn't watch the OL, then they better have supreme confidence that the OL coach would bring that to his attention-- "Hey, OC, we are having problems with OZ because Johnny just can't block a shade. He is stepping with the correct foot, he is bringing his hips, he just isn't strong enough, but he is the best we have. So lets go ahead and scrap that and just GAP block" IF the OL coach isn't doing that, then the OC needs to watch ALL the positions. THAT is how the process should be handled. Of course, I am sure you will now say how you guys have won 3 state titles, and this works for you.. so whatever. Whether it's scouting opponents or self-scouting, I think that a lot of staffs are so preoccupied with inputting data that they forget to WATCH the film. BAM!
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Post by natenator on Dec 26, 2015 9:08:40 GMT -6
Very simply, we use data to inform our decisions during the season and the offseason. In-season, we evaluate our run and pass concepts weekly using Hudl data and custom reports. After week 4, we axed two pass concepts because we had thrown more picks than completions on them and had never targeted our rhythm routes (sure signs that we have a problem). We also adapted our run game because our gap scheme was averaging over 6 yards per carry while our outside zone was netting only 4. That led to consecutive 300-yard rushing games. Offseason, we evaluate our run and pass concepts against different fronts and coverages. I can tell you that Stick killed cover 2 but didn't do as well against man coverage. How do I know? By looking at the numbers in Hudl. The "old-timer" response might be that they could see that on film and don't need the numbers. Unfortunately, I don't have 30+ years of coaching experience to fall back on when I watch film. I haven't seen everything a team might do to defend my offense. I don't necessarily know that our outside zone stinks because our center can't reach the playside 1-tech. But when the data show me that, I'm able to make adjustments so my players are put in a better position to succeed. Maybe in 20-some years, I'll be good enough to simply watch film and know exactly what the problem is. I'm not there yet, though, so I have to use all the tools at my disposal to even the playing field with coaches who ARE good enough to do that. For me, data is one of those tools that helps me gain an edge. I'd be doing my players a disservice if I didn't use that tool. I'm just a dumb DC and it didn't take more than a few clips to know that my 1 tech was continually getting beat by the centre on outside zone in our second game this year, I don't have 20 years of coaching experience either.
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Post by silkyice on Dec 26, 2015 9:14:33 GMT -6
Everyone's looking for an edge, whether you agree or disagree w the methodology of finding said edge there's nothing wrong with it (if you aren't on that staff you disagree with). I do find statistical breakdowns helpful but not sure if they fall under metrics or self scouting. I look at what I'd assume a DC would look at to put in tweaks, break tendencies for big play potential, etc. I also want to know what plays and formations they've seen on our official trade film. I also look at percentages to see if we are who we think we are. I've been a part of staffs where the HC or whomever thought we were a blank team or were only successful when we established blank when in actuality we weren't very good at that or we didn't run that play nearly as much as they thought so that's why the auxiliaries werent successful. I've also run stats to see exactly what specific QBs were best at or most comfortable with. Sometimes our memories and eyes, just like data, can be skewed by one big play or bad play. I think this is a good post. But, the comment that nothing is wrong with it is not always true. What if that time, effort, energy, money was spent somewhere else? There is a cost to everything. I also think, let me start over. I also KNOW that if someone puts a lot of time, effort, and energy into something, they will have to justify it somehow. So whether or not that data really gives them USEFUL information or not, something will be data mined either for the benefit or detriment of the team.
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Post by CS on Dec 26, 2015 9:39:08 GMT -6
Everyone's looking for an edge, whether you agree or disagree w the methodology of finding said edge there's nothing wrong with it (if you aren't on that staff you disagree with). I do find statistical breakdowns helpful but not sure if they fall under metrics or self scouting. I look at what I'd assume a DC would look at to put in tweaks, break tendencies for big play potential, etc. I also want to know what plays and formations they've seen on our official trade film. I also look at percentages to see if we are who we think we are. I've been a part of staffs where the HC or whomever thought we were a blank team or were only successful when we established blank when in actuality we weren't very good at that or we didn't run that play nearly as much as they thought so that's why the auxiliaries werent successful. I've also run stats to see exactly what specific QBs were best at or most comfortable with. Sometimes our memories and eyes, just like data, can be skewed by one big play or bad play. I think this is a good post. But, the comment that nothing is wrong with it is not always true. What if that time, effort, energy, money was spent somewhere else? There is a cost to everything. I also think, let me start over. I also KNOW that if someone puts a lot of time, effort, and energy into something, they will have to justify it somehow. So whether or not that data really gives them USEFUL information or not, something will be data mined either for the benefit or detriment of the team. That's an interesting metric. Time committed to calculating metrics vs. useful information that comes from it. For example how many minutes of data processing results in points ?
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Post by 44dlcoach on Dec 26, 2015 10:05:21 GMT -6
I'm inclined to try to measure things in numbers just by my nature but I agree that there is a big difference between the self scouting type of numbers and that metrics that just show how you did.
I like to go back at the end of the season and determine our points per possession defensively but the only thing it does is satisfy my curiosity and the only thing I use it for is my own comparison of this year's team to previous teams, and even then I recognize that's it's just a comparison of how each team performed against its peer group. It takes a couple hours to figure out so if I've got the free time I do it to satisfy my curiosity, if it took 10 hours I wouldn't do it because I really don't get anything of value from that metric.
I also go back and tag every run and pass play and like to run a little report to show how much each "concept" was called against us, and I will actually use that data to influence what we work against the most in the Spring. For example, if 50% of the runs called against us our either Power or Zone Read, I want to know that when I'm scripting practice against an "imaginary" opponent.
I won't be strictly tied to that report I'll also use my own experience and judgment to determine what we will introduce in the spring, which concepts reinforce our fundamentals the most clearly, etc. but if the teams we play think the way to beat our coverage is Smash then I want to make sure we are very clear on how to defend it.
I hope I'm making my point clearly, but to me there is a difference between the self scouting or opponent scouting metrics, and the "how did we do" type metrics. I like to calculate both, but the "how did we do" ones only really get used to compare one teams performance to past teams, not overly useful for determining what we'll do next year. The self scouting type of numbers will actually impact how much time we spend against certain stuff as we introduce the scheme next year.
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Post by bignose on Dec 26, 2015 11:00:12 GMT -6
I look at metrics as broad generalities that may, or may not, affect your tactical thinking during the game.
As I mentioned earlier, I look at these as a part of the decision making process to help improve the odds in your favor. There are always going to be exceptions to these metrics due to the fluid nature of the situations that occur during the game.
As an example: You are 4 th and 2 at the 50 yard line. You are ahead by fours points. Are your odds better in going for the first down, and possibly giving your opponent the ball at midfield, or are you better off punting?
What are the odds. What are the risks versus the rewards?
Variables to consider: your punter, your ability to get the kick off, your opponents ability to return a punt, your offenses' ability to grind out a short gain, your opponents chances of driving for 50 yards or 80 yards. Some of this falls under the category of "Calculated Risk." Are you a Poker player who is going to raise with a pair of 2's?
This is where the metric of points versus starting field position could be considered. Me, I'm of the school of thought of: "Give them a long way to go, and not much time to get there."
Scouting and specific data are tools in which you can gather and apply information into the decision making process, both before and during the game, once again, to put you into the best position to win.
"Knowledge is Power" (unless you are in a "Game of Thrones" situation where you are bigger and better than your opponent). In that case "Power is Power!"
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guck
Sophomore Member
Posts: 130
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Post by guck on Dec 26, 2015 11:54:38 GMT -6
WOW I posted a question on the 23rd that I thought was a legit "football question" and I guess I whacked a hornets nest (grumpy old Man). My post disappeared, under the avalanche of old school vs new school thinking. Sorry if I pissed in anybody's Wheaties.
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Post by lochness on Dec 26, 2015 15:02:50 GMT -6
I don't think it has anything to do with "old school vs new school thinking." I think that's just as limited as saying the shotgun is "new school" and the T is "old school."
It's a question of VALUE.
What value do you get out of metric that has a measurable impact on the way you conduct your business as a coach...and if you do change your methods as a result of these metrics, how do you know that the changes directly help you win football games.
I have yet to see one answer that comes even close to explaining this. The closest thing to a true, self-aware answer I've seen is someone admitting that they like numbers and the analysis helps quench their curiosity.
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Post by coachd5085 on Dec 26, 2015 15:19:59 GMT -6
I don't think it has anything to do with "old school vs new school thinking." I think that's just as limited as saying the shotgun is "new school" and the T is "old school." It's a question of VALUE. What value do you get out of metric that has a measurable impact on the way you conduct your business as a coach...and if you do change your methods as a result of these metrics, how do you know that the changes directly help you win football games. I have yet to see one answer that comes even close to explaining this. The closest thing to a true, self-aware answer I've seen is someone admitting that they like numbers and the analysis helps quench their curiosity. lochness I will say this much--if the use of these metrics spurs discussion and thought about the process then that probably has some value to it. I guess a lot of my surprise just comes with the processes, and reading coaches saying that without an exhaustive data analysis, they would not have noticed their players were not executing. Of course I shouldn't be surprised. I have worked with staffs who thought the idea of holding up a scout card showing the opponents play to the scout team was revolutionary. They previously had made the HS playoffs by just scrimmaging offense vs defense each practice...
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Post by 44dlcoach on Dec 26, 2015 16:40:48 GMT -6
I do think that we get a lot of value from the breakdown of what the opposing run and pass concepts we saw were in the previous year and the relative frequency that they were called against us. I'm not sure that those types of things were really what coachd5085 was referring to when the thread was started, but I can say that those percentages will in fact have a direct impact on how I script practice in the spring and summer when we are getting ready for the season.
I look at practice as being mostly about us and getting better at what we do, but some component of it is also about getting prepared for what you think the other guys are going to do. The best data I have for that before a season is what the other guys did last year, so that's what we use.
Now some of the others like how many points per possession we scored, yards per points, or things like that will never cross my mind when I'm planning practice or coaching on the field.
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jmg999
Junior Member
Posts: 263
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Post by jmg999 on Dec 26, 2015 17:48:24 GMT -6
Just a side note, for those suggesting that they saw something right away after a few plays or a few games and didn't need to see more to know that a change needed to be implemented, apply that logic elsewhere. If you flipped a coin 10 times, and it came up seven heads and three tails, you would have wrongly concluded that flipping a coin would, on average, deliver a 70% production of heads. This datum point would be rendered incorrect based on the size of the sample. Small samples sizes are the death of otherwise good data.
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Post by spos21ram on Dec 26, 2015 17:58:52 GMT -6
Just a side note, for those suggesting that they saw something right away after a few plays or a few games and didn't need to see more to know that a change needed to be implemented, apply that logic elsewhere. If you flipped a coin 10 times, and it came up seven heads and three tails, you would have wrongly concluded that flipping a coin would, on average, deliver a 70% production of heads. This datum point would be rendered incorrect based on the size of the sample. Small samples sizes are the death of otherwise good data. That analogy really doesn't work. If I'm watching a team's season of game film and they fumbled 9 times in the first 4 games I watched them...I'm gonna go out on a crazy limb and say they really need to work more practice time on ball security. If half those fumbles were bad shotgun snaps then we need more work on snaps, if the fumbles were a bad mesh point then u work on that. Now if I watch the last 7 games and they only fumbled 4 times in that span, then my first inclination would be 2 things, they stopped giving those that fumbled carries or 2, they practiced more ball security. Sent from my SAMSUNG-SM-G900A using proboards
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Post by coachd5085 on Dec 26, 2015 18:09:42 GMT -6
Just a side note, for those suggesting that they saw something right away after a few plays or a few games and didn't need to see more to know that a change needed to be implemented, apply that logic elsewhere. If you flipped a coin 10 times, and it came up seven heads and three tails, you would have wrongly concluded that flipping a coin would, on average, deliver a 70% production of heads. This datum point would be rendered incorrect based on the size of the sample. Small samples sizes are the death of otherwise good data. See, that is the point-- you are looking to "change something". What I (and it appears several others ) are trying to say is that we TRY AND CORRECT the thing we "saw right away". It isn't a "small sample size". It is an error. Watch game film. If kids are playing with high pad level, emphasize that. If it was one play that he got whooped on..show him on film to emphasize. If kid can't reach shade because he is stepping with wrong foot, that is not a small sample size. That is bad technique. If kid can't reach shade because he is not physically big strong enough, and upcoming opponent has a strong shade make an adjustment. Not sure what you do for a paycheck, but I do know that some central office somewhere would love to have you as an Educational Reform Administrator.
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Post by coachbdud on Dec 26, 2015 18:11:53 GMT -6
this was the first year i tagged every snap of the season on hudl i have run a lot of reports to see what worked best for us and to validate the things we are doing offensively
i know that overall our offense worked well, maxpreps stats tell me we were first in our section in scoring, rushing, and total yards per game i know we broke every school scoring, rushing, and total yard record
but looking further into the data and using hudl to do all the real number crunching i learned some things we were explosive as heck! more points than plays this season, and we scored a TD every 7 snaps
looking further into actual play and formation data i can compare play results to see exactly which plays gave us the best yards per carry we were better at counter and bucksweep than our regular 2 back power
i also found that anytime we were in a formation with at least 1 wing our yards per carry increased i also found that our yards per play on some of our deep shots was good, our percent of explosive plays on deep shots was higher than i realized
so i know i need to look back and see what made our 2 back power not work as well... was it our mistakes or was it just defensive alignment/assignment to overload our Fb side, and that is why our counter averaged so much more YPC
i know that we need to install and work our wing plays earlier, and use that more often... it became a big addition to our offense as the year progressed. I know i need to call more of our wing counter (averaged 13 ypc, our highest ) and a couple more shots a game wouldnt hurt
now i am looking at metrics from an assessment perspective, not a "goal setting" perspective
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Post by 19delta on Dec 27, 2015 13:10:32 GMT -6
Bill James began circulating The Baseball Analyst in June of '82. It took almost two decades for teams to fully buy in, but once they did, the changes were remarkable. Sabermetric ideas literally changed the way the game was played. Basketball is going through this now, and hockey is one of the most data analysis-enlightened sports around. Soon enough, football will be affected. Agreed that SABR is almost wholly responsible for the new focus on data and metrics in sports. The problem is that football and baseball are fundamentally different games. Baseball really isn't a team sport...it's an individual sport played in a team format. As a result, it is actually quite easy (and good management strategy) to collect as much data as possible on each player. In baseball, the use of SABR-type metrics really do tell the story about the value of a particular player. On the other hand, football is truly a team game. A football player's success is largely dependent on his teammate's performance and the playcalling of coaches. There are too many external variables out of the control of the individual football player for the use of SABR-type analytics to be useful.
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jmg999
Junior Member
Posts: 263
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Post by jmg999 on Dec 27, 2015 15:42:06 GMT -6
Bill James began circulating The Baseball Analyst in June of '82. It took almost two decades for teams to fully buy in, but once they did, the changes were remarkable. Sabermetric ideas literally changed the way the game was played. Basketball is going through this now, and hockey is one of the most data analysis-enlightened sports around. Soon enough, football will be affected. Agreed that SABR is almost wholly responsible for the new focus on data and metrics in sports. The problem is that football and baseball are fundamentally different games. Baseball really isn't a team sport...it's an individual sport played in a team format. As a result, it is actually quite easy (and good management strategy) to collect as much data as possible on each player. In baseball, the use of SABR-type metrics really do tell the story about the value of a particular player. On the other hand, football is truly a team game. A football player's success is largely dependent on his teammate's performance and the playcalling of coaches. There are too many external variables out of the control of the individual football player for the use of SABR-type analytics to be useful. I hear this same argument over and over in these forums, but the problem is, it doesn't hold any water. If the external variable argument were true, it would mean that researchers would not be able to explain much more complicated, open systems, such as the Universe or the human body. Hell, even the mechanics of the human eye or simply how body movement works is astronomically more complicated than the game of football. The reason that there seems to be such reluctance to this idea is that no one is researching football. If researchers turned their attention away from the sciences to football, there are plenty of ways to exclude external variables in clinical trials. It's done every day in the sciences. It's not magic, and it's not overly complicated. It's just something that is required to be accounted for in all calculations.
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Post by silkyice on Dec 28, 2015 7:59:01 GMT -6
Agreed that SABR is almost wholly responsible for the new focus on data and metrics in sports. The problem is that football and baseball are fundamentally different games. Baseball really isn't a team sport...it's an individual sport played in a team format. As a result, it is actually quite easy (and good management strategy) to collect as much data as possible on each player. In baseball, the use of SABR-type metrics really do tell the story about the value of a particular player. On the other hand, football is truly a team game. A football player's success is largely dependent on his teammate's performance and the playcalling of coaches. There are too many external variables out of the control of the individual football player for the use of SABR-type analytics to be useful. I hear this same argument over and over in these forums, but the problem is, it doesn't hold any water. If the external variable argument were true, it would mean that researchers would not be able to explain much more complicated, open systems, such as the Universe or the human body. Hell, even the mechanics of the human eye or simply how body movement works is astronomically more complicated than the game of football. The reason that there seems to be such reluctance to this idea is that no one is researching football. If researchers turned their attention away from the sciences to football, there are plenty of ways to exclude external variables in clinical trials. It's done every day in the sciences. It's not magic, and it's not overly complicated. It's just something that is required to be accounted for in all calculations. What clinical trials are you talking about? And you are wrong about the game of football. There are WAY more variations in a game of football then in the universe. It isn't even close. Quick example. Do you know what a googol is? It is a 1 followed by 100 zeroes. Or 1 x 10^100 or simply 10^100. It is estimated that there are only 10^81 or so atoms in the entire known universe which is not even close to a googol. But yet, if you try to arrange 70 items, there are more than a googol ways of arranging those things. 70 cards, 70 desks, 70 people, 70 pencils. It doesn't matter. Just one more perspective, there are roughly 8 times as many ways to arrange 60 objects than there are atoms in the universe!! What does this have to do with football and the eye? The eye is already arranged. All you have to do is study it. The game of football has an extreme number of variables and arrangements and someone else is trying to stop what you are trying to do and they have an extreme number of ways to try and stop you.
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Post by Chris Clement on Dec 28, 2015 12:05:14 GMT -6
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Post by coachklee on Dec 28, 2015 12:30:30 GMT -6
Bill James began circulating The Baseball Analyst in June of '82. It took almost two decades for teams to fully buy in, but once they did, the changes were remarkable. Sabermetric ideas literally changed the way the game was played. Basketball is going through this now, and hockey is one of the most data analysis-enlightened sports around. Soon enough, football will be affected. Agreed that SABR is almost wholly responsible for the new focus on data and metrics in sports. The problem is that football and baseball are fundamentally different games. Baseball really isn't a team sport...it's an individual sport played in a team format. As a result, it is actually quite easy (and good management strategy) to collect as much data as possible on each player. In baseball, the use of SABR-type metrics really do tell the story about the value of a particular player. On the other hand, football is truly a team game. A football player's success is largely dependent on his teammate's performance and the playcalling of coaches. There are too many external variables out of the control of the individual football player for the use of SABR-type analytics to be useful. And as far as I know, there isn't a great STAT to measure the productivity of the 5 most important guys on the offensive side. Similarly many defensive STATS can be misleading (Tackles which sometimes just means you've maybe been on the field more than another player who is on a unit that gets more 3 & outs & Ints which often means your receiver or zone is threatened more possibly because you are the weakest DB on a unit).
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Post by coachklee on Dec 28, 2015 12:37:11 GMT -6
I hear this same argument over and over in these forums, but the problem is, it doesn't hold any water. If the external variable argument were true, it would mean that researchers would not be able to explain much more complicated, open systems, such as the Universe or the human body. Hell, even the mechanics of the human eye or simply how body movement works is astronomically more complicated than the game of football. The reason that there seems to be such reluctance to this idea is that no one is researching football. If researchers turned their attention away from the sciences to football, there are plenty of ways to exclude external variables in clinical trials. It's done every day in the sciences. It's not magic, and it's not overly complicated. It's just something that is required to be accounted for in all calculations. What clinical trials are you talking about? And you are wrong about the game of football. There are WAY more variations in a game of football then in the universe. It isn't even close. Quick example. Do you know what a googol is? It is a 1 followed by 100 zeroes. Or 1 x 10^100 or simply 10^100. It is estimated that there are only 10^81 or so atoms in the entire known universe which is not even close to a googol. But yet, if you try to arrange 70 items, there are more than a googol ways of arranging those things. 70 cards, 70 desks, 70 people, 70 pencils. It doesn't matter. Just one more perspective, there are roughly 8 times as many ways to arrange 60 objects than there are atoms in the universe!! What does this have to do with football and the eye? The eye is already arranged. All you have to do is study it. The game of football has an extreme number of variables and arrangements and someone else is trying to stop what you are trying to do and they have an extreme number of ways to try and stop you. I agree somewhat with the Canadian Guy's question mark here. Much of the game can be explained mathematically...however, I do think we all have to admit that most of us would struggle to properly account all the variables & as mentioned earlier, eventually the value gained from such data might not be worth the time invested.
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Post by 33coach on Dec 28, 2015 12:54:51 GMT -6
i think you guys are taking the use of metrics to the extreme...
Im not trying to quantify the game, find the winning formula. i simply want to know matter of factly how often each player on my team screws up their assignment, and what effect that screw up has:
if i have 1 DB who screws up an average of 1 out of every 3 snaps, i need to get some individual workouts with him.
if all my DB's screw up an average of 1 out of every 2 snaps, i need to reevaluate how the scheme is being taught if all my DB's screw up an average of 2 out of every 3 snaps, i need to reevaluate the scheme
BUT i cant do that if i dont have the REAL data in front of me.
i can guess...or i can know. both take the same amount of effort.
its not rocket surgery...its just basic analysis
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Post by spos21ram on Dec 28, 2015 14:21:01 GMT -6
i think you guys are taking the use of metrics to the extreme... Im not trying to quantify the game, find the winning formula. i simply want to know matter of factly how often each player on my team screws up their assignment, and what effect that screw up has: if i have 1 DB who screws up an average of 1 out of every 3 snaps, i need to get some individual workouts with him. if all my DB's screw up an average of 1 out of every 2 snaps, i need to reevaluate how the scheme is being taught if all my DB's screw up an average of 2 out of every 3 snaps, i need to reevaluate the scheme BUT i cant do that if i dont have the REAL data in front of me. i can guess...or i can know. both take the same amount of effort. its not rocket surgery...its just basic analysis Can't you figure that out by just watching film? I don't really consider tracking how often someone messes up their assignment as metrics, but that's just me. I have two eyes to see if people are screwing up, not sure how numbers change things besides tallying how many assignments the kids miss. Sent from my SAMSUNG-SM-G900A using proboards
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Post by 33coach on Dec 28, 2015 14:26:12 GMT -6
i think you guys are taking the use of metrics to the extreme... Im not trying to quantify the game, find the winning formula. i simply want to know matter of factly how often each player on my team screws up their assignment, and what effect that screw up has: if i have 1 DB who screws up an average of 1 out of every 3 snaps, i need to get some individual workouts with him. if all my DB's screw up an average of 1 out of every 2 snaps, i need to reevaluate how the scheme is being taught if all my DB's screw up an average of 2 out of every 3 snaps, i need to reevaluate the scheme BUT i cant do that if i dont have the REAL data in front of me. i can guess...or i can know. both take the same amount of effort. its not rocket surgery...its just basic analysis Can't you figure that out by just watching film? I don't really consider tracking how often someone messes up their assignment as metrics, but that's just me. I have two eyes to see if people are screwing up, not sure how numbers change things besides tallying how many assignments the kids miss. Sent from my SAMSUNG-SM-G900A using proboards film is a form metric analysis. your taking in data (in visual form) analyzing it, and acting on it, just not recording it the way i tend to. but again for me its the degree. you can say "wow he messes up alot...". or you can say "wow he really doesnt understand cover 3 vs this formation in these 4 situations". which one would you prefer? Performance analysis over time is absolutely a must in this business.
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Post by silkyice on Dec 28, 2015 14:37:32 GMT -6
Can't you figure that out by just watching film? I don't really consider tracking how often someone messes up their assignment as metrics, but that's just me. I have two eyes to see if people are screwing up, not sure how numbers change things besides tallying how many assignments the kids miss. Sent from my SAMSUNG-SM-G900A using proboards film is a form metric analysis. your taking in data (in visual form) analyzing it, and acting on it, just not recording it the way i tend to. but again for me its the degree. you can say "wow he messes up alot...". or you can say "wow he really doesnt understand cover 3 vs this formation in these 4 situations". which one would you prefer? Performance analysis over time is absolutely a must in this business. Not sure of the official definition of data metrics. But in my opinion, the working definition in this thread is taking objective data and evaluating that data. I would call what you are doing just evaluation. Evaluation is absolutely necessary.
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Post by spos21ram on Dec 28, 2015 14:39:19 GMT -6
Can't you figure that out by just watching film? I don't really consider tracking how often someone messes up their assignment as metrics, but that's just me. I have two eyes to see if people are screwing up, not sure how numbers change things besides tallying how many assignments the kids miss. Sent from my SAMSUNG-SM-G900A using proboards film is a form metric analysis. your taking in data (in visual form) analyzing it, and acting on it, just not recording it the way i tend to. but again for me its the degree. you can say "wow he messes up alot...". or you can say "wow he really doesnt understand cover 3 vs this formation in these 4 situations". which one would you prefer? Performance analysis over time is absolutely a must in this business. I think you can come up with both those answers by watching film and jotting notes down. I'm a head baseball coach and use numbers all the time, but I don't think using those metrics in football are worth much. I also think myself and some others do use metrics in football, but we come up with the same outcome using different methods. Sent from my SAMSUNG-SM-G900A using proboards
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Post by spos21ram on Dec 28, 2015 14:42:19 GMT -6
For example what you call a metric analysis, I call film review. I never considered it metrics.
Sent from my SAMSUNG-SM-G900A using proboards
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Post by spos21ram on Dec 28, 2015 15:49:01 GMT -6
I think my view of metrics differs from some of you because I'm a baseball guy. To me metrics is using several different stats, coming up with a formula that makes that final number usable for a purpose. A common example is OPS (On Base % + Slugging).
So in football I consider metrics along the lines of a stat like QB rating, but somehow coming up with a RB raiting, or Oline rating using mitiple stats into a formula to come up with 1 number.
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Post by coachd5085 on Dec 28, 2015 16:04:35 GMT -6
I think my view of metrics differs from some of you because I'm a baseball guy. To me metrics is using several different stats, coming up with a formula that makes that final number usable for a purpose. A common example is OPS (On Base % + Slugging). So in football I consider metrics along the lines of a stat like QB rating, but somehow coming up with a RB raiting, or Oline rating using mitiple stats into a formula to come up with 1 number. And you do what with this number?
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