3 ms·

This sounds really good and NFL teams would definitely want something like this, but even coaches would wary about using mostly data. For example, let's say yo

by socrates1998 13y ago

This sounds really good and NFL teams would definitely want something like this, but even coaches would wary about using mostly data. For example, let's say you are the coach of the Patriots and you have been running the ball very successfully the past few games, even winning games because of your running game. And it's 4th down and 2 yards to go against the Broncos. The data says, run the ball. Especially since you have done it well in the past. However, you forgot to take into account the stud defensive tackle that has just started playing really well for the Broncos. So, you try to run the ball and you lose the game. This is just one example of the inability of data to deal with match-ups and schemes. As both a person who likes data and coached football, I would love the integration of the two, but football has too many variables. If you have all this data, you are actually going to make the wrong decision because the matchup is bad for your team. Matchups and schemes trump data.

JackFr 13y ago
Additionally, it could be that the statistics show a result that is an artifact of coaches decisions. If a particular decision is chosen by the pro coaches extremely rarely, but has a moderately better expected result, it could be that the typical expected result is very poor, but the only times coaches make the decision is when they observe a decisive matchup or a special situation -- making it appear statistically like that decision is the better one. (Like looking at basketball shooting percentages, and wondering why centers don't take all the shots given how high their FG%s are.)
- socrates1998 13y ago
  That is an excellent point. Coaches do what they think will be successful. If they can't run the ball well, then they don't run the ball, skewing the data. Also, tendencies change from week to week. You really need a deep understanding of football to get the right, correct data for that week. This is why data hasn't dominated football, you need to have tons of knowledge before anything else.
  - the_watcher 13y ago
    The best use of data is to give coaches a high level picture of what the likely result of a given play call will be (trusting sample size to even it out). You hire a coach to then adjust for those other things. However, if the data says that 99% of the time a given play call will have a specific result, coaches shouldn't try to be the exception (unless the game situation demands it). There is a happy medium here. The Rays have figured it out pretty well with Joe Maddon, the NFL will get there too. No one thinks a machine should call all the plays (yet). We just think machine learning and big data should be leaned on as tools the same way that film is. Don't forget, Bill Sharman was considered a nut for watching film in the 1980s. Imagine coaching without now.
- centralwinger 13y ago
  I think it's more than "additionally", your point is the major point. It's difficult, but data can in fact control for matchups and schemes.
the_watcher 13y ago
The point of all the data is to give coaches more objective information. To use your example: The data says run the ball. The stud defensive tackle has just started playing really well. Here's the beauty of the way this data can be presented: While there is a way to present it as "expected points," you can also present it as "likelihood of a given result." In this case, the positive outcomes for the offense are a first down (or score, which would also be a first down). If the data says you will pick up a first down 51% of the time and you know the Broncos tackle has recently begun playing well, you adjust down for it, and likely decide not to run (and no analytics guy will fault you for it). If the data says you'll pick up a first down 85% of the time, you need a better reason to justify not going for it (is this new tackle the greatest of all time? Or just an upgrade on what they had?). Data is not best used as a replacement for a coach. It is best used to give a coach the likelihood of a given event occurring, and then let the coaches knowledge of matchups, injuries, and personnel issues adjust that likelihood up or down.

JackFr 13y ago

Additionally, it could be that the statistics show a result that is an artifact of coaches decisions. If a particular decision is chosen by the pro coaches extremely rarely, but has a moderately better expected result, it could be that the typical expected result is very poor, but the only times coaches make the decision is when they observe a decisive matchup or a special situation -- making it appear statistically like that decision is the better one. (Like looking at basketball shooting percentages, and wondering why centers don't take all the shots given how high their FG%s are.)

socrates1998 13y ago
That is an excellent point. Coaches do what they think will be successful. If they can't run the ball well, then they don't run the ball, skewing the data. Also, tendencies change from week to week. You really need a deep understanding of football to get the right, correct data for that week. This is why data hasn't dominated football, you need to have tons of knowledge before anything else.
- the_watcher 13y ago
  The best use of data is to give coaches a high level picture of what the likely result of a given play call will be (trusting sample size to even it out). You hire a coach to then adjust for those other things. However, if the data says that 99% of the time a given play call will have a specific result, coaches shouldn't try to be the exception (unless the game situation demands it). There is a happy medium here. The Rays have figured it out pretty well with Joe Maddon, the NFL will get there too. No one thinks a machine should call all the plays (yet). We just think machine learning and big data should be leaned on as tools the same way that film is. Don't forget, Bill Sharman was considered a nut for watching film in the 1980s. Imagine coaching without now.
centralwinger 13y ago
I think it's more than "additionally", your point is the major point. It's difficult, but data can in fact control for matchups and schemes.

the_watcher 13y ago

The point of all the data is to give coaches more objective information. To use your example: The data says run the ball. The stud defensive tackle has just started playing really well. Here's the beauty of the way this data can be presented: While there is a way to present it as "expected points," you can also present it as "likelihood of a given result." In this case, the positive outcomes for the offense are a first down (or score, which would also be a first down). If the data says you will pick up a first down 51% of the time and you know the Broncos tackle has recently begun playing well, you adjust down for it, and likely decide not to run (and no analytics guy will fault you for it). If the data says you'll pick up a first down 85% of the time, you need a better reason to justify not going for it (is this new tackle the greatest of all time? Or just an upgrade on what they had?). Data is not best used as a replacement for a coach. It is best used to give a coach the likelihood of a given event occurring, and then let the coaches knowledge of matchups, injuries, and personnel issues adjust that likelihood up or down.