BurntSushi
commented
11 years ago Here's the problem. The CSV dump of nflgame isn't supposed to be used like this. The entire API of nflgame is designed with the assumption that you'll be doing your analysis in Python. The CSV dump is there as an exit point if you need it, but it's not meant to be as flexible as you're wishing here.
I'll respond to the rest of your questions, but my most significant recommendation is to invest some more time into learning Python if you want to use nflgame effectively. If you know a little bit of Python and learn how to maneuver around nflgame's API, then dumping any kind of data to a CSV file is simple.
now I see inconsistent results, And I’m not sure why. ??
Because we're dealing with imperfect data, and it's impossible to reconcile correctly. In any given game, the variations are usually small or non-existent. But when you're summing everything up over a season, they become noticeable. As you've seen.
Where does the inconsistency come from? The source. NFL's GameCenter JSON actually contains two different sets of statistics: game level statistics and play-by-play statistics. Game level statistics are limited, but are sometimes more correct than play-by-play. Play-by-play statistics are exhaustive, but are sometimes more correct than game-level statistics. (Whacky, eh?)
When you use allfields=True, then every field from game and play statistics is combined. There is overlap between these two categories, and where there is overlap, there is inconsistency.
It is possible that there is a sane way to handle this, but I haven't thought of it yet. As a compromise, combine_max_stats was added, which tries to combine these two sources intelligently. But it isn't perfect.
Additionally, most weeks yield 135 columns of data when all-fields is true, but other weeks only 134 columns.
Could you please post the commands you're running that reproduce this?
This works but only yields scoring drives per game. Need all drives by all teams, including starting field position per given week. Also in the form of a .csv dump
I've run the commands you've posted, and I get all drives in the game. Not just scoring drives:
>>> import nflgame
>>> g = nflgame.one(2011, 17, "NE", "BUF")
>>> print g.drives
[BUF (Start: Q1 15:00, End: Q1 11:18) Touchdown, NE (Start: Q1 11:18, End: Q1 09:52) Punt, BUF (Start: Q1
09:52, End: Q1 05:19) Touchdown, NE (Start: Q1 05:19, End: Q1 03:55) Punt, BUF (Start: Q1 03:55, End: Q1 0
0:48) Touchdown, NE (Start: Q1 00:48, End: Q2 11:58) Touchdown, BUF (Start: Q2 11:58, End: Q2 08:59) Punt,
NE (Start: Q2 08:59, End: Q2 05:42) Touchdown, BUF (Start: Q2 05:42, End: Q2 02:25) Downs, NE (Start: Q2
02:25, End: Q2 00:51) Interception, BUF (Start: Q2 00:51, End: Q2 00:00) Missed FG, NE (Start: Q3 15:00, E
nd: Q3 12:19) Field Goal, BUF (Start: Q3 12:19, End: Q3 08:38) Punt, NE (Start: Q3 08:38, End: Q3 05:13) F
ield Goal, BUF (Start: Q3 05:13, End: Q3 03:54) Interception, NE (Start: Q3 03:54, End: Q3 01:32) Touchdow
n, BUF (Start: Q3 01:32, End: Q4 12:04) Interception, NE (Start: Q4 12:04, End: Q4 11:16) Touchdown, BUF (
Start: Q4 11:16, End: Q4 10:23) Punt, NE (Start: Q4 10:23, End: Q4 03:02) Touchdown, BUF (Start: Q4 03:02,
End: Q4 02:55) Interception, BUF (Start: Q4 02:55, End: Q4 01:30) Interception, NE (Start: Q4 01:30, End:
Q4 00:00) End of Game]nflgame doesn't dump drive data to a CSV for you. You'll have to do that yourself using Python's csv module.
teamfball
ochawkeye
""Issues should be open for just about anything—including questions about how to use nflgame, or even problems with NFL.com data. There should be a pretty low threshold to opening one.""
Okay then, here goes. I’m clearly too old and not smart enough to understand Python or this little slice of heaven you call, nflgame. I haven’t been able to a damn thing on my own, if the code hasn’t been published here or in the tutorial, all I get are errors.
I'm using version ‘1.1.8’ of nflgame. My main focus is player stats, post game at rest data. I’ve used this code successfully, mostly because it’s in the tutorial.
nflgame.combine_max_stats(nflgame.games(2012)).csv('PD2012.csv',allfields=True)
The new
allfieldsparameter, ‘thank you Andrew’ is very helpful, however, now I see inconsistent results, And I’m not sure why. ?? total players receiving_rec receiving_tar receiving_yac_yds receiving_yds ver. 1.1.7 1812 10838 17550 53939 125983 ver. 1.1.8 all fields=T 1812 10779 17429 53656 125259 ver. 1.1.8 1812 10838 17550 53939 125983 Additionally, most weeks yield 135 columns of data when all-fields is true, but other weeks only 134 columns. The “def_misc_yds” column appears to the culprit. This column misalignment makes summing values across multiple excel sheets a challenge. So how could I query just the data columns I want.?This is the only query I’ve been able to work on my own.
Additional things I’m tying without success are:
· Drive charts
· Schedule o All teams for entire season, in the form of a .csv dump · Team rosters o All teams for any given week, in the form of a .csv dump · Injury report, player status o All teams for any given week, in the form of a .csv dump
Any help would be greatly appreciated. And thank you in advance.