Spotlight - Cornerback (CB) Tackle (TAK) attribute

    This is going to be the first in a series of posts that will focus on the tackle (TAK) attribute in Madden 12.  My plan is to do every defensive position and then maybe have one final tackle (TAK) blog that wraps them all together.  Cornerback (CB) is the first position I decided to look at.  I selected 29 CBs in Madden, from some of the best in TAK attribute to some of the worst.  I intentionally selected big name CBs and have included some rookies as well.

    I started out by looking at their solo tackle stats and missed tackle stats up to week 16 of 2011 through 2009.  I used stats from ProFootballFocus.com to get missed tackles (MT) and solo tackles (Solo).  PFF does not include sacks in their solo tackles stat, so I added any sacks a player had to their solo tackles for my tables.  I decided to use the MT information and solo tackle information to come up with a MT%.  A percentage is a better figure to use than just the total MTs.  To come up with this percentage, I divided MTs by (Solo + MTs).  It should be noted, that I did not include tackle assists for this calculation.  I have emailed PFF to see if they count MTs on attempted assists or just solo tackle attempts.  I have yet to receive a reply.  After looking at all the stats for CBs, most of them have very few assists.  Even without the tackle assists, I believe this MT% gives us a good idea of how well each player performs the act of tackling.   I will admit that it's not an exact science.  That said,  I believe using something like MT% is a more accurate way to rate the TAK attribute for Madden 12 players.  Of course, we have no idea what the current procedure is for determining the TAK rating in Madden 12.

    The following is two of my tables, one is for 2011 and one is a 3 year total (2009 -  Week 16, 2011):

TAK = Madden 12 tackle attribute as of Week 16 roster update

Solo = ProFootballFocus solo tackles + sacks (PFF does not record a solo tackle for sacks)

MT = Missed tackles per ProFootballFocus

MT% = MTs/(SoloTak + MTs)

* = Rookie or 1st year player

2011 Season		2011	2011	2011
CB's	TAK	Solo	MT	MT%
Winfield	86	37	2	5%
Haden	58	55	3	5%
Browner*	65	49	3	6%
Newman	42	45	3	6%
Sherman*	53	43	3	7%
C.Harris*	62	56	4	7%
A. Williams*	70	26	2	7%
A.Jefferson*	63	64	5	7%
Taylor	66	34	3	8%
Revis	64	44	4	8%
Gilchrist*	70	21	2	9%
Tillman	70	88	9	9%
Rogers	65	37	4	10%
Webb	62	59	7	11%
Jammer	63	42	5	11%
Routt	55	45	6	12%
Clements	72	52	7	12%
Grimes	53	42	6	13%
Joseph	52	44	7	14%
P. Peterson*	66	39	7	15%
Cromartie	54	36	7	16%
Woodson	66	69	15	18%
Bailey	66	34	8	19%
Talib	52	34	8	19%
Greer	56	65	17	21%
Gamble	55	36	10	22%
D. Robinson	64	42	12	22%
Asomugha	57	35	11	24%
Barber	66	67	22	25%
Average	61.83	46.21	6.97	13%
Totals		1340	202	13%

3 year MT%		09'-11'	09'-11'	09'-11'
CB's	TAK	Solo	MT	MT%
Haden	58	107	5	4%	10'-11'
Browner*	65	49	3	6%
Winfield	86	165	11	6%
Sherman*	53	43	3	7%
C.Harris*	62	56	4	7%
Newman	42	175	13	7%
A. Williams*	70	26	2	7%
A.Jefferson*	63	64	5	7%
Tillman	70	229	19	8%
Routt	55	118	11	9%
Gilchrist*	70	21	2	9%
Taylor	66	141	14	9%
Bailey	66	141	14	9%
Revis	64	118	12	9%
Webb	62	137	14	9%
Clements	72	154	17	10%
Joseph	52	150	18	11%
Rogers	65	120	15	11%
Talib	52	127	17	12%
Jammer	63	131	20	13%
Woodson	66	215	35	14%
Cromartie	54	109	18	14%
Grimes	53	172	29	14%
P. Peterson*	66	39	7	15%
D. Robinson	64	148	27	15%
Greer	56	164	31	16%
Barber	66	207	50	19%
Gamble	55	70	18	20%
Asomugha	57	84	24	22%
Total		3480	458	12%
Average	61.8			12%

Final thoughts and observations:

1.  The cumulative 3 year MT% (12%) for these 29 CBs and the 2011 MT% (13%) are very similar.  As a group, these 29 CBs are pretty consistent.

2.  For many of these CB's their individual 2011 MT% is very similar to their 3 year MT%.  Does 3 years of data give us a good indication of how well a player performs the act of tackling?  I believe it does.

3.  Should Newman, Webb, Revis, Routt, and Haden really be rated lower in the tackle (TAK) attribute than some like Barber or even Charles Woodson (14% MTs in the last 3 years).  I know, Woodson is a shocker.  Since he is on my IDP fantasy team, I have had the "pleasure" of watching Woodson whiff  on many tackles this season.

4.  The really interesting part of this table, is that it actually shows some accurate ratings as well.  Asomugha,   Gamble, Grimes, and Greer are correctly rated below average.  You could argue that Asomugha and Gamble could actually be lower.  Than you have the Newman/Barber issue, which tops the list of inaccurate ratings.

Thanks for following my blogs.  I hope you enjoy this one.  Remember, this is the first in a series of tackle (TAK) attribute blogs.  I plan to do either safeties or ILB next.  Happy New Year.  Please, "DON'T DRINK AND DRIVE" tonight (or any night for that matter) and don't let anyone else drink and drive.

Attribute spotlight - Injury (INJ) attribute in Madden 12

    Some might be surprised that I have decided to analyze the injury (INJ) attribute in Madden 12.  It wasn't my intention to do injury.  The idea came to me after watching the MaddenBible Game of the Week (GOTW)  http://www.ustream.tv/recorded/19438338 and seeing Aaron Rodgers get knocked out of the game early.  This forced ZFarls to play most of the game with backup Matt Flynn.  I can think of several times that my wide receiver or line backer has been knocked out of the game.  On many occasions it's the same players over and over again.  I don't mind having a player knocked out of a game, especially if he has a history of injuries.  That said, I don't like having players consistently knocked out of a game who have very little to no injury history.  I have no idea how many times Rodgers gets knocked out in Madden 12, but the GOTW got me thinking so I decided to take a look.  

    When I first started to look at the INJ attribute, I looked at all players regardless of position.  Looking at all positions at once, shows several inconsistencies.  I thought, maybe looking at the INJ attribute by position would paint a better picture.  By looking at the INJ attribute on a position level, it did show some consistencies.  Overall, I would still consider the INJ attribute in Madden 12 to be inconsistent.  I had a very long list to start with, I had to cut it down to prevent information overload.  It's still a lot of information, but I believe it's needed to show the consistency within the inconsistency.  

    I decides to look at the last three years for the players included in the spreadsheet.  I know some of these players have had injuries prior to 2009, but I believe three years is enough time to show a trend on the players behalf.  I fully understand if some folks believe the entire career should be looked at when rating a players injury attribute.  That is a valid argument.  If looking at the entire career is the way EA is rating the injury attribute, the table still show inconsistency with the younger players and some older players.  I believe a player should have the opportunity to shed the "injury prone" label, or can receive the "injury prone" label.   I would love to hear what you think in the comments section.  

INJ = Current Madden 12 injury attribute rating as of Week 16 update.
GMSD = Games missed

QB's	Injury	2011	2010	2009
Name	INJ	GMSD	GMSD	GMSD
E. Manning	98	0	0	0	118 Consecutive gms
Cutler	95	5	1	0
P. Manning	87	15	0	0
Romo	87	0	10	0
A Rodgers	84	0	1	0
Stafford	65	0	13	6
RB's	Injury	2011	2010	2009
Name	INJ	GMSD	GMSD	GMSD
Leshoure	94	15	College	College
Hightower	94	10	0	0
Fred Jackson	92	5	0	0
Moreno	88	8	3	0
APeterson	85	3	2	0
McFadden (Oak)	74	8	2	3
Reggie Bush	73	0	8	2
Tate	72	1	16	College
McCluster	65	0	5	College
Ryan Matthews	65	1	4	College
TE's	Injury	2011	2010	2009
Name	INJ	GMSD	GMSD	GMSD
Finley	85	0	11	3
R. Gronkowski	84	0	0	College	Missed senior yr
J. Gresham (CIN)	60	2	1	College	Missed senior yr
WR's	Injury	2011	2010	2009
Name	INJ	GMSD	GMSD	GMSD
R. Wayne	95	0	0	0	144 Consecutive gms
Hankerson	94	12	College	College
Andre Johnson	86	9	3	0
Julio Jones	85	3	College	College
Harvin	78	0	2	1
Olineman	Injury	2011	2010	2009
Name	INJ	GMSD	GMSD	GMSD
Gross	97	1	0	7
Michael Roos	96	0	0	0	111 Consecutive gms
VasQuez (SD)	95	2	6	2
Light	94	1	0	5
Jake Scott	93	0	0	0	119 Consecutive gms
Backus	92	0	0	0	175 Consecutive gms
B. Moore	90	0	0	0	120 Consecutive gms
Weigmann	72	0	0	0	174 Consecutive gms
Sitton (GB)	47	2	0	0	Missed 5 in 08'
Dlineman	Injury	2011	2010	2009
Name	INJ	GMSD	GMSD	GMSD
Kyle Williams	96	10	0	2
Justin Smith	96	0	0	0	170 Consecutive gms
LBs	Injury	2011	2010	2009
Name	INJ	GMSD	GMSD	GMSD
Flecther	99	0	0	0	178 Consecutive gms
Harrison (PIT)	97	5	0	0	1 to suspension in 11'
Ryans	97	0	10	0
Beason	95	14	0	0
Woodley	93	5	0	0
Lewis	85	4	0	0	0 games fr 08' - 10'.
DB's	Injury	2011	2010	2009
Name	INJ	GMSD	GMSD	GMSD
Sheldon Brown	99	0	0	0	Never missed a gm
Major Wright	95	4	5	College
R. Barber	95	0	0	0	198 Consecutive gms
Atogwe	94	3	0	4
Chung	93	8	2	0
K Rhodes	93	8	0	0
B. Harris (HOU)	92	9	College	College
Bullitt	91	13	12	2
Berry	88	14	0	College
Collins (GB)	87	13	0	0
Reed	85	1	6	4

Statistics collected from NFL.com
Consecutive games information collected from NFL.com and   http://en.wikipedia.org/wiki/Most_consecutive_starts_(NFL)#cite_note-Jake_Scott_-_Profile-38 

    You will notice that I included some notes on a few players.   I did verify the consecutive game streaks at NFL.com.  I also did my best to confirm that players missed these games due to injury.  If anyone does find an error please let me know and I will correct it ASAP.  I do not want to put out incorrect information.

    For the most part, EA has giving credit to top 10 players with the longest active consecutive streaks.  I have noted the length of those streaks next to the players name.  One player, Casey Weigmann of the Kansas City Chief has slipped through the cracks.  He has a 72 INJ attribute while having started 174 consecutive games.

    Only one player (London Fletcher) who is in the top 10 of active streaks has received a 99 INJ from EA.  I would suggest that a 99 INJ should be reserved and giving to these exact type of players.  All 10 of these players have earned a 99 INJ attribute at this point.  What else would a player have to do to receive a 99?

    Looking over these attributes and games missed, you should see inconsistencies within positions and as a whole.

Final thoughts:

1.  How in the world does Justin Smith and Kyle Williams have the same INJ when Smith has proven to be an Ironman and Williams has missed 12 games over the last three years?

2.  Should Jay Cutler and Tony Romo really have a better INJ than Aaron Rodgers.  Rodgers has only missed one game since becoming a starter in 2008.

3.  When does Matthew Stafford get out of the INJ doghouse (65 INJ).  If he starts on Sunday, he will have played every game this season.  Should he have to prove it one more season before getting a bump?

4.  If you want inconsistency, just look at the RBs.

5.  Should Gronkowski and Finley be that closely rated in INJ?  Is Gresham really that bad?

6.  Gross, Vaquez, and Light, should not have a higher INJ attribute than Backus, Weigmann, Moore, and Scott.

7.  Linebackers are the second most inconsistent when it comes to the INJ attribute.

8.  Defensive backs don't seem to take as much of a hit in INJ than other positions.  BTW - Why in the (blank) does Melvin Bullitt have a 91 INJ?

    I know some people won't think the INJ is a very important attribute, I believe it's very important especially for the online gameplay experience.  A gamer can change an attribute when playing offline to correct these inconsistencies, but they can't be corrected for online ranked play.  Losing a player during a game is one thing, but the frequency of losing that player should be based on reality.  Have a great New Year and I will keep reminding all of you "DON'T DRINK AND DRIVE."

Inconsistent - Catch (CAT) attribute in Madden 12

    Last week I really started looking at the drop statistic for wide receivers (WR) in the NFL.  I was actually shocked at who I found leading the league in drops.  Names like Brandon Marshall and Roddy White are near the top of every list for drops this year.  They are among the most targeted WRs in the NFL, so it's to be expected.  Isn't it?  I think the answer is no. 

    One statistic I found along way, was courtesy of www.ProFootballFocus.com.  They have a stat called "drop %".  This percentage is the number of drops a player has, divided by the number of "catchable" targets.  Granted, this stat is based on their subjective opinion when it comes to what a catchable ball is.  The percentage is still very useful, because they apply the same rules for determining what is a catchable ball to all players equally.  By applying the same rules to each player, they reduce (if not eliminate) bias and create a more objective statistic. 

    I can't go over every little part of their grading policy on this blog, but I encourage you to go to their website and read the grading (under the about tab).  You can read this information for free.

    It's become clear to me over the last couple of weeks, there is basically two sides of the Madden ratings debate.  There is the statistical side (objective) and the perception side (subjective).  Obviously, I lean toward the objective side.  I have realized that some attributes in Madden are easy to look at objectively (CAR, CAT, THA) and others are more of a subjective attribute (SPC, CIT, AWR).  For Madden ratings to be consistent there needs to be a balance between objectivity and subjectivity.  There also needs to be a clearly defined ratings system.  The reason ProFootballFocus can maintain a high level of credibility while admitting that there is some subjectively in their stats, is because they "define a clear set of rules" that apply to all players and all teams.  (ProFootballFocus.com)

    The #1 thing EA should address when it comes to Madden player ratings, should be implementing a "clear set of rules" and procedures for rating players and each individual attribute.  Rules and procedures give credibility to the entire ratings staff.  This would also make their jobs easier when rating players, plus it will result in more consistency.  EA could than put the ratings policy and procedures on the web for all to see.  While some people will always disagree with the ratings, others will be very happy to see the procedures in black and white.  Full transparency would work wonders, similar to what PFF has given it's audience.

    Now, let's look at some catch (CAT) attributes.  The table includes WRs with the top CAT rating in Madden and other well known/lesser known WRs.  The inconsistencies are pretty obvious.  I included the spectacular catch (SPC) and catch in traffic attribute (CIT) as well, althought they are  subjective attributes.  You will also see the current number of catches the players have in 2011.  Stats were collective from STATS LLC and ProFootball Focus.  The attributes are from the most current roster update (week 16).

Drop% = ProFootballFocus drop % based on "catchable targets".
Red = worst
Blue = best
<><><><> <><><><> <><><><> <><><><> <><><><>

WR's Catch (CAT) attribute analysis
Current ratings				2011	Drop %	Drop %	Drop %
Name	CAT	CIT	SPC	Catches	2011	2010	2009
Welker	98	99	84	116	8.80	13.13	4.65
Fitzgerald	98	97	100	71	4.11	3.23	3.06
Bess	95	75	67	45	10.00	7.06	8.54
Smith (CAR)	95	88	86	73	7.69	18.18	4.41
Marshall	94	96	86	77	14.44	13.13	7.41
R. White	94	96	90	96	12.50	7.26	6.84
Lloyd	94	80	99	64	11.76	4.94	20.00
Wayne	94	94	90	67	2.90	7.50	2.91
Gaffney	90	82	79	64	3.03	7.14	5.26
Dez Bryant	88	88	97	57	1.72	6.25		2009 College
Harvin	85	80	86	77	2.86	6.58	6.45
D. Nelson	81	83	78	59	6.35	6.06		2009 College
Garcon	79	72	86	68	6.85	16.25	7.84

 © 2010 ProFootballFocus.com. All rights reserved.
 © 2011 STATS LLC. All Rights Reserved

    After looking at this small sample, you may be thinking that there is absolutely no consistency with the catch (CAT) rating.  I would agree.  I included actual catches on the season to see if there was some correlation between actually NFL catches and CAT rating.  There is a possible connection, but it is not consistent.  It is clear, that drops or in this case the "Drop %"  are a non factor in the CAT rating.  I may be wrong, but I see the catch attribute as being the players ability to catch a pass.  If so, "Drop %" should play a role in rating that attribute.

    Remember at the beginning I mention that CIT and SPC tend to be more of a subjective attribute.  This means that even though Brandon Marshall should have a lower CAT rating, he may still be one of the better WRs when it comes to CIT and SPC.  This would still make him a very good player in Madden, but to lower his CAT would be a more realistic representation of his play on the field.

   Marshall has a clear trend over the last three years.  He is actually dropping a higher percentage of his passes as each year goes by.  Harvin on the other hand is getting better throughout his career and has been better than Marshall every year from 2009 to 2011.

Final thoughts:

1.  Does perception trump everything when rating players like Marshall and White?

2.  Why has Garcon payed such a heavy price for his terrible 2010, when Steve Smith of Carolina hasn't?  Garcon has actually been better than Smith the last two seasons.

3.  Should the catch (CAT) rating be based on the number of catches a player has during a season (career) or should it be based on their actual ability to catch a "catchable" pass?

4.  Why in the world does Devon Bess have a 95 CAT when Harvin is only an 85 and Nelson is only an 81.

5.  Does David Nelson get missed because he plays in Buffalo?  He has been very good and consistent his first two seasons when it comes to catching the ball.  In no way should he have an 81 CAT.

6.  Take some time and look at the CAT ratings in Madden and look at stats from places like ProFootballFocus or STATS Inc.  It will show that this inconsistency in catch (CAT) attribute is present not only in wide receivers (WR), but among tight ends (TE) and running backs (RB) as well. 

    Pierre Thomas went two seasons in 2009 and 2010 without a catchable drop and is doing great this year with a 4.08% drop rate and is only a 74 CAT.  Gore has been horrible this year and has declined over the last two seasons, yet he is still a 76 CAT.

				Catches	Drop %	Drop %	Drop %
TE's	CAT	CIT	SPC	2011	2011	2010	2009
Witten	97	93	79	69	5.48	2.17	5.81
Gates	93	94	93	59	1.67	5.77	7.14
J. Graham	93	89	92	88	6.38	8.82	Rookie
Clark	91	76	93	29	20.00	7.50	7.14
Finley	87	84	93	48	18.64	0.00	6.78	Limited in 10
Fasano	86	84	67	28	0.00	5.00	8.82
V. Davis	85	74	80	59	7.94	10.00	14.29
Pitta	85	85	84	34	0.00	0.00	Rookie	Limited in 10
Lewis	84	87	71	36	12.50	8.33	11.76
Chandler	82	82	74	35	0.00	0.00	Rookie
K. Davis	75	80	75	18	10.00	0.00	10.00	Limited 09/10
				Catches	Drop %	Drop %	Drop %
RB's	CAT	CIT	SPC	2011	2011	2010	2009
Forte	84	75	70	52	1.89	1.92	5.00
R. Bush	83	84	87	43	4.44	5.56	0.00
Sproles	83	65	55	81	10.11	4.84	4.26
F. Jackson	79	65	40	39	0.00	22.50	6.12
S. Jackson	79	70	59	41	2.38	9.80	5.56
Tolbert	78	60	45	53	10.17	7.69	15.00
Gore	76	48	53	17	29.17	9.80	1.92
M. Bush	74	40	25	35	2.78	5.26	5.56
P. Thomas	74	67	45	47	4.08	0.00	0.00
Gerhart	64	55	33	22	0.00	12.50	Rookie
D. Ware	55	50	45	26	3.70	12.50	0.00	Limited in 11
Lynch	54	35	40	26	10.34	8.70	12.50

© 2010 ProFootballFocus.com. All rights reserved.
© 2011 STATS LLC. All Rights Reserved


Please leave feedback.  Have a great New Year and DON'T DRINK AND DRIVE.