Updated analysis of football injuries in the Big Ten

Submitted by m1jjb00 on

As can be seen in the table, Michigan is second to Purdue in missed starts, updated through Saturday’s game.  The third column takes starts lost (SL) divided by games played (GP).  I’ve changed the methodology a bit due to popular demand and explain the changes below. 

 

 

GP

SL

%GM

Non QB

QB

Steele

Adj

Purdue

10

65

6.5

39

0

26

 

Michigan

10

64

6.4

46

0

18

 

Maryland

9

46

5.1

46

0

18

-18

Minnesota

9

43

4.8

27

1

15

 

Northwestern

9

43

4.8

16

0

27

 

OhioState

9

37

4.1

14

9

12

2

Rutgers

9

37

4.1

28

0

9

 

Indiana

9

35

3.9

13

2

20

 

Nebraska

9

33

3.7

24

0

9

 

PennState

9

33

3.7

13

0

20

0

Wisconsin

9

30

3.3

22

4

4

 

Illinois

9

25

2.8

14

4

7

 

MSU

9

23

2.6

13

0

10

 

Iowa

9

20

2.2

19

1

0

 

 

I calculated the total of starts lost (SL) as the sum of four columns. 

  • Non QB counts starts lost as previously.  For every player with at least one start, I sum up across players the difference between the number of games the team played versus the number of games the player appeared in.  This is calculated only for non quarterbacks and is non-edited, so it should be replicable.
  • QB counts the starts lost by quarterbacks.  The second table presents the relevant data.  Lunt, Sudfeld, Rudock, Leidner and Stave had verifiable injuries.  I’m counting Stave’s yips as missed starts for the first four games.  I assume that games not played by the others were coaches’ decisions.  Yes, Morris had an injury, but I don’t think he not playing in the games after Minnesota truly represents lost games by starters.  Ohio State’s 9 lost starts are Braxton Miller.
  • The third column, Steele, is a response to previous comments.  This lists all the games “lost” by players that were thought to be starters preseason but haven’t started a game yet.  (Preseason starters who started a game but also missed some games are already counted in the Non QB column.)  I used Phil Steele’s preseason magazine as I wanted a consistent, easily available source.  The third table presents all the Steele starters who didn’t start a single game so far, how many games they played, and hence the games missed.  All of this is unedited and therefore should be easily replicable.
  • The fourth column represents some sensible adjustments I made to three teams.
    • Steele lists two freshmen as starters on the offensive line for Maryland, but Gray and Prince appear to be headed for redshirts.  So, it doesn’t seem like their missed games should be counted.
    • The NCAA data count Noah Spence as having started a game and played in two.  Hence, the rest of the games he missed are counted in the Non QB column.  But, a poster said that he didn’t play in those games that the NCAA thinks he appeared in.  So I added 2.  If I’m wrong, let me know.
    • I made offsetting adjustments to Penn State.  Thompkins is listed as a starter by Steele, but he’s headed for a redshirt.  So, I subtracted the 9 missed games.  On the other hand Diefenbach wasn’t listed as a starter by Steele because he knew he was out before publication.  But, it seems like those should be counted anyway, so I added back 9.

 

Starting Big Ten Quarterbacks

 

 

GP

GS

GM

Illinois

O'Toole

9

4

0

Illinois

Lunt

5

5

4

Indiana

Sudfeld

7

6

2

Indiana

Diamont

3

3

0

Iowa

Rudock

8

8

1

Iowa

Beathard

6

1

0

Maryland

Brown

9

9

0

Michigan

Gardner

10

9

0

Michigan

Morris

5

1

0

MSU

Cook

9

9

0

Minnesota

Leidner

8

8

1

Minnesota

Streveler

5

1

0

Nebraska

Armstrong

9

9

0

Northwestern

Siemian

9

9

0

OhioState

Barrett

9

9

0

OhioState

Miller

0

0

9

PennState

Hackenberg

9

9

0

Purdue

Appleby

8

5

0

Purdue

Etling

5

5

0

Rutgers

Nova

9

9

0

Wisconsin

McEvoy

9

5

0

Wisconsin

Stave

5

4

4

 

Phil Steele Starters in the Big Ten with No Starts

 

 

GP

GM

Class

Illinois

Day

9

0

So

Illinois

James

2

7

Fr

Illinois

Schmidt

9

0

So

Illinois

Smoot

9

0

So

Indiana

Eckert

5

4

Sr

Indiana

Friend

0

9

So

Indiana

Green

9

0

Jr

Indiana

Taylor

2

7

Sr

Iowa

Powell

9

0

Sr

Maryland

Gray

0

9

Fr

Maryland

Prince

0

9

Fr

Michigan

Bosch

1

9

So

Michigan

Morgan

1

9

Sr

MichiganState

Arnett

3

6

Sr

MichiganState

Knox

5

4

Jr

Minnesota

Bak

0

9

Sr

Minnesota

Bobek

3

6

Jr

Nebraska

Reeves

9

0

Jr

Nebraska

Rose, J

9

0

Jr

Nebraska

Rose, M

0

9

So

Northwestern

Jones, C

0

9

Sr

Northwestern

Mark

0

9

Sr

Northwestern

McEvilly

0

9

Sr

OhioState

Lindsay

0

9

Sr

OhioState

Reeves

8

1

Jr

OhioState

Underwood

7

2

Jr

PennState

Anderson

0

9

So

PennState

Thompkins

0

9

Fr

PennState

Zwinak

7

2

Sr

Purdue

Clements

7

3

Jr

Purdue

Gregory

8

2

So

Purdue

Monteroso

2

8

So

Purdue

Newton

0

10

So

Purdue

Robinson, G

9

1

Fr

Purdue

Yancy

8

2

Fr

Rutgers

Lambert

9

0

So

Rutgers

Peele

0

9

So

Wisconsin

Hudson

8

1

Fr

Wisconsin

Keefer

8

1

Jr

Wisconsin

Maly

8

1

Jr

Wisconsin

Wheelwright

8

1

So

 

Comments

Frieze Memorial

November 11th, 2014 at 12:07 AM ^

If only there was someone who could suggest a better way, for the welfare of our players, to avoid these injuries.  A new strength and conditioning regimen, maybe?  Trigger release something?

LBSS

November 11th, 2014 at 10:47 AM ^

Thanks for this. Can you do the analysis for past years?  It always seemed to me like M's injury rate was higher under Barwis than other teams', as it does now for Wellman. That might just be proximity bias because I obviously pay more attention to Michigan than to other teams, but this is starting to confirm that vague suspicion.

For further reading: "Prediction of Sports Injuries by Mathematical Models" (free full text):

"Sports injuries are most commonly caused by poor training methods; structural abnormalities; weakness in muscles, tendons, ligaments; and unsafe exercising environments. ... The most common cause of sports injuries is improper training whether from a technical or tactical point of view or simply training that is poorly planned and executed (Shaffer, 2006). The athlete exposes him or herself to possible sports injuries without adequate preparation for: exposure to potential danger, the playing position or type of activity, the duration of the competition or league, competition level, time dedicated to training and to rest. These variables can be quantified and turned into predictive factors (Ferrara, 2007)." 

That statement doesn't prove anything, of course. Just food for thought.

Tater

November 11th, 2014 at 5:11 PM ^

OK, BIGBLUEWORLD: everyone "knows" how you have been "wronged" now.  So, why not just give it a rest?  Better yet, when your material is deleted, why not ask the mods for feedback behind the scenes and ask them how you could improve your material to better fit the quality standards of the board?

My take: Brian works really hard to keep this board a couple of levels above RCMB and others of their ilk.  Whether or not you agree with everything that goes into maintaining those standards, they are part of what makes MGoBlog the best of its genre.  

Pretend you are an athlete.  If you don't make the cut, come back with more "game" the next time.

vanbluegens

November 11th, 2014 at 3:58 PM ^

So when Caldwell came here, many of the players commented how he allowed them to go easier during practice to avoid injury.  Hoke takes pride in practicing like we play.  Any stats on how many of these injuries happened during practice versus on the field?

 

TESOE

November 12th, 2014 at 1:09 AM ^

I appreciate the effort but ... let's be real.  Playing a game of football is roughly equivalent to driving a car into a brick wall at 30 miles an hour.  For the most part you are going to be OK but people get hurt.  

Bosch's missed games have nothing to do with S&C but account for 14% of Michigan's reported injuries here by games missed.  Steele's projections have nothing to do with reality.  We are penalized for starting a freshman OT.  

There is no accounting for the types of injury here either.  You don't get turf toe or a high ankle sprain from lifting weights.  The ability of S&C to ward off injury is not documented nor documentable without specifics.  What exactly does Michigan do differently than other schools?  Difference doesn't imply significance.  There is no accounting for good years that this team has had wrt injury with the same S&C.

What is the % signify in %GM?  There are 22 starts in every game (more if you count special teams.)  Michigan had 6.5% games missed by dividing starts lost by games played??    

If you break this down by individual injuries you will get a varied batch of particulars that can't be so nicely tossed in the coaching bucket.  Knowing what I do about Michigan makes me think the rest of the B1G is just as specious.

Concussion gate, stretch gate, Barwis vs. Wellman methods... it doesn't add up to a conspiracy.  Accountability starts and stops with the head coach.  

There's more to say here... it's just not worth it.  This analysis is wrong-headed.

Yeoman

November 11th, 2014 at 5:24 PM ^

Back of the envelope calculation: we seem to be looking at an average of rougly six or so significant injuries per team (I'm guessing that the injury length of the injuries driving the totals have been around five games per, now that we're nine games in). The s.d. would be roughly the square root of that, so one sigma is maybe 40% of the total, which would put Michigan and Purdue about two sigma above average.

Is that convincing? You'd expect somebody to end up at 55+ here even if everybody's injury risk was the same and there was no causal relationship behind any of this at all.

That Michigan and Purdue are in an unusual zone is interesting if you're trying to evaluate their season, but if you want to infer from this that the high injury rate is due to some cause, be it the staff, or S&C, or the head coach, you probably need more. We've got years of information on Wellman, on Hoke, for that matter most of this staff has been together for quite a while now other than Nussmeier. Is this season a one-off or is there a career-long pattern here? Same goes for any other hypothesis anyone wants to try.

steve sharik

November 11th, 2014 at 5:53 PM ^

...the timing of the injuries.

For example, when you take Braxton Miller out of the data, Ohio jumps down the list considerably.  The reason I bring this up is that my qualitative (i.e., non-data) opinion is that as teams lose, guys don't put up with injuries they way they do when they're winning.

I've coached long enough to know that when there is something to play for, guys do everything they can to get back on the field; when there is not much to play for, guys find reasons to avoid playing, especially practicing.

That said, I just quickly did the following excel exercise, so it looks like my theory sucks:

Team GP SL Win %
Purdue 10 65 0.3
Michigan 10 64 0.5
Maryland 9 46 0.666667
Minnesota 9 43 0.777778
Northwestern 9 43 0.333333
Rutgers 9 37 0.555556
Indiana 9 35 0.333333
Nebraska 9 33 0.888889
PennState 9 33 0.555556
Wisconsin 9 30 0.777778
OhioState 9 28 0.888889
Illinois 9 25 0.444444
MSU 9 23 0.777778
Iowa 9 20 0.666667

 

  SL Win %
SL 1  
Win % -0.46942

1

I calculated the correlation using excel, which is r = -0.4149.  The closer the absolute value of r to 1, the more correlated the data.  The fact that this is a negative value shows that, in general, the fewer the injuries, the greater the winning percentage.

Of course, even if there was high statistical correlation, there is a logical issue: does losing lead to increased sensitivity to injuries, or does the rash of injuries lead to more losing?  Or do they go hand-in-hand?

.

m1jjb00

November 11th, 2014 at 8:11 PM ^

Keep in mind the limitations of this excercise.  

It includes suspensions and other coaches' decisions.

You only count if you have been a starter this season or preseason.  So, injuries to important guys who only rotate in aren't going to get counted.

It only counts guys who missed entire games.

It's only this season.

Hence, making broader points/analysis beyond, hey Michigan and Purdue seem to have to overcome a lot more than Iowa and Michigan State are not proven or disproven with this.

BIGBLUEWORLD

November 13th, 2014 at 11:47 PM ^

Could you possibly analyze the number of ACL injuries per team? While trauma and impact injuries are more random, the medical evidence does indicate a direct correlation between ACL injuries and the training methods utilized. When you remove the random nature of impact injuries, the "noise", we'll have a more clear picture of the costly mistakes being made in our football S&C program. 

Some training methods improve the resilience of connective tissue (tendons, ligaments, fascia, etc). Some training methods can produce hypertrophy, yet degrade agility, mobility, flexibility. Therefore, the incidence of ACL injuries would have a more direct correlation with regards to training methods, than occurrences such as broken bones or concussions.

Thanks. Peace.