Gillette one of the top injurious stadiums?

[Richard Camembert]

Don't see any comment on whether the differences are significant so even though this paper might have face validity it's impossible to see if the differences are meaningful.

 

[maineman209]

Don't see any comment on whether the differences are significant so even though this paper might have face validity it's impossible to see if the differences are meaningful.

It doesn't appear to me that this analysis is making any cause-and-effect claims, but merely demonstrating that there appears to be a sufficiently significant correlation to consider turf type as a contributing factor in lower leg injuries.

 

[Richard Camembert]

It doesn't appear to me that this analysis is making any cause-and-effect claims, but merely demonstrating that there appears to be a sufficiently significant correlation to consider turf type as a contributing factor in lower leg injuries.

With respect, there is no description of any such correlation in the article. Let alone a discussion of whether the correlation is significant. (A correlation is the result of a mathematical operation, and there's no math here.). So they aren't demonstrating anything, just saying that it's looks like there could be a difference. This is one reason why this article is weak.

 

[archstanton543]

But....the Pats lost more players to injury last week on the road in a completely different stadium.

 

[maineman209]

With respect, there is no description of any such correlation in the article. Let alone a discussion of whether the correlation is significant. (A correlation is the result of a mathematical operation, and there's no math here.). So they aren't demonstrating anything, just saying that it's looks like there could be a difference. This is one reason why this article is weak.

Well, it's far from being a scientific study that's being submitted for peer review, but the published results of their analysis appear to show a correlation whether the authors explicitly describe or discuss it as such.

Also, while it's true that the authors didn't publish any mathematical operations they may have performed, the fact that they're published charts are quantified seems to suggest that they must have performed some mathematical operations on the data at some point.

 

[Bobsyouruncle]

The difference in Jets and Giants rates in the same stadium suggests that other factors besides the turf probably play larger roles.

I think the biggest issue is that the injuries may not be turf related. If someone gets a concussion due to a helmet to helmet hit it doesn't say much about the turf. If there was a way to sift out injuries like that it might be more revealing.

 

[Gumby]

The difference in Jets and Giants rates in the same stadium suggests that other factors besides the turf probably play larger roles.

I think the biggest issue is that the injuries may not be turf related. If someone gets a concussion due to a helmet to helmet hit it doesn't say much about the turf. If there was a way to sift out injuries like that it might be more revealing.

One authors didn't mention: quality of opponents??? NEP with a consistent first place schedule.

Turn on your sarcasm meter for 2d:
AFCE opponents consistently faking injuries to slow down the NEP no-huddle.

 

[Richard Camembert]

Well, it's far from being a scientific study that's being submitted for peer review, but the published results of their analysis appear to show a correlation whether the authors explicitly describe or discuss it as such.

Also, while it's true that the authors didn't publish any mathematical operations they may have performed, the fact that they're published charts are quantified seems to suggest that they must have performed some mathematical operations on the data at some point.

Sort of. Looks like they just averaged the number of injuries by stadium and rank ordered them. You would see language about the Field Turf group having significantly more injuries, with a p value reflecting how confident they are in their assertion. In fact, by the eyeball test, since you can see that a lot of the ranges overlap and some of the highest injury rates are from grass fields, I would say that there is likely NO significant difference. This might reflect that the fact that football itself is very dangerous is more important by far in the injury mechanism than the specific field composition.

 

[Richard Camembert]

The difference in Jets and Giants rates in the same stadium suggests that other factors besides the turf probably play larger roles.

I think the biggest issue is that the injuries may not be turf related. If someone gets a concussion due to a helmet to helmet hit it doesn't say much about the turf. If there was a way to sift out injuries like that it might be more revealing.

Probably small sample size. A couple guys got hurt on one team, not the other, and it's not important enough to draw any conclusion.

 

[Mack Herron]

About to get worse?

 

[archstanton543]

About to get worse?

Eh, they're just trying to throw their weight around so they have more bargaining power when the CBA is up. They've gotten crushed in court so this is their only recourse.

 

[jbb9s]

since one would expect that the home team would be more familiar with the quirks of the stadium (where the bad seams in the turf are and the like) that could skew things even more.

What? You get it mixed up with the parquet at the Boston garden? The field is completely uniform - not saying it isn't uniformaly bad just saying uniform one way or another.

 

[XLIX]

If they were trying to use analytics to prove something statistically, they really haven't done so. Almost every single team's confidence interval is within every other team's confidence interval. So right away you can throw all those out.

The only thing the top chart demonstrates a statistical likelihood of is Sea, NE, Buf and Indy are each more dangerous than SF and Washington. However, given that they are looking at 31 stadiums, there would probably be such a result even if they were analyzing completely random coin flips.

 

[IllegalContact]

Jj watts ego was injurious today

 

[seven]

View attachment 18038 FTA: Futzed with graph, hopefully it is more legible.

Natural grass green trends left/less injuries
Turf types trend right/more injuries
Appears to be a clear correlation.

Scale on left goes from 1.5 to 10.5
Range best to worst as charted is about 10

Possible causes from:
hss.edu/conditions_artificial-turf-sports-injury-prevention.asp

Coefficient of Friction: This relates to how sticky or “grabby” the surface is and how much force it will take for a planted foot to slip. For surfaces with high coefficients of friction (e.g. old AstroTurf™) this requires a large amount of force. It is these surfaces on which players say their foot gets “caught in the turf.” Studies have shown that there is a higher incidence of ACL injuries with surfaces that have a higher coefficient of friction.

Coefficient of Restitution: This is defined as the ability of a field to absorb shock. It is measured by using the G-Max value where one “G” represents one unit of gravity. The United States Consumer Products Safety Commission (USCPSC) has determined that fields with a G-Max of greater than 200 are unsafe for athletic play. For example, concrete has a high G-Max level and grass has a low G-Max level. Athletic fields with a high G-Max level place more impact upon the athlete during a collision with the field. This translates to higher injury and concussion rates.


Knee/Ankle/Foot Visitor Injury Rate per 1000 AEs

 

[NE-VT]

Not sure exactly they would assume the stadium accounts for their noticed effect. All of those visiting teams at Gillette are forced to play the Patriots. It could be something about the Patriots style of play and/or the common trends in Patriots home games that causes this.

Are they certain that the Patriots are not just hitting harder than most other teams? Perhaps trying to cover and tackle Gronk is hurting people. Maybe away teams get hurt as their effort level starts to drop in discouragement after being blown out by a far superior team.

This is a dishonest use of statistics. It is one thing to find a numerical difference between groups. It is BS to pretend to know exactly what is causing that difference. The deflategate study shared the same problem.