FB: American Southwest Conference

[Ralph Turner]

SRSU 21, McM 17 Final

LC 27 ETBU 20 Final

[baddog]

SRSU won as CUAfan predicted but the scores seem a little out of the range of what he anticipated. Still, not too bad.
The LC/ETBU scores were pretty close, but the winner was wrong.

cowboy fan -- we are on the same side, but I would not call CUAfan's predictions "horrible." Perhaps a little accuracy-challenged. Average perhaps. Not horrible.
(Sorry CUAfan, that is the best I can do!)

[crufootball]

Got to give a lot of credit to MC for playing a great game against the Cru today. They played great and #44 Mays was a beast.

Here is hoping the Cru can get through the rest of the remaining games with W's and get a few people healthy.

[golden_dome]

Massey ratings has Miss College at #15 schedule.  Closer review shows 7 NESCAC teams having more difficult schedules, but they should not be considered since they do not play out of conference, (IMHO).

I wonder if anyone else has played four ranked teams so far? Or four ranked among the top 16 in the country, DIII or NAIA.

The top ranked Massey schedule to date, UW-LaCrosse, has played three ranked teams (Eau-Claire, Whitewater, HSU). Massey's #2 strength of schedule to date, Middlebury of the NESCAC, hasn't even played a ranked team yet.

MC's Schedule to Date
#12 Millsaps (7-0)
#14 Cumberlands (6-1 NAIA)
McMurry (0-7)
#16 Hardin-Simmons (6-1)
Louisiana College (3-3)
#3 UMHB (6-0)

I know there are other difficult schedules to date, but I'd put that up against just about anyone.

[Toby Taff]

IN fairness to CUAfan, his numbers are based on this seasons performances, and I think it took HSU to find itself as a team.  As we get closer to the end of the season and HSU puts a mud stomping on a few folks the numbers will get closer.

crufootball,

Amen.  Need to get some people healthy.  Of course the positive side of this is if they survive with the injuries and get some people healthy in time to be ready for playoffs, there are some young guys that are gaining good game time experience that will make the offense deeper.

[hsucowboyfan]

 Team Totals  HSU  HPU 
FIRST DOWNS  32  24 
   Rushing  22  7 
   Passing  9  16 
   Penalty  1  1 
NET YARDS RUSHING  499  126 
   Rushing Attempts  47  31 
   Average Per Rush  10.6  4.1 
   Rushing Touchdowns  7  0 
   Yards Gained Rushing  506  133 
   Yards Lost Rushing  7  7 
NET YARDS PASSING  193  250 
   Completions-Attempts-Int  12-15-0  34-51-2 
   Average Per Attempt  12.9  4.9 
   Average Per Completion  16.1  7.4 
   Passing Touchdowns  2  2 
TOTAL OFFENSE YARDS  692  376 
   Total offense plays  62  82 
   Average Gain Per Play  11.2  4.6 
Fumbles: Number-Lost  0-0  1-0 
Penalties: Number-Yards  6-37  1-5 
PUNTS-YARDS  1-23  5-194 
   Average Yards Per Punt  23.0  38.8 
   Net Yards Per Punt  23.0  30.8 
   Inside 20  0  1 
   50+ Yards  0  0 
   Touchbacks  0  0 
   Fair catch  0  0 
KICKOFFS-YARDS  10-595  3-180 
   Average Yards Per Kickoff  59.5  60.0 
   Net Yards Per Kickoff  46.7  40.7 
   Touchbacks  0  1 
Punt returns: Number-Yards-TD  3-40-0  0-0-0 
   Average Per Return  13.3  0.0 
Kickoff returns: Number-Yds-TD  2-38-0  9-128-0 
   Average Per Return  19.0  14.2 
Interceptions: Number-Yds-TD  2-2-0  0-0-0 
Fumble Returns: Number-Yds-TD  0-0-0  0-0-0 
Miscellaneous Yards  0  0 
Possession Time  26:53  33:00 
   1st Quarter  8:20  6:40 
   2nd Quarter  5:59  8:54 
   3rd Quarter  7:05  7:55 
   4th Quarter  5:29  9:31 
Third-Down Conversions  4 of 6  8 of 17 
Fourth-Down Conversions  1 of 1  1 of 3 
Red-Zone Scores-Chances  4-4  2-4 
Sacks By: Number-Yards  0-0  0-0 
PAT Kicks  6-9  1-2 
Field Goals  0-0  0-0 


WOW....total domination!! keep it up cowboys!!

[CUAfan]

To be quite honest, I never expect to get scores, or even winners, exactly right. What I'm doing is running an experiment of sorts, to see if the method I'm using can at least get in the ballpark...well, at least the neighborhood. There is so much variability in college football that when going off of a half-season's worth of stats, even getting in the right neighborhood can be hard (see HSU/HPU for an example ).

What I may do to address the sample size issue in future weeks is include the last season or two's worth of data. That may help, but if a team has a lot of new starters this year it would hurt the system. My other thought is to wait until the season's over, see what the projected scores for past games are at that point, and see how close the projections are once all the regular season games have been played. If I do that I'll just have to wait till next year to try again.

[roocru]

To be quite honest, I never expect to get scores, or even winners, exactly right. What I'm doing is running an experiment of sorts, to see if the method I'm using can at least get in the ballpark...well, at least the neighborhood. There is so much variability in college football that when going off of a half-season's worth of stats, even getting in the right neighborhood can be hard (see HSU/HPU for an example ).

What I may do to address the sample size issue in future weeks is include the last season or two's worth of data. That may help, but if a team has a lot of new starters this year it would hurt the system. My other thought is to wait until the season's over, see what the projected scores for past games are at that point, and see how close the projections are once all the regular season games have been played. If I do that I'll just have to wait till next year to try again.

CUA,

What you are trying is truly a daunting task.  I, for one, appreciate you posting your efforts here.  It is harder to post for all to see as you are honing your system than to announce later that your system works after the fact.  +k

[CUAfan]

Yes, well, it's also practice for when I try to do the same thing during basketball season. Might try it during baseball/softball season too, if I can figure out a satisfactory starting place.

This week I may try to do some crude measure of individual player value on the offensive side, if I can fit it in between work and another ongoing NBA project I'm working on.

[Bill McCabe]

CUAfan, keep it up.  Look at all the conversation this generated. 

[Ralph Turner]

CUAfan, your projection of SRSU 30 McM 16 in 28 possessions showed me how well McMurry did running the ball against SRSU.

McMurry had a long drive that ended in a red-zone fumble (at the SRSU 16) and gave up a 62 yd INT for a TD.

Otherwise, they controlled the ball for 293 yards rushing and the clock for 38:24.

That meant only 24 possessions for the game including the INT.

SRSU-McM box score

[Josh Bowerman]

To be quite honest, I never expect to get scores, or even winners, exactly right. What I'm doing is running an experiment of sorts, to see if the method I'm using can at least get in the ballpark...well, at least the neighborhood. There is so much variability in college football that when going off of a half-season's worth of stats, even getting in the right neighborhood can be hard (see HSU/HPU for an example ).

What I may do to address the sample size issue in future weeks is include the last season or two's worth of data. That may help, but if a team has a lot of new starters this year it would hurt the system. My other thought is to wait until the season's over, see what the projected scores for past games are at that point, and see how close the projections are once all the regular season games have been played. If I do that I'll just have to wait till next year to try again.

This actually sounds like an excellent doctoral thesis project.

You might try factoring in a sliding scale of points based on a team's record relative to the .500 mark.  What I mean is, if a team is 4-2 on the season, they get a +2 in their column, while a team that is 2-4 would get a -2.  A 4-4 team would get +/- 0 points, since they are "statistically neutral".

Might be interesting to see how that affects the outcomes.

[CUAfan]

To be quite honest, I never expect to get scores, or even winners, exactly right. What I'm doing is running an experiment of sorts, to see if the method I'm using can at least get in the ballpark...well, at least the neighborhood. There is so much variability in college football that when going off of a half-season's worth of stats, even getting in the right neighborhood can be hard (see HSU/HPU for an example ).

What I may do to address the sample size issue in future weeks is include the last season or two's worth of data. That may help, but if a team has a lot of new starters this year it would hurt the system. My other thought is to wait until the season's over, see what the projected scores for past games are at that point, and see how close the projections are once all the regular season games have been played. If I do that I'll just have to wait till next year to try again.

This actually sounds like an excellent doctoral thesis project.

Interesting that you say so, since all I have is a bachelor's....in kinesiology. If I could just get a job doing this kind of thing, I wouldn't have to work another day in my life.

Also makes me wonder what you'd think of a project I'm working on (just restarted actually) involving player development in the NBA since the 1979-80 season.

[roocru]

I was at the UMHB/MC game Saturday.  Just wanted to post some of my thoughts/impressions of the game.

I was impressed with Mississippi.  They are definitely improving.  The new RB is big, has good speed and most imprtantly has quick feet and made some nice moves yesterday. I liked the QB also as he made some good runs off fakes to the RB.   Although 71 rushing yards came on the first two offensive plays of the game, MC ended with 183 yards rushing and broke the UMHB streak of holding opponents to under 100 yards rushing.  Congratulations to MC.  They did what a bunch of other teams could not do!!

MC was crowding the LOS and daring UMHB to pass (like they did last year?) and made it more difficult to do so.  Apparent difference was no real breakaway runs like last year. (see below)

Kudos to the UMHB offensive line.  They are still dominant at the line of scrimmage no matter who is the "Tailback of the Day".  UMHB started Vaddell (normal starting FB) at tailback and appeared to use him to ram it up the middle.  The freshman they moved up then came in and made some nice shifty runs but appears rather small (not listed in the program).  I have an idea UMHB is confident enough in their offensive line to go with other tailbacks and are letting the injured ones get completely healthy.

UMHB is going to run the ball whenever they can.    However, this year when they do pass they are very effective.  In the third quarter when MC was putting 9 in the box, UMHB went to the pass, got two scores ahead and then went back to the run.  Going into this week, Josh Saenz had an efficiency rating of 193.32.  He ended the game with a rating of 184.66.  He is not nationally ranked because UMHB does not throw enough passes, but his rating would place him 5th if he were.  Feaster was second in the conference and 26th in the nation at an efficiency rating of 154.06.  (I am not saying Josh is a better QB, just that he is very effective in UMHB's offense!).

I am anxious to see the Cru with everybody healthy and am really curious about he game this week with a non-D3 team like Southern Oregon.  The NWC is very competitive with these Oregon schools and I think it will be a nice measuring stick for the Cru!

Also have to note that my Austin College Roos are on a roll and I will be there next week for Homecoming!!

[yessir]

Kudos Bill on the offensive line....Coach George does a good job of keeping the "Hogs" in check.  UMHB's always had an impressive/dominant O-line. One aspect of their team that is often over looked. Great job O-line!!!!