Beyond the Box Score: S&P

You know how baseball stat nerds decided that batting average wasn’t a very strong indicator of a batter’s performance, so they started looking at OPS (On-base % + slugging avg)?  Well...what if there were a similar measure for football?

What makes OPS so great is that there are a couple different ways to end up with a good measure.  I would consider anything over .800 a pretty decent OPS.  To get there, you could have a great on-base % (.400) with mostly singles power (.400 slugging) or maybe a mediocre on-base % (.325) with solid power-hitting (.475).  Or maybe you’re terrible at getting on-base (.275), but you hit the crap out of the ball when you do (.525).  All those different types of hitters end up with an .800 OPS.

Basically OPS measures efficiency (on-base %) and explosiveness (slugging).  Well, isn’t that basically what my two recent obsessions—success rates and PPP—measure?

What would happen if we combined Success Rates and PPP?  Would that give us the football version of OPS?

We could even call it something catchy, like S&P!

Click 'Full Story' for more.

To see if S&P is a worthwhile tool, let’s compare Big 12 RBs with it.  For these purposes, I’ll look at each RB’s overall Run Success Rate and PPP (no filters like "close games only" or anything like that), and I’ll look at only RBs with at least 50 carries in 2007.  Strangely, that comes up with a nice, neat list of 25 RBs.

  1. Shannon Woods (Tech): .643 success rate + .535 PPP = 1.18 S&P
  1. Jimmy Jackson (MU): .583 success rate + .564 PPP = 1.15 S&P
  1. Jorvorskie Lane (A&M): .604 success rate + .500 PPP = 1.10 S&P
  1. Kendall Hunter (OSU): .616 success rate + .441 PPP = 1.06 S&P
  1. Brandon McAnderson (KU): .543 success rate + .493 PPP = 1.04 S&P
  1. Demarco Murray (OU): .528 success rate + .459 PPP = 0.99 S&P
  1. James Johnson (KSU): .509 success rate + .463 PPP = 0.97 S&P
  1. Jake Sharp (KU): .587 success rate + .376 PPP = 0.96 S&P
  1. Jamaal Charles (UT): .491 success rate + .459 PPP = 0.95 S&P
  1. Dantrell Savage (OSU): .575 success rate + .328 PPP = 0.90 S&P
  1. Quentin Castille (NU): .539 success rate + .355 PPP = 0.89 S&P
  1. Chris Brown (OU): .479 success rate + .385 PPP = 0.86 S&P
  1. Vondrell McGee (UT): .457 success rate + .354 PPP = 0.81 S&P
  1. Allen Patrick (OU): .468 success rate + .338 PPP = 0.81 S&P
  1. Marlon Lucky (NU): .471 success rate + .280 PPP = 0.75 S&P
  1. Hugh Charles (CU): .441 success rate + .309 PPP = 0.75 S&P
  1. Brandon Whitaker (BU): .431 success rate + .294 PPP = 0.73 S&P
  1. Jay Finley (BU): .418 success rate + .288 PPP = 0.71 S&P
  1. Tony Temple (MU): .407 success rate + .292 PPP = 0.70 S&P
  1. Alexander Robinson (ISU): .376 success rate + .272 PPP = 0.65 S&P
  1. Leon Patton (KSU): .321 success rate + .325 PPP = 0.65 S&P
  1. Mike Goodson (A&M): .435 success rate + .197 PPP = 0.63 S&P
  1. J.J. Bass (ISU): .358 success rate + .228 PPP = 0.59 S&P
  1. Jason Scales (ISU): .343 success rate + .231 PPP = 0.57 S&P
  1. Demetrius Sumler (CU): .327 success rate + .166 PPP = 0.49 S&P

Interesting.  The first thing I notice is, the top of the list includes a nice mix of short-yardage guys (Jackson, Lane) with scat-style backs (Woods, Hunter) and explosive guys (Murray, Johnson).  I like that.

The second thing I notice is, backup RBs (Jackson, Hunter, Murray, Sharp) make up 4 of the top 8, while established names like Marlon Lucky, Allen Patrick, Hugh Charles, and Tony Temple languish—and in the case of Lucky, Patrick, and Temple, they’re ranked reasonably far below their backups (though that’s not fair in the case of Patrick, who was pretty much #1A to Murray’s #1B and Brown’s #1C).  Is that a sign that this list isn’t very good?  Is that a sign that coaches just don’t know what they’re doing?  A little of both?  

For a lot of other measures, I only look at what happened in "close games" (i.e. games that were within two possessions or less)—should I do the same here?  If there are a lot of backups at the top of the list, was a lot of their damage done in blowouts?

S&P (CLOSE GAMES ONLY)

  1. Jimmy Jackson (MU) = 1.20
  1. Jorvorskie Lane (A&M) = 1.15
  1. Shannon Woods (TT) = 1.09
  1. Kendall Hunter (OSU) = 1.01
  1. James Johnson (KSU) = 0.96
  1. Chris Brown (OU) = 0.93
  1. Quentin Castille (NU) = 0.92
  1. Brandon McAnderson (KU) = 0.91
  1. Jamaal Charles (UT) = 0.89
  1. Demarco Murray (OU) = 0.83
  1. Allen Patrick (OU) = 0.83
  1. Dantrell Savage (OSU) = 0.82
  1. Jake Sharp (KU) = 0.78
  1. Vondrell McGee (UT) = 0.74
  1. Hugh Charles (CU) = 0.69
  1. Marlon Lucky (NU) = 0.69
  1. Brandon Whitaker (BU) = 0.68
  1. Leon Patton (KSU) = 0.67
  1. Tony Temple (MU) = 0.64
  1. Mike Goodson (A&M) = 0.61
  1. J.J. Bass (ISU) = 0.54
  1. Jay Finley (BU) = 0.49
  1. Jason Scales (ISU) = 0.48
  1. Alexander Robinson (ISU) = 0.46
  1. Demetrius Sumler (CU) = 0.43

So a few went up and a few went down, but that stayed relatively similar.  Consistency is good, but...yeah, while I love Jimmy Jackson, I don’t think I’ll go around calling him the best RB in the Big 12.

Should I maybe take receptions into account here?  I realize being a running back is about running, not catching, but in today’s game, offenses are getting more and more creative in getting their best athletes touches in space.  However, does this favor spread and west-coast offense RBs over the power backs who don’t catch passes?  Let’s see...

S&P (Rushes and Receptions – and close games only)

  1. Jorvorskie Lane (A&M) = 1.19 (scratch the "hurts the power back" thing)
  1. Jimmy Jackson (MU) = 1.13
  1. Shannon Woods (Tech) = 1.02
  1. Kendall Hunter (OSU) = 1.00
  1. Chris Brown (OU) = 1.00
  1. Quentin Castille (NU) = 0.98
  1. James Johnson (KSU) = 0.97
  1. Brandon McAnderson (KU) = 0.95
  1. Jamaal Charles (UT) = 0.89 (fourth quarters only: 1.20)
  1. Dantrell Savage (OSU) = 0.88
  1. Marlon Lucky (NU) = 0.83
  1. Allen Patrick (OU) = 0.83
  1. Hugh Charles (CU) = 0.80
  1. Jake Sharp (KU) = 0.80
  1. Brandon Whitaker (BU) = 0.79
  1. Demarco Murray (OU) = 0.77
  1. Mike Goodson (A&M) = 0.75
  1. Vondrell McGee (UT) = 0.74
  1. Leon Patton (KSU) = 0.72
  1. Jay Finley (BU) = 0.71
  1. Tony Temple (MU) = 0.68
  1. J.J. Bass (ISU) = 0.54
  1. Alexander Robinson (ISU) = 0.52
  1. Demetrius Sumler (CU) = 0.48
  1. Jason Scales (ISU) = 0.47

So no matter how I filter the numbers, the same few names—Lane, Jackson, Woods, Hunter—appear at or near the top.  And it doesn’t change if I weight PPP > success rates (or vice versa).  So I think I have to accept that if I’m looking at effectiveness and efficiency, the RBs at the top of the list really were the best in the conference.  And really, that makes some amount of sense.  If we’re looking at consistency, then that’s obviously going to penalize Jamaal Charles, who was thrice the RB in the fourth quarter as he was the rest of the game (which is great if it’s close in Q4...and bad if you fell behind in Q’s 1-3 because of poor RB play).  And it’s going to penalize guys like Allen Patrick, Hugh Charles, and Dantrell Savage, who dealt with nagging injuries for part of the season.

In all, though, this does show us one thing: that coaches tend to play guys with potential over guys with a defined ceiling.  Demarco Murray is a threat to score any time he touches the ball, but Chris Brown’s more likely to move the chains.  Same, really, with Tony Temple and Jimmy Jackson.  JJ’s never going to break a run for more than about 15-20 yards, but while TT can take one 99 yards, he’s also infinitely more likely to dance and lose about 8.  When it comes to evaluating players for what they did in a given season, though, potential doesn’t really mean jack, does it?

Coming up, I'll look at QB and WR/TE numbers too...see if I have something here, or if I need to look at these numbers in a different way.  And as always, if you have comments or suggestions, I'm all ears.

Oh, and the S&P measure certainly also proves something else: that Dennis Franchione is an idiot.

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