Archive for the ‘Graphs/Charts’ Category

Marlon Lucky and Nebraska on Third Down

October 5, 2007

Who knows what the Missouri game will actually come down to, but Nebraska’s ability to convert on third down will certainly be key. Thus far, Nebraska is converting 45.83% of their 3rd down attempts, which ranks us 20th nationally in this statistic. On the road, however, we’ve been absolutely brutal, converting just 3/15 attempts (20%)at Wake Forest. That’s just not going to cut it in Columbia.

An important component of 3rd down success is the emergence of big play guys who step up when it’s time to move the chains. If you think back to 2006, the go-to guy on 3rd down was Maurice Purify. In 2006, Nebraska threw to Purify 23 times on 3rd down resulting in 14 receptions. Of those 14 completions, 11 garnered first downs and three resulted in touchdowns. It’s early in 2007, so we’re still waiting for our 3rd down weapon to emerge…or are we?

I took a closer look at Marlon Lucky’s numbers for the year and was surprised by what I saw from him, especially on 3rd down. In the table below we have Lucky’s rushing statistics on 3rd down for 2007.

What jumps out immediately is the eye-popping average yards per carry. Did anyone realize that Lucky is averaging 7.77 yards per carry on third down? That’s pretty impressive. By digging a little further I was able to put that figure into perspective.

In this table we have the nation’s Top 10 players in average yards per carry on third down plays (with a minimum of 10 carries).

Here we see that Lucky’s 7.77 yards/carry rank 4th nationally, ahead of such stars as P.J. Hill, Ray Rice and Darren McFadden. Color me impressed.

But yards per carry is really only way to look at third down backs. Another and perhaps more important variable is the running back’s ability to convert on 3rd downs. Once again I looked at the statistics and found that Lucky has turned 8 of his 13 third down carries into first downs. That’s a third down conversion percentage of 61.54%.

So how does that stack up nationally? Below we see the Top 10 nationally for running backs in terms of 3rd down conversion percentage (Again minimum of 10 carries). Currently Lucky sits 9th nationally in this category.

These numbers tell me that Lucky’s contributions are being overlooked by many of us (myself included). He’s proven so far that he can come up big when the offense needs yards and we haven’t even talked about his ability to catch passes out of the backfield. To help illuminate this part of his game I also examined his receptions on third down.

I have to admit, I was surprised to see how infrequently we’ve thrown to Lucky on third down. However, he has had some success proving that he must be accounted for on every down, and is always a danger to move the chains for the Husker offense.

Pythagorean Projection – Nebraska and Expected Wins

May 23, 2007

The Pythagorean projection is an approximation of a team’s wins based solely on points scored and allowed. This concept was made famous by baseball analyst Bill James who discovered that the record of a baseball team could be very closely approximated by taking the square of team runs scored plus the square of team runs allowed.

Later statistician Daryl Morey of STATS, Inc. attempted to apply the formula to many sports. The basic Pythagorean projection formula looks like this:

What Morley found was the formula worked best for other sports if the exponent was tweaked. For example, for the NFL, the exponent is 2.37 instead of 2. The Pythagorean projection works remarkably well for the NFL. According the 2006 Football Prospectus:

“Out of 18 Super Bowls played since the 1987 strike season, 11 were won by the team that led the NFL in Pythagorean Wins, while only seven were won by the team with the most actual victories”.

Using this information as a starting point, I have attempted to examine the Expected vs. Actual Wins for Nebraska from the Osborne era through Callahan’s first three years. For my analysis I utilized the 2.37 figure of the NFL. The results of the analysis are listed in the table below.

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Coach Year Games Points For Points Against Expected Wins Actual Wins
Callahan 2006 14 428 256 10.8 9
2005 12 296 252 7.13 8
2004 11 275 298 4.98 5
Solich 2003 13 322 188 10.16 10
2002 14 383 335 8.10 7
2001 13 449 189 11.52 11
2000 12 456 213 10.3 10
1999 13 411 150 11.91 12
1998 13 383 183 11.08 9
Osborne 1997 13 565 197 12.01 13
1996 13 512 153 12.30 11
1995 12 421 150 11.04 12
1994 13 421 145 12.04 13
1993 12 421 176 10.65 11
1992 12 427 172 10.75 9
1991 12 454 208 10.37 9
1990 12 413 147 11.05 9
1989 12 492 174 11.06 10
1988 13 474 182 11.78 11
1987 12 423 133 11.27 10
1986 12 416 150 11.02 10
1985 12 398 136 11.13 9
1984 12 359 105 11.38 10
1983 13 624 186 12.30 12
1982 13 493 137 12.40 12
1981 12 349 103 11.37 9
1980 12 439 93 11.70 10
1979 12 380 131 11.11 10
1978 12 444 216 10.16 9
1977 12 315 200 8.95 9
1976 13 416 181 11.41 9
1975 12 367 137 10.94 10
1974 12 373 132 11.06 9
1973 12 306 163 9.80 9

Some have since utilized the formula as a crude measure of whether a team has over- or under-achieved. From this perspective if actual wins than expected wins that team has “over-achieved”. Notre Dame blog The Blue-Gray Sky completed a similar analysis of their team last year. Like BGS, I tend to see the formula more as a measure of a team’s luck over the course of a season. As BGS states:

“…because what the Pythagorean method really measures is how many games you were supposed to win based on a strict measurement of points scored and points given up; it’s not a measurement of how good a team really is. Perhaps another way to talk about it is in terms of Fate: which teams were “luckiest”, and which teams were snakebitten.”

So we could see the 2006 Huskers as a team that under-performed according to this measure. After all, the team’s expected wins were 10.8 and their actual wins were 9. Or we could think about the luck or lack of break’s the team experienced. Like say a 22-20 loss to Texas on a late fumble or a 17-14 loss to Auburn that included a “risky” fake punt.

But whichever way you choose to view the Pythagorean projection (and there are many), it is an interesting statistic in college football. I continue to hope that CFB moves toward the statistical analysis that is now commonplace among the MLB blogosphere. My plan is to continue to help usher Nebraska football coverage into the “Moneyball” era with pieces such as these.

As it stands, the analysis was hardly earth-shattering, but was an interesting undertaking nonetheless. Some things of note:

  • Check out how consistent Nebraska was during the 1980s and early 90s. Even managing to score 421 points three straight years.
  • One of the first things I did was jump to some years I felt the Huskers under-achieved (1987,1992,1998). Lo and behold, the formula agrees!
  • I don’t see a whole lot of “over-achieving” going on. Have we really been that unlucky through the years?
  • You can read more about the Pythagorean projection at:
    Pigskin Pythagoras
    Football Outsiders

    NFL Draft Analysis – The Lazy Version

    April 30, 2007

    This is all I’ve got, considering these two days are the last I will follow the NFL until playoff time.

    When I heard the names of this year’s crop of Huskers called on NFL Draft weekend, I thought the teams selecting them seemed familiar.

    Adam Carriker – St. Louis
    Brandon Jackson – Green Bay
    Stewart Bradley – Philadelphia
    Jay Moore – San Francisco

    It just seemed at first glance, that we have had a lot of Nebraska players on the rosters of these particular NFL squads. That got me thinking about patterns among NFL teams and which colleges they tend to raid for talent. In particular I was interested in which teams seem to select Huskers at higher rates than others.

    I limited my analysis to the years of 1982-2007, as that seemed to be the most readily available. I also tried to do some combining of teams based on moves to new cities. For example, the LA Rams and the St. Louis Rams simply became the Rams.

    Anyway, here is the chart showing the teams that have drafted the most Nebraska players from 1982-2007.

    Not that enlightening and only the Rams selection of Carriker would seem to fit the data. Certianly we have had many players on rosters of other NFL teams, but these are the ones that have drafted the most Huskers during that time period.

    Other random notes from the data:

    We’ve had 141 players drafted during that time period.
    Linebacker, DB, RB, and offensive line are the most common positions drafted.
    We’ve had three players drafted with picks #6 and #39.
    The players drafted at #6 were: Broderick Thomas, Lawrence Phillips, Grant Wistrom. The players picked at #39 were: Jared Tomich, Toniu Fonoti, Mike Brown


    If anyone else would like the data to play around with data, shoot me an email at jcadams(at) and I’ll send you the Excel file.

    Charting Our Progress – Time of Possession

    April 26, 2007

    Today we look at another of college football’s great axioms – time of possession, in our charting the progress series. I’d harbor a guess that this was one of the most discussed (or at least mentioned) variables during the Osborne era. Win the time of possession, win the game. Right? Maybe not.

    According the work of SMQ, this statistic means very little, only slightly more than yards penalized in college football.

    Here is what SMQ’s tables tell us about time of possession:

    Really not much to look at there. Time of possession, just doesn’t seem to be all that important in college football. Or at least it wasn’t in 2006.

    So it appears we have another reason to turn the volume to mute during televised college games – too much discussion about a variable that just doesn’t seem to matter. But why doesn’t time of possession matter like we think it should? Well there are actually already some pretty good explanations already out there, so let’s start with those.

    First we have a fantastic rant from Brian at MGoBlog from a point last season in which Michigan was leading the nation in TOP (they ultimately finished 2nd behind Texas A&M).

    Time of possession is a fraud. It is a fraud for these reasons:

    You cannot “keep the ball away from your opponent” any more than a basketball team can keep the ball away from their opponent. When you score or turn the ball over, they get the ball back, no exceptions. Unless you attempt an onside kick, your opponent is getting the ball back after you’re done with it. They will have the exact same number of possessions you do, plus or minus one depending on end-of-half and end-of-game hijinks.

    It describes the actions of teams after they acquire a big lead and not what they do to get said lead. One of the primary reasons Michigan is #1 in time of possession: they’ve jumped out to massive leads in many games and cruised home. Opponents like Michigan State and Notre Dame have spent entire halves in a spread hurry-up emphasizing quick movement of the ball. Meanwhile, Michigan leisurely pounds the ball into the line until the game is over. Result: in the second half Michigan three-and-outs can take more time than 80-yard touchdown drives by the opponent. This is hugely distorting and tells us nothing more than “Michigan has a big lead.”

    It places undue emphasis on the run game. Michigan features a crushing ground game and a crushing run defense. Result: lots of Michigan runs and very few opponent runs. This naturally helps TOP, but the reason Michigan is good isn’t because they possess the ball for relatively large amounts of time but rather those crushing units. Time of possession obscures the real reasons for Michigan’s success.

    Well played. I suspect TOP obscuring the real reasons for success can be said for a lot of folks. But we’ll come back to that.

    There is also real, academic research that also contradicts the implied importance of TOP. Harold and Daniel Sackrowitz in an issue of Chance, argued against the use of a ball-control, TOP-favoring offense. They claim:

    that “a team using ball control may reduce the number of possessions and points scored by its opponent, but it will lose more often than if it did not use ball control.”

    In their study, the Sackrowitz team developed a mathematical model for evaluating the efficacy of three styles of play: unconstrained (a team’s normal mix of offensive maneuvers and actions), time-consuming (using additional time), and hurry-up (using less time than normal).

    Beware dorky math mumbo-jumbo ahead.

    They modeled a typical time-limited game by a multidimensional Markov chain — a sequence of random vectors, each of which can be written as a string of numbers. The first three numbers, or coordinates, may indicate which team has possession, the current point difference between the teams, and the amount of time remaining. The remaining numbers of a given vector could represent the values of other variables deemed important for the particular game being considered, such as the number of time-outs remaining. Such a vector describes the state of the game at the beginning of each possession.

    Such a computational model allowed the researchers to check game outcomes over a broad range of possible situations involving weak and strong teams adopting different styles of play at different times. A consistent pattern emerged in all the cases studied: An unconstrained strategy is preferable to either the time-consuming or the hurry-up strategies for both teams, even when one team is demonstrably weaker than the other.

    And what the hell does that mean?

    “The results also force us to the realization that, despite what one feels emotionally, a proficient ball-control offense reduces the number of possessions for both teams,” the authors note. “Thus, if anything, one might guess that the better team would decrease its probability of winning by using ball control, particularly if it had reduced its probability of scoring.”

    But what about seemingly irrelevant Super Bowls involving the Big Tuna?

    In a 1993 New York Times article about football coach Bill Parcells, the reporter stated, “His masterpiece was the 1991 Super Bowl, in which his Giants defused the powerful and innovative offense of the Buffalo Bills through the simple expedient of denying Buffalo the use of the football.”

    The Sackrowitzes have a different view. “Even in the supposed ultimate endorsement of ball control, the 1991 Super Bowl, the Bills had ten possessions (but punted six times),” they remark. “In that game, a great defense helped to create the illusion that ball control is effective.”

    Hopefully you are at least starting to understand that time of possession is not a key to college football success.

    Now let’s look at Nebraska’s time of possession under Bill Callahan.

    Here we see some pretty amazing progress during Callahan’s tenure. Unfortunately it is in a statistic that we have highlighted to be irrelevant to success. But wait, here is where it gets a bit tricky.

    If we look at Nebraska in 2006 we will notice that the Huskers actually went 8-2 in games in which they won the time of possession battle. They were just 1-3 in games their opponents had the ball longer. So TOP does matter then in Nebraska, right? Wrong.

    Time of possession is still a shaky predictor of success. It looks like the football equivalant of a “red herring”. We think it matters, but research and a little better understanding of its ability to mask other, more important variables (that I will be focusing on later), allows us to see it a more appropriate fashion.

    But for those that are still a bit confused, or who insist on hanging on to the importance of TOP, here is a bit more.

    In 2006, Nebraska finished fifth in the country in TOP, but our record was just 9-5. Arkansas State finished one slot ahead of us at fourth in the nation. They finished the season with a 6-6 record.

    In 2005 Nebraska won four games when they possessed the ball more than their opponent. The Huskers also won four games when their opponent won the time of possession battle.

    It just doesn’t matter. Or at least not to the degree we might think it does.

    Charting Our Progress – Yards Penalized Per Game

    April 23, 2007

    With the rebirth of this series I have decided to look at the statistical categories in order of relevance from least important to most important according to the fine work of SMQ. To accomplish this I have combined both parts of his stats relevance watch to determine which statistic was the least relevant in terms of W-L record and Top 25 ranking in 2006.

    The overall loser was yards penalized per game. You can see its lack of relevance in CFB in the following table.

    Now, here is the chart of Nebraska’s standing relative to the national average in this statistic.

    And here is how they ranked nationally in each of those three season.

    2004: 46th; 51.00 yards/game
    2005: 63rd; 57.75 yards/game
    2006: 41st; 43.86 yards/game

    I could spend time analyzing Nebraska’s progress in this statistic, and it might actually be interesting to do so. But I won’t. Why spend time analyzing a statistic that has been shown to be irrelevant. How irrelevant? In 2006, Nebraska went 4-2 in games where they were penalized less yards than their opponent. In games the Huskers racked up more penalty yards they were 5-2 (the Cotton Bowl was a push as Nebraska and Auburn were both penalized 45 yards).

    Therefore, I thought it would be interesting to examine why this statistic might not be as important as the casual observer might think.

    First, let’s go with what SMQ said. After Part I:

    “First counterintuitive result: the most penalized teams were slightly better as a whole than the least penalized teams. Penalty yardage, over the course of an entire season, had no discernible effects on winning and losing. You can probably think of a situation that would specifically argue otherwise, cuz penalties are definitely bad, mmmkay?, but they’re bad more as situational mistakes than an overall, cumulative drain.

    Then after Part II:

    ”Again, penalty yards stand out as utterly meaningless; as in Part One, higher penalty yardage actually correlates slightly more with success, which makes no sense and should not indicate that jumping offsides is desirable or even, in the short term, meaningless (hello, Louisville), but the overall, cumulative consequences of flags were apparently nil.”

    Perhaps surprisingly, SMQ wasn’t actually the first to discover the lack of correlation between fewer yards penalized and success. Football Outsiders also examined this finding in the NFL back in 2003. They point out that this phenomenon was actually first noted in a 1988 book, The Hidden Game of Football written by Bob Carroll, Pete Palmer and John Thorn. However, according to Football Outsiders these authors made a key error in describing it, when they said:

    “[Penalties] don’t make a whole lot of difference. Over the course of a season, they tend to even out. For every drive-killing holding penalty, there’s an interference call that keeps a drive going.”

    Football Outsiders doesn’t buy the “even-ing out” hypothesis, because:

    ”The truth is, penalties don’t even out. Looking at the whole of last season, it’s clear that some teams were consistently penalized more than other teams. The difference is equal to a few hundred yards, which is also the difference between the best teams and the worst teams in punt return yardage. Would we say punt returns don’t really matter and even out over the course of the season? Certainly not.”

    Football Outsiders goes on to discuss that:

    What is perhaps even more surprising is the discovery that the majority of Super Bowl champions have actually been more prone to penalties than their opponents in the regular season. In fact, of the 37 Super Bowl champions, 23 actually had more penalty yards than their opponents.

    From here the article goes on to do the work for me. The talented Michael David Smith of Football Outsiders provides his theories for the finding that many of the most successful teams are actually penalized more in the NFL. I would guess that we could also apply these theories to college football as well. I will present each of Smith’s theories in italics and then provide my response after these.

    1. Good teams have the lead late in the game, which means they’re on defense against the pass more often. This makes them more likely to be called for defensive pass interference, which is the only penalty that can cost more than 15 yards.

    I never would have thought of this, but it seems like a possible explanation in the NFL. It is less helpful for college football given that pass interference is still just a 15 yard penalty.

    2. Good teams are more likely to decline their opponents’ penalties and have their own penalties accepted. All the NFL’s statistics are for accepted penalties only; declined penalties are treated as if they never occurred. It would make sense that a good team is more likely to have a successful play and therefore decline an opponent’s penalty, whereas a bad team is more likely to have an unsuccessful play and take the penalty yards.

    Another thought provoking hypothesis, that would be difficult to prove or dispel.

    3. Good teams are more aggressive, and while aggressiveness is usually a positive trait in football, it can lead players to be penalized.

    I actually like this hunch. It was the first one that came to mind. Think Florida State in the 90s.

    4. Winning teams could be smarter about taking penalties at the right times. For instance, it’s often advantageous to take a delay of game penalty rather than waste a timeout. (This only happens a few times a season and probably isn’t statistically significant.)

    I certainly agree with the lack of statistical significance portion of this hypothesis.

    5. When discussing penalties, it’s important to keep in mind that, contrary to what coaches and commentators tend to say, penalties shouldn’t really be called “mistakes.” When an offensive lineman holds Michael Strahan, he didn’t do it on accident. He did it on purpose because he knew Michael Strahan would beat him otherwise. He just hoped he wouldn’t get caught. Ditto a defensive back interfering with Randy Moss. Yes, there are some penalties that are mistakes — offsides, false starts, delays of game — but even those would seem to happen more often against better opponents. I’d expect a tackle to be called for illegal procedure much more often against Jason Taylor than against some practice squad scrub. So when you see that the Giants’ opponents were flagged for more penalties than any other team’s opponents last year, don’t assume the Giants just got lucky. The Giants certainly played a role in it. Also keep in mind that NFL officiating crews are not all created equal. Some crews call more penalties than others. But even if one team was stuck with a flag-happy crew more times than another team, it would make no difference in the net penalties shown here.

    Now we’re talking! This is one that definitely needs to be considered and should probably be analyzed more carefully. It certainly doesn’t clarify the entire picture, but no one ever seems to bring this one up.

    Ok, let’s conclude this piece by keeping our wits about us. Teams should continue to attempt to avoid penalties whenever possible. And we should not expect to hear coaches come out and endorse a high number of penalties, but at the same time we now know a little bit more than most announcers about their relative importance. As Football Outsiders concludes:

    So does this data say that penalties don’t matter? It most certainly does not. We’ve all seen penalties that had game-altering implications. But penalties are probably less important than coaches and commentators would have us believe. And this probably deserves further study.

    Bowman, the Secondary and Interceptions

    April 3, 2007

    The injury to Zack Bowman got me to crying in my beer thinking more about our secondary.

    Obviously we are back to where we were when the season began last August. Grixby and Jones will be the ones to go against the Big 12’s best. In case you forgot, here is just a short list of that talent:

    Todd Blythe
    Malcolm Kelly
    Adarius Bowman
    Limas Sweed
    Billy Pittman

    Ouch. Anyway, Grixby made a great point the other day, that shouldn’t be overlooked.

    “We have two corners that started every game last year,” Grixby said. “We went 9-5. Back with more experience, we just keep getting better.”

    Grixby and Jones will be improved. They will still be physically overmatched at times, but they will be improved.

    Bowman’s injury also gives someone a chance to step up. That player could be Armando Murillo. Callahan sounds optimistic when discussing Murillo’s abilities.

    “He can burst. He can change direction,” Callahan said. “He can play physical-type coverage techniques that we want him to.”

    Another guy to watch will be Anthony West who just moved back to corner after beginning the spring at FS. I think West is going to be a great player for us once he finds a stable home. I was very impressed by West’s film a year ago and reports indicated he was giving Tierre Green all he could handle in the battle for starting FS this spring. His development is definitely something to watch.

    My biggest concern with the loss of Bowman is our defense’s ability to make big plays. I’m talking game-changing takeaways and interceptions returned for TDs. We just haven’t seemed to have many of those in the Callahan era. This spring the corners stated they were looking for more interceptions. They should be. This is a graph of Nebraska’s interceptions over the last seven years. Note – I would have gone back further, but the national stats were difficult to find.

    Click to enlarge

    The blue line within the graph shows the national average of interceptions for each of the seasons. Aside from the 2003 season when Bo Pelini’s band of marauding bandits led the nation in interceptions, you can see that our interception rate has been, well, average.

    I don’t know exactly what to make of all this. Obviously Pelini’s zone coverages allowed the DBs to watch the eyes of the QB more, but outside of that type of schematic variable, our performance is difficult to account for. Clearly we have had some talent during those years, including NFL players Fabian Washington, Josh and Daniel Bullocks, Keyou Craver, and Jerrell Pippens (I’m sure I left some folks out). But we’ve also had some players who were nice, had good personalities, tried their best (Pat Ricketts, Blak Tiedtke,Andrew Shanle). What we haven’t had is a consistent threat to pick off passes outside of Josh Bullocks. I had high hopes that might change this year. I’m less optimistic now without Bowman.

    Finally, for those that doubt that interceptions are important, here are some numbers:

    2006: Florida and Ohio State – 21 each
    2005: USC – 22
    2004: USC – 22
    2003: Oklahoma – 22, LSU – 21
    2002: Ohio State – 18
    2001: Miami – 27, Nebraska – 19
    2000: Oklahoma – 22, Florida State – 19

    Lastly, Brandon and Chuck made some interesting points about whether Bowman will bother to come back in 2007 or 2008, or whether he will jump to the NFL. That’s a tough situation. I think he needs to play before he thinks about the NFL. Whether that will be November of this year or not, remains to be seen.

    Another Look at Nebraska’s Third Downs in 2006

    March 14, 2007

    To piggy-back on yesterday’s work, I thought I would take another look at Nebraska’s third down conversions last season. In 2006 the Huskers converted 45.2% of their third down chances. This was a vast improvement over 2005 when Nebraska’s third down conversion percentage was just 33%.

    Yesterday we compared Nebraska to the rest of the NCAA with regards to 3rd down conversions. Another useful comparison is that of the expected percentages in the NFL. I have posted this before, but this is the expected success ratio that has been identified by Brian Billick in Developing an Offensive Gameplan:

    3rd and Long (7+ yards) 20-25%
    3rd and Medium (4-6 yards) 45-50%
    3rd and Short (1-3 yards) 75-85%

    Again that just provides us with some more context and is important given Coach Callahan’s coaching background.

    Today, I thought we would look more at the third down playcalling of the 2006 Huskers. Let’s start with third and short situations (1-3 yards to go). Last season Nebraska faced this situation around 4.5 times/game. Given that I would expect that Callahan has eight to ten plays in his offensive game plan for this situation.

    According to Brian Billick there are two schools of thought regarding third and short situations: get the first down (duh!), or take a shot at a big play. A “big play” in this situation is one with definite touchdown potential or at least a large, meaningful gain. Running a play to get a first down, on the other hand, would look more like Callahan’s three-tight-end, smash-mouth formation or a simple QB sneak. With that said, let’s look at Nebraska’s third and short play-calling breakdown.

    Here we see 35 run/29 pass split. This is a pretty even split given the short yardage involved. Most would probably expect a heavier dose of runs. This is also an area in which Callahan seems to really work hard to go against common tendencies. Or he just doesn’t have faith in our running game to pick up the yardage on the ground. What you’ll see, however, is a slightly higher success rate on third and short when we run rather than when we pass. This is unfortunately, pretty good support for all those who bashed Callahan’s decision to pass on 3rd and 1 late in the Texas game.

    The second important third down situation is third and medium (4-6 yards to go). This breakdown is covered in the same chart. Third and medium success is important to a coach’s overall game plan. If he feels that his team can convert in this situation, his first and second down calls take on an additional dimension. This may allow more deep throws on first down, or more aggressive “big play” type calls on second and medium when you are confident in your third and medium chances. You’ll notice that Nebraska enjoyed amazing success in 2006 when facing this situation. I would attribute much of this success to the success of Nebraska’s play-action passing game and to the development of the middle screen to Brandon Jackson and Marlon Lucky that was successful several times on third and medium. Another reason Callahan seems to have success in this situation is his use of shifts and motion and running plays that have not been used earlier in the game. Both of these help keep the defense off-balance.

    The next area is third down and long which refers to any situation where the team faces 3rd and 7+ yards to go. You can see Nebraska’s 2006 breakdown below:

    Obviously you’ll notice we don’t run a lot on third and long for obvious reasons. While it is worth a shot occasionally, it is generally not in the team’s best interest. In the NFL, teams average just 11 runs per year when faced with 3rd and long, and they typically convert just two of these rushing attempts per season.

    Yesterday’s graphs indicated that Nebraska converted at a higher percentage than the national average when facing situations between 3rd and 7, and 3rd and 13 yards to go. Much of this again can likely be attributed to Callahan’s scripted plays for facing this type of situation. These plays should be designed to meet at least one of the following three objectives:

    1. Given the right rotation by the secondary, presents you with an opportunity for a deep throw down the field for a substantial gain.

    2. If given the right one-on-one match up, allows your receiver to run a good route whereby the catch should, at a minimum gain the yards needed for the first down.

    3. Provides the quarterback, by way of a dump-off to a primary receiver, with a receiver who has a chance to make an easy catch, allowing him to try to make a move that will enable him to gain the distance needed after the catch.

    By scripting plays with these objectives in mind, and having the players in place to make the plays, Callahan has helped the team to improve immensely on third and long. This has also gone a long ways toward improving the team’s overall success on third down. Next up will be spending time working on improving the team’s overall success on third and short. Knowing that, fans should not be surprised that another big back like Quentin Castille was signed this February.

    A Look at Nebraska’s Third Downs in 2006

    March 13, 2007

    All of the work and the graphs come courtesy of the indomitable Brian at MGoBlog. This is an amazing accomplishment to have put this together for all Division I teams. Unbelievable. This is the reason he is considered one of the 20 Most Influential Sports Bloggers.

    Anyway let’s take a look and see what we find for Nebraska.


    The first graph shows, third down efficiency. According to Brian – the thick line in the center is the NCAA average (e.g., approximately 68% of third and ones were converted last year). There is a second line that represents an individual team’s third down efficiency. Where there is a gap between the lines that gap is filled in with either red or green depending on whether it is “good” or “bad”. Being above the line is good for offenses–you convert more often. Being above the line is bad for defenses–you are converted upon more often. You want to see a lot of green in these graphs.

    Overall, the majority of the graph depicts good news for Nebraska fans. We see a lot of green, which is great. Our third down conversion rate was above the national average from about 3 yards out, to about 14 yards out. It should come as no surprise, therefore, that we finished the season ranked 17th nationally in third down conversion percentage (45.2%). What might be surprising, perhaps, is the red we see on the left end of the graph. This indicates that we converted third downs from between 1 and 3 yards out at a clip that was below the national average. I’m not sure what to attribute this to. The lack of a power running game against stacked defenses is one possibility and injuries to Cody Glenn are another. Interestingly, the lack of conversions on 3rd and short led us to to go-for-it on fourth down 23 times in 2006. This was more 4th down attempts than all but 18 other Division I teams.

    This second graph illustrates third down distance distribution. Again, the line in the center is the NCAA average and the thinner line is the individual team’s. Green is just “above”; red just “below,” since there’s no clear distinction on good or bad based solely on what side of the line you’re on.

    Here we see lots of green on the left hand side of the graph. This indicates that we have more third downs of distances between 1 and 5 yards than the national average. This is good thing at first blush. It means our first down efficiency is putting us in third and short situations. Unfortunately when you couple this graph with the first one, we see a bit of a problem. We are having more third and short situations, but that is one major area we convert at a level below the national average. I can only imagine this is the type of stuff that keeps Coach Callahan up at night.


    Now we are looking at the defensive side of the ball. Here we want to be green and below the thick line, which is indicative of third down efficiency defense that is better than the national average. You’ll notice that we look good on third short and third and long. Where you see the Huskers struggle is on third and medium defense. I’m a little surprised by these findings. I truly thought we would be worse than the national average on third and long. How many times did it seem like teams completed a big pass on third and long? We all of course remember the third and long OU faced backed up to their goal line in the Big 12 Championship Game. Apparently this is a bit of an abberation and we find ourselves attending more to third and long conversions by our opponent, than the times our defense gets a stop. Or perhaps the conversions on third and long just come at inopportune times.

    This graph again shows the distribution of third downs that the Nebraska defense faced. Not much really jumps out here to me, except for the big green spike at the 3rd and 10 yards-to-go mark. Did we really hold our opponents to no yards on first and second down that frequently? It is definitely well above the national average and I find that extremely interesting. I have absolutely no idea what to make of it, however.

    I once again want to reiterate that none of this is original work and you can check out graphs for every team on MGoBlog. This is more of the amazing work that is being done by CFB bloggers. For those of you that pay for Nebraska football sites ask yourself what you are paying for? If you’re reading the MSM outlets in Nebraska – why don’t/can’t they do this? I belong to several pay-sites and read both major papers daily, and I’ve never come away with any information that was half this meaningful. Here it is being produced and openly distributed for free. See why many folks truly believe that blogging and its off-shoots are the future of sports coverage?

    The Safeties: A Rudimentary Semi-Historical Analysis

    December 12, 2006

    This year’s safeties have taken a lot of heat from Nebraska fans (and especially from me). As a result, I thought it might be helpful to try and put their performance into some type of historical perspective. The results are below.

    A few things to keep in mind: First, when we examine the statistics we must remember that these reflect four different defensive coordinators, each with his own system. Secondly, these statistics do not summarize all that is expected or required of a safety. Third, the performances include those of a “once in a generation” type player in Mike Brown along with 3 other players who made NFL rosters at one time or another. Fourth, I am not privy to film sessions or to how the performers graded out in the eyes of the coaches. And finally, the 2006 season is the only one of those included, in which both safety spots were filled by first-time starters.

    Player Games Tackles TFL INTs FF FmbRec
    Tierre Green 13 48.5 .5 1 0 1
    Andrew Shanle 13 47.5 0 4 0 1
    Player Games Tackles TFL INTs FF FmbRec
    Daniel Bullocks 12 83 4 1 2 1
    Blake Tiedtke 12 68 6 1 2 0
    Player Games Tackles TFL INTs FF FmbRec
    Josh Bullocks 11 68 2 2 0 0
    Daniel Bullocks 11 58 4 5 1 1

    Player Games Tackles TFL INTs FF FmbRec
    Phillip Bland 4 7 1 0 0 0
    Josh Bullocks 13 49 0 10 0 0
    Daniel Bullocks 13 59 4 2 1 1

    Player Games Tackles TFL INTs FF FmbRec
    Philllip Bland 13 84 6 1 1 1
    Josh Bullocks 13 48 0 1 1 1
    Shane Siegel 14 14 1 0 0 0
    Aaron Terpening 14 17 2 0 0 0

    Player Games Tackles TFL INTs FF FmbRec
    Dion Booker 12 62 1 1 0 0
    Willie Amos 9 28 0 4 0 0
    Phillip Bland 10 24 1 0 0 0

    Player Games Tackles TFL INTs FF FmbRec
    Joe Walker 11 44 2 2 1 1
    Dion Booker 11 34 2 0 0 0
    Troy Watchorn 11 27 2 5 0 0
    Clint Finley 11 22 1 0 0 0

    Player Games Tackles TFL INTs FF FmbRec
    Mike Brown 12 96 8 5 6 1
    Dion Booker 12 28 0 1 1 0
    Clint Finley 12 27 0 1 0 1
    Joe Walker 10 11 4 0 2 1

    Player Games Tackles TFL INTs FF FmbRec
    Mike Brown 12 102 5 1 1 1
    Clint Finley 9 28 3 3 3 1
    Joe Walker 12 50 5 3 1 0

    After looking things over, my take is that our safeties performed average to a little below average by way of statistical analysis. Shall we say, I don’t know…mediocre? What do you guys think?

    Quick Starts – Sluggish Finishes?

    November 23, 2006

    Tom Shatel recently discussed the second half struggles with Coach Callahan. I still maintain too much is being made about adjustments or a lack thereof at halftime. I remain convinced a stronger argument could be made concerning our execution by half. Let’s face it – we are hot right now in the first half of games. In the second half – not so much.

    Coach Callahan seems to agree somewhat with my assessment:

    “It’s not like you go in at halftime and come up with a whole new game plan. Games are usually declared in the first quarter, the first 25 plays of the game. You can get a good look at how the offenses and defenses are going to play. It’s not like you’re going to go in and flip your whole game plan, tear it apart and come up with something new.

    I know people like to make a big deal about halftime adjustments, but you really don’t see people change what they do that often. A lot of times people play better (Emphasis mine). You may jump on them early and they feel an urgency. Players pick up on things, too. Players are smart. They see things and they make adjustments out there. A lot of times, that’s what you see.”

    A year ago we were worried about our anemic starts, now we’re stumped by our second half output. The “Goldilocks Theory” suggests next year we put together a full four quarters.

    But anyway here is what our offense and defense performance looks like on a quarter-by-quarter basis.

    Rushing Offense
    Quarter Attempts Yards Avg TDs
    1st Quarter 122 620 5.08 5
    2ndQuarter 109 446 4.09 8
    3rd Quarter 108 452 4.19 2
    4th Quarter 108 487 4.51 8

    Passing Offense
    Quarter Att Comp Pct Yards Ints TDs Rating
    1st Quarter 69 46 66.7 673 1 8 183.96
    2nd Quarter 84 56 66.7 836 2 8 176.94
    3rd Quarter 72 42 58.3 577 0 4 143.98
    4th Quarter 78 42 53.8 624 1 7 148.10

    Rushing Defense
    Quarter Attempts Yards Avg TDs
    1st Quarter 75 232 3.09 1
    2ndQuarter 90 402 4.47 3
    3rd Quarter 75 278 3.71 1
    4th Quarter 100 443 4.43 6

    Passing Defense
    Quarter Att Comp Pct Yards Ints TDs Rating
    1st Quarter 54 26 48.1 282 4 1 83.31
    2nd Quarter 98 62 63.3 810 3 6 146.78
    3rd Quarter 72 42 58.3 577 0 4 143.98
    4th Quarter 112 64 57.1 927 3 4 133.09

    I’m going to stay out of this, but I have an informed readership, so you guys tell me what jumps out at you?