"Jim's a tough guy and you can see his personality is all over this football team," Fitzgerald said.
Greetings again, my fellow Wolverines! Last week, I was able to drop the first official wallpaper of the season in my vintage schedule wallpaper based on a schedule card from 1969. This week, I’m happy to bring you the wallpaper for our first opponent of the season, the Utah Utes.
In preparing to do this wallpaper, I did a good amount of research on the Ute people, for whom the team is named. The Ute people are also the namesake of the state of Utah, itself. The word “Ute,” in the native tongue of the Ute people, Shoshonean, means “land of the sun” or “ the high place.” The Ute people were a highly-artistic people, making all sorts of beaded jewelry for use in battle and for trade. The Ute were also some of the earliest adopters of the horse in America (reports state as early as 1580). They were fierce warriors and with the addition of horses, became excellent big game hunters, as well. They were also highly spiritual, and are credited as being the first documented (by approx. 200 years) peoples to make use of a process called “mechanoluminescence” in their ceremonies. It’s said that they would use clear quartz crystals inside of translucent buffalo hide rattles. When rattled, the friction and mechanical stress of the crystals impacting each other would create a light that would be visible through the hide rattles. They believed this was evidence that the spirits were being called to their ceremonies.
I had a lot of fun researching the Ute people and it reminded me of the excellent time I had when doing research for the CMU wallpaper. I loved learning about the Chippewa and the Ute were the same experience. That being said, I hope that we stomp them on the football field. Respect gained for their history or not, I want them crying in defeat.
The image I used for the wallpaper below is of an actual Ute Tipi (or Teepee) on file at the Library of Congress. I hope I did a job that is both respectful and artistically-sound. Let me know! As always, I appreciate constructive criticism and/or suggestions for future works. Have a wonderful day and GO BLUE!
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Smart and efficient QB play vs. the Utah defense will be the key to a Michigan victory at Utah on September 3rd. With Michigan in submarine mode, and the limited amount of info coming from camp we can only still assume who the starter at QB will be at Utah on September 3rd. My guess is that Rudock will be the Starter to open the season. Harbaugh needs his experience to help lead an offense that we extremely inefficient under the old regime and with Devin Gardner under center.
Below I performed another exercise. This time I compared the Utah Defense to Jake Rudock while he was at Iowa in 2014. I can do this with confidence because I know Harbaugh is light years far, and away better of a coach than what Rudock had at Iowa and Michigan has similar or more talented players at the skilled positions. If Michigan continues where they left off improving on the Offensive line in 2014, I will bet an arm he will improve, or put up exactly the same type of numbers as Michigan’s 20015 starters.
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Scroll Lower for the breakdown.
|QB 2014 entire year||TEAM||Pos||G||Att||Comp||Pct.||Yards||Yards/Att||TD||Int||Rating||Att/G||Yards/G|
|Utah Pass D 2014||Utah||13||450||267||59.3||3206||7.1||23||12||130.71||34.6||246.6|
|Ruddock vs. power 5 2014||Iowa||JR||10||252||149||59.1||1864||7.4||12||5||133||25.2||186.4|
|Utah Pass D VS power 5 2014||Utah||10||335||201||60||2499||7.5||17||11||132.84||33.5||249.9|
When comparing Rudock to last years Utah defense it is easy to see the difference a more efficient QB would have made in critical situations. Too often last season and against Utah, Michigan must avoid third and long. The run game will have to be effective on first and second down, and a mix of run and pass on first down will help keep Utah unbalanced on defense.
I analyzed the overall stats first and then compared the Utah pass D vs. what Rudock was able to do in 2014 at Iowa. Utah Gave up a lot of yards overall, but the key stat overall is their pass D rating. Efficiency and good decision making on the road will be the deciding factor as to whether Michigan will score points and not turnover the ball.
As I skip down to the next tab, I compared 3rd down and 7-9 yds to go. Rudock was efficient and careful. In fact, Rudock was number 6 in the Big Ten in this category, while Utah's D ranked 7th in the Pac 12. Utah ranked 98th nationally on 3rd a 7-9 yds to go on defense in 2014. Rudock was ranked 36th nationally on 3rd and 7-9 too. Rudock also takes care of the ball in this situation and Utah did not record a single Int during the 2014 season.
Rudock was solid in the 4th qtr last season. He led the Big Ten in this category as the most efficient QB. Rudock posted a 6-1 TD/int ratio in 2014. Devin Gardner, on the other hand, was severely inefficient and finished 10th in the Big Ten in this category. Michigan was in the game last year, but could not get anything going in the 4th qtr.
|4th qtr entire year 2014||Team||Yr||Pos||G||Att||Comp||Pct.||Yards||
The next element that will make a huge difference will be comparing the returning production of Utah, vs. that of Michigan's. Utah returns 76% of their defense in terms of who recorded at least one tackle. Utah returns five starters on defense, and each contributed significantly. The Utes return Jared Norris, who led the team in tackles in 2014. The Utes lost 18.5 sacks from last year from the graduating Nate Orchard, but Hunter Dimick returns this year after being second on the team with ten sacks. Utah is an aggressive defense that likes to blitz, but they give up the big play often. As you can see above they gave up 23 plays of 15 yards or more during the fourth qtr of all game in 2014. Utah was the second best defense in the Pac 12, but they gave up 393 yards per game. Utah would rank as the number 10 defense overall in the Big Ten in 2014. The more alarming stat for Utah will be that they gave up 3200 yards passing in 2014, that would be good for dead last in the Big Ten.
|Utah Defense||Solo Tackles 2014||solo tackles ret 2015||Sacks 2014||Sacks ret 2015||Int 2014||Int ret 2015||% ret tac 2015||% ret int 2015||% Sack Ret 2015||Projected starters returning 2015||2015 total returning production|
|Returning starters||Solo Tac||Sacks 2014||Int 2014||2014 starts|
Advanced Football Analytics puts together an interesting game summary, titled Game Scripts, for the NFL. Early last season I decided that I would put together these stats for the Big Ten, and here they are! (If this seems like an odd time to put together a summary of anything that happened in an actual football game last season, you’re not wrong. But it’s basically the last opportunity before there’s actual new football so… enjoy.)
What is a Game Script?
A Game Script (GS) is an average of the point differential for every second of a game. For example, if a team scores a field goal at the very end of the 1st quarter and that is the only score in the game (God save us from Big Ten football), the point differential was 0 for 900 seconds and +3 for the remaining 2700 seconds. The final point differential (Margin of Victory, or MoV) is +3 and the Game Script is +2.25.
Basically, gaining a lead early and maintaining it gives you a higher Game Script than keeping a game close and blowing it wide open at the end of the game.
Why is it useful?
Useful is perhaps too high a bar to clear, as Game Scripts have little predictive value for future games, but it's certainly interesting and descriptive. A comparison of the final point differentials and Game Scripts can, at a glance, show which teams pulled off big comeback victories (a positive margin of victory, but a negative game script, indicating the other team held the lead for much of the game), which teams dominated the whole game (high game script and high margin of victory), and which teams played tight games but pulled away at the end (a low game script, but a high margin of victory). If you’ve watched a particular game from beginning to end, it doesn’t help much, but it does provide a good summary for games you weren’t able to watch in full.
I should be more clear when I say Game Scripts have little predictive value. Game Scripts correlate very strongly (~.94) with the final Margin of Victory for the same game - this should not be surprising, as both rely directly on points scored, i.e. you establish a lead, you maintain a lead, you tend to finish the game with a similar lead.
Average Game Scripts for the season correlate weakly with your results for the next game (~.28), and only slightly stronger than the correlation for average Margin of Victory for the season to your results for your next game (~.26). Sample size issues abound here, as we're looking at a single season and a stat that is only recorded once per game.
How’d Michigan do in this stat?
Rather dismally, I’m afraid, which is why instead of a mid-season project with weekly updates, this turned into an offseason summary project. As you are no doubt aware, last season Michigan lost regularly and emphatically. The good news is that Game Scripts offer plenty of schadenfreude to go around!
Game Scripts for all 2014 Big Ten Teams (In- and Out-of-Conference Games)
Which teams won in the most dominant fashion in the Big Ten this year (defined as biggest average Game Scripts in wins)?
MSU and OSU are the clear leaders in this category, with MSU averaging a 16.5 point lead in all of their wins (which includes a big late comeback against Baylor dragging their average down) and OSU averaging a 13.8 point lead in all of their wins. As we knew, they both had impressive seasons (certainly their last or close to last, right guys? Because Harbaugh?).
Some surprising teams are featured in the next echelon of this category, with Indiana, Minnesota, Michigan, Nebraska, Northwestern, Wisconsin, Purdue, Maryland, and Rutgers all averaging between one and two touchdowns in their victories. This is where strength of schedule (i.e. wins over cupcakes) and sample size (Indiana has a big game script in their wins… of which they had three) make a big difference. Michigan, for example, averaged a lead of 10.1 points in our wins, but that is anchored mainly by big wins over App State, Miami of Ohio, and Indiana. Similarly, Indiana won big over Indiana State and UNT, and squeaked by Mizzou with a 4-point victory. On the other hand, Wisconsin was just plain dominant in most of their victories this year, with the lone exceptions being their 2-point win over Iowa and their 3-point win over Auburn.
The last category has some of the teams you’d expect, with Rutgers, Illinois, Iowa, and Penn State all averaging a less-than-one-touchdown lead in their wins. Illinois deserves its own what’s-the-room-below-the-basement category, as its average lead in its five wins was a rather terrible 2.7 points.
This year’s biggest comeback wins (defined as largest negative Game Script in a victory)
MSU had the biggest comeback of the year against Baylor, with an average point differential of -7.8 for the game, and a 1-point final margin of victory. The next five closest were
- Rutgers over Maryland (GS: -6.7, MoV: 3)
- Minnesota over Nebraska (GS: -5.2, MoV: 4)
- The thoroughly embarrassing Iowa over Ball St (GS: -5, MoV: 4)
- PSU over Rutgers (GS: -4.6, MoV: 4)
- The absolutely glorious Northwestern over Notre Dame (G: -4.3, MoV: 3).
Michigan’s lack of any significant games in this category fits the narrative of the 2014 season – a lack of hope that this team could win a game once it fell behind. The lone comeback for Michigan on the season was against PSU, with a Game Script of -0.6 and a final margin of 5.
This year’s biggest comeback losses (defined as largest positive Game Script in a loss)
Wisconsin choking away its lead over LSU takes the cake in this category, with a Game Script of 5.9 and a final margin of -4. Not surprisingly, this category also features a few teams that were on the opposite end of the games mentioned in the section above – Nebraska, Rutgers, and Maryland were on the less glamorous end of those big comebacks. A miserable loss we wouldn’t want to overlook, however, is Iowa’s three point loss to ISU, with a Game Script of 4.1. Michigan’s only comeback loss was to Maryland, with a final margin of -7 and a Game Script of 1.2.
The depressing loss you knew you should have turned off in the 1st half but probably didn’t (defined as largest negative Game Script in a loss)
While Michigan’s embarrassing loss at Notre Dame was certainly its worst loss in this category, the good news is that that game doesn’t even make the top ten most depressing loss by a Big Ten team! Wisconsin leads off this category with its 59-0 loss to OSU in the BTCG, featuring a Game Script of -31.8. Other OSU wins (over Illinois and Rutgers) round out the top three. Wisconsin is the only team to both deliver and sustain a top-ten loss in this category (Maryland’s 45 point loss to Wiscy, with a game script of -25.3, comes in fourth on this list).
The dominant victory that made you feel all warm and fuzzy about the future of your team (defined as largest positive Game Script in a win)
Cupcakes fill out the majority of this category, with OSU’s win over Kent St (GS: 40.2, MoV: 66), MSU’s win over EMU (GS: 38.4, MoV: 59), and Wisconsin’s win over BGSU (GS: 29, MoV: 51) all placing in the top five. Michigan’s win over App State qualifies with a Game Script of 24.9, but falls outside the top ten.
Which games were closer than they seemed? (Game Script between -3 and 3, with a two-score win or loss)
Only seven games fell into this category:
- Illinois vs Purdue (GS: 2.5, MoV: 11)
- Northwestern vs Nebraska (GS: 2.1, MoV: 21)
- OSU @ Navy (GS: 2, MoV: 17)
- Illinois vs YSU (GS: 1.6, MoV: 11)
- Minnesota vs Mizzou (GS: -0.8, MoV: -16)
- Wisconsin vs Minnesota (GS: -2.7, MoV: 10)
- Purdue vs Iowa (GS: 0.6, MoV: 14)
I think OSU @ Navy and Minn vs Mizzou are the most interesting games from this category – the first because it shows OSU as a bit more fallible than they looked in the final score, and the second because the eventual SEC East Champion almost lost to two Big Ten teams that weren’t particularly close to the top of their divisions.
What does it all mean?
In perhaps the most obvious conclusion ever made in the history of sports analysis, scoring more points early (and throughout the game) is better and leads to more winning. Allowing your oppononent to score more points than you do in the later parts of games occasionally leads to unexpected losses. Quote me as frequently as you wish, and send all royalties to me by check via USPS.
Beyond that, I think you can argue that MSU had the more dominant season than OSU, given how close the GS was for their game, and the number of OSU games that featured low GS but high MoV (Navy, MSU, Indiana, Michigan, Alabama). Whether that's good news or bad news is up to you.
Happy to hear your comments and feedback on this analysis! In particular, I’d love to hear:
- How awesome you think this is;
- Suggestions on how to incorporate pass/run ratios into some of the above analysis;
- Suggestions on visual representations of the analysis;
- New categories to include in future versions;
- How to figure out those lightboxes for my image links...
I’m planning on continuing this in the 2015 season, and perhaps even providing weekly updates. If you’re interested, you can view the full Game Scripts data for the 2014 Big Ten season here. And of course, I urge you to check out the Advanced Football Analytics site (recently acquired by ESPN), which does all sorts of awesome analysis of NFL games.
In a lot of ways I feel like this offseason has been a time machine. Almost all of the things we hated about Michigan football have been fixed, as if someone turned back the clock to the glory days. Of course, one thing is still missing: wins.
This wallpaper is meant to harken back those days. Hopefully the wins come too. Enjoy.
Photo credit to Bryan Fuller.
Fuller – MGoBlog
For all intents and purposes, last season was pretty much a disaster. Following the back-to-back upsets at the hands of NJIT and Eastern Michigan, the team went into free fall: starting with that first shocking upset (by what turned out to be a surprisingly adequate NJIT team), the Wolverines finished the year with a 10-15 record, recorded only one Top 50 win, and didn’t even make the NIT.
After the mercurial highs of a two-year run that will go down as one of Michigan’s best ever, this was a sobering crash back to earth. While the disappointment of the season was mitigated somewhat by a feisty group of underdogs who usually acquitted themselves well, even in defeat, against a brutal Big Ten schedule, the absence of the Wolverines’ star – preseason All-America Caris LeVert – loomed large.
Right or wrong, the focus usually falls on the star player when a team underachieves (or, in football, the quarterback is often credited with success or failure regardless of any other variables). Naturally, LeVert received plenty of blame for Michigan’s struggles before his injury, and even though there really aren’t very many useful data points – 18 games, some of which were against cupcakes – he really didn’t play too badly: 14.9 points, 3.7 assists, 4.9 rebounds, and 1.8 steals per game. That he had an offensive rating of 101.1 was disappointing in the context of his 111.7 number as a sophomore, though his usage jumped from 21.4% to 25.9%.
* * *
Two games before LeVert was sidelined for the season, I basically wrote a Leave Caris Alone post (and fully expected him to leave for the NBA at the time):
To state the obvious, this season has been a disappointment. Michigan’s customarily blistering offense has looked stagnant and has been prone to bouts of cold shooting; Kam Chatman hasn’t been able to fill Glenn Robinson’s vacancy at the four; Michigan’s corps of big men have been underwhelming as a whole (even if Ricky Doyle has shown good things); Spike Albrecht and Derrick Walton have been injured and Michigan’s struggled to get consistent production from the point guard spot.
In all fairness, Caris has contributed to the disappointment as well – although, notably, he still leads the team in points, rebounds, assists, and steals. Against NJIT, he put the team on his back to the tune of 32 points (on just 18 FGA) and Michigan still lost; but in other losses against Eastern Michigan, Arizona, SMU, and Purdue, he scored ten points or fewer, often inefficiently. It’s too reductive to place those losses squarely on Caris, but still, better performances (particularly against Eastern and SMU) might have made all the difference.
With what we know now, there were some little things from Caris that led to Michigan’s struggles. He too frequently locked in to one-on-one matchups and though he’s an elite isolation player, his ball-stopping tendencies were noticeable and detrimental. He shot far too much from the mid-range at a poor percentage (33%) as Michigan’s late shot clock offense far too frequently devolved into “Caris, go do something” and the something was often a tough shot off the dribble. It’s not easy to suss out blame for Michigan’s pick-and-roll struggles, but Caris wasn’t successful in what became Michigan’s bread-and-butter with Burke and Stauskas. Passivity was often a fair criticism, as LeVert shot the ball 12 or fewer times in six of Michigan’s seven losses. All of that’s fair, and it’s safe to say that we all expected more out of the Wolverines – and, by extension, LeVert – than what we saw.
[AFTER THE JUMP: nice(r) things!]