Everyone that's writes about college football will have a "Bold Predictions" moment this season. They pick a few darkhorses to win their conferences, another one to win the Heisman, claim something new that has never happened before will happen, and do it all to generate a little discussion and get attention.
I want to make predictions that will endure the test of time. I want predictions that are rational, reasonable and, perhaps to some, just plain boring. I, too, will be completely wrong, but at least I actually try to be right. So hold on to your seats - here we go.
Prediction #1: Jake Locker will complete 61% of his passes, throw for 3,200 yards, rush for 600 and be dropped from the Heisman discussion before mid-October. How can you foresee anything but modest improvement for a guy heading into his final college campaign? Even if the kid is heroic, with their schedule he'd have to be Herculean to win 8 games, and he's not a Heisman candidate if his team is floating around .500. On the other had, if UW skates in with 9 or 10 wins, Mr. Locker will take home more hardware than Michael Phelps.
Prediction #2: Garrett Gilbert will be just as successful as Colt McCoy in his first (and second) go as a Longhorn. This means 9-3 regular season, 5-3 in conference, and a relatively prestiguous, non-BCS bowl game. I think the world underestimated the contributions of 3rd rounders Jordan Shipley and Jamaal Charles to Colt's success, and the Texas D took some heavy losses in 2009 as well.
Prediction #3: Have you guys seen the helmets Virginia Tech was wearing in the early 70s? Talk about hideous. I predict that no team in college football has helmets so ugly. And the Hokies will reign over the ACC again. Deep competition in the Coastal just gives Beamer room for error.
Prediction #4: One team from Alabama will be conference champions. That is, the Other Men of Troy. I was going to go with MTSU for the Sunbelt crown until Dasher ran into some troubles with Big Brother. I also predict that all of 10 people will watch a Sunbelt conference game this season, and they will all be next-of-kin.
Prediction #5: Someone will win the MAC, and nobody will care. The same goes for the Pac-10.
Prediction #6: Michigan loses another home opener. Like the other home openers (App State and Utah) Michigan loses this one because the Wolverines are not actually very good at football. And Rich Rod keeps his job because the state of Michigan is economically on par with Zimbabwe right now.
Prediction #7: Alabama's Greg McElroy will get more Heisman love than teammate Mark Ingram. But they'll both get left out in the cold because . . . (see Prediction #8). Kellen Moore will run away with the Heisman if Boise can beat Virginia Tech (See Prediction #9). Landry Jones would be able to turn a Big 12 championship into more hardware except he decides to sport the 'stache. In the end, the Heisman goes to . . . (see Bonus Prediction).
Prediction #8: Florida wins the SEC. 'Bama will win Redneck Rumble III, but Florida will get revenge in the SEC championship game (RRIV). This will then cause the universe to implode (see Prediction #9).
Prediction #9: Boise State will . . . . not beat Virginia Tech. TCU will be the nation's only undefeated team, winning every game by 400 points. Both Florida and Alabama will claim a spot in the national championship game, and will have a legitimate argument. Oklahoma will be disqualified for the 'stache and the Pac-10 champion will be disqualified because they will officially become a professional franchise, trading places with the Raiders. The Big Ten champ will also have less claim to the title game than the SEC runner up (see Prediction #10).
Prediction #10: Ohio State will win the Big Ten. And Terrelle Pryor will again be quite pedestrian - because the guy has pedestrian talent. Sure he's fast, but he's not at all quick and he doesn't have good vision. Yes he can throw a spiral, but that's the only compliment I can bestow on his passing potential with a straight face. He seems like a good kid, but all hype. Ohio State loses two on its way to its last conference championship in Joe Pa's lifetime.
Bonus Prediction: The Heisman trophy goes to . . . .(Drumroll) . . . Dion Lewis. Pitt wins 10 games and the Big East. Lewis puts up huge numbers - and he's a sophomore, which has been Heisman gold recently.
BPR | A system for ranking teams based only one wins and losses and strength of schedule. See BPR for an explanation. |
EPA (Expected Points Added) | Expected points are the points a team can "expect" to score based on the distance to the end zone and down and distance needed for a first down, with an adjustment for the amount of time remaining in some situations. Expected points for every situation is estimated using seven years of historical data. The expected points considers both the average points the offense scores in each scenario and the average number of points the other team scores on their ensuing possession. The Expected Points Added is the change in expected points before and after a play. |
EP3 (Effective Points Per Possession) | Effective Points Per Possession is based on the same logic as the EPA, except it focuses on the expected points added at the beginning and end of an offensive drive. In other words, the EP3 for a single drive is equal to the sum of the expected points added for every offensive play in a drive (EP3 does not include punts and field goal attempts). We can also think of the EP3 as points scored+expected points from a field goal+the value of field position change on the opponent's next possession. |
Adjusted for Competition | We attempt to adjust some statistics to compensate for differences in strength of schedule. While the exact approach varies some from stat to stat the basic concept is the same. We use an algorithm to estimate scores for all teams on both sides of the ball (e.g., offense and defense) that best predict real results. For example, we give every team an offensive and defensive yards per carry score. Subtracting the offensive score from the defensive score for two opposing teams will estimate the yards per carry if the two teams were to play. Generally, the defensive scores average to zero while offensive scores average to the national average, e.g., yards per carry, so we call the offensive score "adjusted for competition" and roughly reflects what the team would do against average competition |
Impact | see Adjusted for Competition. Impact scores are generally used to evaluate defenses. The value roughly reflects how much better or worse a team can expect to do against this opponent than against the average opponent. |
[-] About this table
Includes the
top 180 QBs by total plays
Total <=0 | Percent of plays that are negative or no gain |
Total >=10 | Percent of plays that gain 10 or more yards |
Total >=25 | Percent of plays that gain 25 or more yards |
10 to 0 | Ratio of Total >=10 to Total <=0 |
Includes the
top 240 RBs by total plays
Total <=0 | Percent of plays that are negative or no gain |
Total >=10 | Percent of plays that gain 10 or more yards |
Total >=25 | Percent of plays that gain 25 or more yards |
10 to 0 | Ratio of Total >=10 to Total <=0 |
Includes the
top 300 Receivers by total plays
Total <=0 | Percent of plays that are negative or no gain |
Total >=10 | Percent of plays that gain 10 or more yards |
Total >=25 | Percent of plays that gain 25 or more yards |
10 to 0 | Ratio of Total >=10 to Total <=0 |
Includes
the
top 180 players by pass attempts)
3rdLComp% |
Completion % on 3rd and long (7+
yards) |
SitComp% |
Standardized completion % for
down and distance. Completion % by down and distance are weighted by
the national average of pass plays by down and distance. |
Pass <=0 | Percent of pass plays that are negative or no gain |
Pass >=10 | Percent of pass plays that gain 10 or more yards |
Pass >=25 | Percent of pass plays that gain 25 or more yards |
10 to 0 | Ratio of Pass >=10 to Pass<=0 |
%Sacks |
Ratio of sacks to pass plays |
Bad INTs |
Interceptions on 1st or 2nd down
early before the last minute of the half |
Includes the top 240 players by carries
YPC1stD |
Yards per carry on 1st down |
CPCs |
Conversions (1st down/TD) per
carry in short yardage situations - the team 3 or fewer yards for a 1st
down or touchdown |
%Team Run |
Player's carries as a percent of team's carries |
%Team RunS |
Player's carries as a percent of team's carries in short
yardage situations |
Run <=0 |
Percent of running plays that
are negative or no gain |
Run >=10 |
Percent of running plays that
gain 10 or more yards |
Run >=25 | Percent of running plays that gain 25 or more yards |
10 to 0 | Ratio of Run >=10 to Run <=0 |
Includes the top 300 players by targets
Conv/T 3rd | Conversions per target on 3rd Downs |
Conv/T PZ | Touchdowns per target inside the 10 yardline |
%Team PZ | Percent of team's targets inside the 10 yardline |
Rec <=0 | Percent of targets that go for negative yards or no net gain |
Rec >=10 | Percent of targets that go for 10+ yards |
Rec >=25 | Percent of targets that go for 25+ yards |
10 to 0 | Ratio of Rec>=0 to Rec<=0 |
Includes the top 300 players by targets
xxxx | xxxx |
...
Includes players with a significant number of attempts
NEPA | "Net Expected Points Added": (expected points after play - expected points before play)-(opponent's expected points after play - opponent's expected points before play). Uses the expected points for the current possession and the opponent's next possession based on down, distance and spot |
NEPA/PP | Average NEPA per play |
Max/Min | Single game high and low |
Includes players with a significant number of attempts
NEPA | "Net Expected Points Added": (expected points after play - expected points before play)-(opponent's expected points after play - opponent's expected points before play). Uses the expected points for the current possession and the opponent's next possession based on down, distance and spot |
NEPA/PP | Average NEPA per play |
Max/Min | Single game high and low |
Adjusted | Reports the per game EPA adjusted for the strength of schedule. |
Defensive Possession Stats
Points/Poss | Offensive points per possession |
EP3 | Effective Points per Possession |
EP3+ | Effective Points per Possession impact |
Plays/Poss | Plays per possession |
Yards/Poss | Yards per possession |
Start Spot | Average starting field position |
Time of Poss | Average time of possession (in seconds) |
TD/Poss | Touchdowns per possession |
TO/Poss | Turnovers per possession |
FGA/Poss | Attempted field goals per possession |
%RZ | Red zone trips per possession |
Points/RZ | Average points per red zone trip. Field Goals are included using expected points, not actual points. |
TD/RZ | Touchdowns per red zone trip |
FGA/RZ | Field goal attempt per red zone trip |
Downs/RZ | Turnover on downs per red zone trip |
Defensive Play-by-Play Stats
EPA/Pass | Expected Points Added per pass attempt |
EPA/Rush | Expected Points Added per rush attempt |
EPA/Pass+ | Expected Points Added per pass attempt impact |
EPA/Rush+ | Expected Points Added per rush attempt impact |
Yards/Pass | Yards per pass |
Yards/Rush | Yards per rush |
Yards/Pass+ | Yards per pass impact |
Yards/Rush+ | Yards per rush impact |
Exp/Pass | Explosive plays (25+ yards) per pass |
Exp/Rush | Explosive plays (25+ yards) per rush |
Exp/Pass+ | Explosive plays (25+ yards) per pass impact |
Exp/Rush+ | Explosive plays (25+ yards) per rush impact |
Comp% | Completion percentage |
Comp%+ | Completion percentage impact |
Yards/Comp | Yards per completion |
Sack/Pass | Sacks per pass |
Sack/Pass+ | Sacks per pass impact |
Sack/Pass* | Sacks per pass on passing downs |
INT/Pass | Interceptions per pass |
Neg/Rush | Negative plays (<=0) per rush |
Neg/Run+ | Negative plays (<=0) per rush impact |
Run Short | % Runs in short yardage situations |
Convert% | 3rd/4th down conversions |
Conv%* | 3rd/4th down conversions versus average by distance |
Conv%+ | 3rd/4th down conversions versus average by distance impact |
Offensive Play-by-Play Stats
Plays | Number of offensive plays |
%Pass | Percent pass plays |
EPA/Pass | Expected Points Added per pass attempt |
EPA/Rush | Expected Points Added per rush attempt |
EPA/Pass+ | Expected Points Added per pass attempt adjusted for competition |
EPA/Rush+ | Expected Points Added per rush attempt adjusted for competition |
Yards/Pass | Yards per pass |
Yards/Rush | Yards per rush |
Yards/Pass+ | Yards per pass adjusted for competition |
Yards/Rush+ | Yards per rush adjusted for competition |
Exp Pass | Explosive plays (25+ yards) per pass |
Exp Run | Explosive plays (25+ yards) per rush |
Exp Pass+ | Explosive plays (25+ yards) per pass adjusted for competition |
Exp Run+ | Explosive plays (25+ yards) per rush adjusted for competition |
Comp% | Completion percentage |
Comp%+ | Completion percentage adjusted for competition |
Sack/Pass | Sacks per pass |
Sack/Pass+ | Sacks per pass adjusted for competition |
Sack/Pass* | Sacks per pass on passing downs |
Int/Pass | Interceptions per pass |
Neg/Run | Negative plays (<=0) per rush |
Neg/Run+ | Negative plays (<=0) per rush adjusted for competition |
Run Short | % Runs in short yardage situations |
Convert% | 3rd/4th down conversions |
Conv%* | 3rd/4th down conversions versus average by distance |
Conv%+ | 3rd/4th down conversions versus average by distance adjusted for competition |
Offensive Possession Stats
Points/Poss | Offensive points per possession |
EP3 | Effective Points per Possession |
EP3+ | Effective Points per Possession adjusted for competition |
Plays/Poss | Plays per possession |
Yards/Poss | Yards per possession |
Start Spot | Average starting field position |
Time of Poss | Average time of possession (in seconds) |
TD/Poss | Touchdowns per possession |
TO/Poss | Turnovers per possession |
FGA/Poss | Attempted field goals per possession |
Poss/Game | Possessions per game |
%RZ | Red zone trips per possession |
Points/RZ | Average points per red zone trip. Field Goals are included using expected points, not actual points. |
TD/RZ | Touchdowns per red zone trip |
FGA/RZ | Field goal attempt per red zone trip |
Downs/RZ | Turnover on downs per red zone trip |
PPP | Points per Possession |
aPPP | Points per Possession allowed |
PPE | Points per Exchange (PPP-aPPP) |
EP3+ | Expected Points per Possession |
aEP3+ | Expected Points per Possession allowed |
EP2E+ | Expected Points per Exchange |
EPA/Pass+ | Expected Points Added per Pass |
EPA/Rush+ | Expected Points Added per Rush |
aEPA/Pass+ | Expected Points Allowed per Pass |
aEPA/Rush+ | Expected Points Allowed per Rush |
Exp/Pass | Explosive Plays per Pass |
Exp/Rush | Explosive Plays per Rush |
aExp/Pass | Explosive Plays per Pass allowed |
aExp/Rush | Explosive Plays per Rush allowed |
BPR | A method for ranking conferences based only on their wins and losses and the strength of schedule. See BPR for an explanation. |
Power | A composite measure that is the best predictor of future game outcomes, averaged across all teams in the conference |
P-Top | The power ranking of the top teams in the conference |
P-Mid | The power ranking of the middling teams in the conference |
P-Bot | The power ranking of the worst teams in the conference |
SOS-Und | Strength of Schedule - Undefeated. Focuses on the difficulty of going undefeated, averaged across teams in the conference |
SOS-BE | Strength of Schedule - Bowl Eligible. Focuses on the difficulty of becoming bowl eligible, averaged across teams in the conference |
Hybrid | A composite measure that quantifies human polls, applied to converences |
Player Game Log
Use the yellow, red and green cells to filter values. Yellow cells filter for exact matches, green cells for greater values and red cells for lesser values. By default, the table is filtered to only the top 200 defense-independent performances (oEPA). The table includes the 5,000 most important performances (positive and negative) by EPA.
Use the yellow, red and green cells to filter values. Yellow cells filter for exact matches, green cells for greater values and red cells for lesser values. By default, the table is filtered to only the top 200 defense-independent performances (oEPA). The table includes the 5,000 most important performances (positive and negative) by EPA.
EPA | Expected points added (see glossary) |
oEPA | Defense-independent performance |
Team Game Log
Use the yellow, red and green cells to filter values. Yellow cells filter for exact matches, green cells for greater values and red cells for lesser values.
Use the yellow, red and green cells to filter values. Yellow cells filter for exact matches, green cells for greater values and red cells for lesser values.
EP3 | Effective points per possession (see glossary) |
oEP3 | Defense-independent offensive performance |
dEP3 | Offense-independent defensive performance |
EPA | Expected points added (see glossary) |
oEPA | Defense-independent offensive performance |
dEPA | Offense-independent defensive performance |
EPAp | Expected points added per play |
Tuesday, August 31, 2010
Monday, August 30, 2010
Distance Matters - Travel and HFA
In recent posts, I've shown that crowd size doesn't matter in home field advantage, and I've traveled around college football conferences to show that the teams with the large, historic stadiums are not the ones that enjoy the best home field advantage. In fact, the award for best home field advantage in the country probably goes to Texas Tech's Jones Stadium. Arizona St. got +10 points in the Pac-10 playing at home versus on the road, and Indiana got +9 in the Big Ten.
But if crowd size doesn't matter, why do home teams tend to play better? One answer is travel. Distance makes the heart grow fonder, the legs weaker, the body dehydrated, the sleep patterns disrupted, the equipment misplaced or forgotten, the preparation time cut short, the players distracted, and the visiting teams loser. And I can prove it.
Using game results from 2006 to 2009, we can measure the effect of travel on performance. The first model below uses basic linear regression. We use three variables - DOffense, DDefense and Distance. DOffense and DDefense measure how good the road team's offense and defense are compared to the home team's. Distance is the distance traveled in thousands of miles.
The "Coef." for DOffense and DDefense are about 1. This makes sense. A team that is 1 point better than its opponent on offense or defense will win, on average, by 1 point. If it is 14 points better on offense and 28 points better on defense it will win, on average, by 42 points (28+14=42).
For every 1,000 miles a team travels, it loses 1.68 points. So, when Georgia Tech travels 600 miles to play Miami, it loses a point, but gains a point when the U comes calling. That might not seem like much, but about one out of every 13 games, or almost one game a season for the average team, is decided by 2 points or less - the price in points a team pays for traveling 600 miles instead of receiving a team from 600 miles away.
We then add the "_cons", or the home field advantage not explained by distance, and consider the average distance traveled for a game is about 500 miles, to get a net average home field advantage just under 1/2 a touchdown.
The logistic regression measures the effect of these variables on the probability that the road team will win. An "Odds Ratio" greater than 1 means that, as that variable increases, the odds of winning increase. If the Odds Ratio is less than 1, as that variable increases, the odds of winning decrease. Therefore, being 1 point better increases a team's odds by 1.13 and 1.15 for offense and defense, respectively. Traveling 1,000 miles decreases a team's odds of winning by more than a quarter (.694). So, for example, if Duke and North Carolina were evenly matched when UNC traveled to Duke (odds of UNC win = 1 to 2), the odds of a UNC victory drop to .818 to 2 if they had to travel 1,000 miles for that same game. In this scenario, 1 out or every 5 games is determined by travel.
What does this amount to? About 1 game in every 11 games has a different outcome because of where the game was played. 38% of that influence is a product of the distance that teams travel to play their road games. That, to me, is a pretty big deal.
But if crowd size doesn't matter, why do home teams tend to play better? One answer is travel. Distance makes the heart grow fonder, the legs weaker, the body dehydrated, the sleep patterns disrupted, the equipment misplaced or forgotten, the preparation time cut short, the players distracted, and the visiting teams loser. And I can prove it.
Using game results from 2006 to 2009, we can measure the effect of travel on performance. The first model below uses basic linear regression. We use three variables - DOffense, DDefense and Distance. DOffense and DDefense measure how good the road team's offense and defense are compared to the home team's. Distance is the distance traveled in thousands of miles.
The "Coef." for DOffense and DDefense are about 1. This makes sense. A team that is 1 point better than its opponent on offense or defense will win, on average, by 1 point. If it is 14 points better on offense and 28 points better on defense it will win, on average, by 42 points (28+14=42).
For every 1,000 miles a team travels, it loses 1.68 points. So, when Georgia Tech travels 600 miles to play Miami, it loses a point, but gains a point when the U comes calling. That might not seem like much, but about one out of every 13 games, or almost one game a season for the average team, is decided by 2 points or less - the price in points a team pays for traveling 600 miles instead of receiving a team from 600 miles away.
We then add the "_cons", or the home field advantage not explained by distance, and consider the average distance traveled for a game is about 500 miles, to get a net average home field advantage just under 1/2 a touchdown.
The logistic regression measures the effect of these variables on the probability that the road team will win. An "Odds Ratio" greater than 1 means that, as that variable increases, the odds of winning increase. If the Odds Ratio is less than 1, as that variable increases, the odds of winning decrease. Therefore, being 1 point better increases a team's odds by 1.13 and 1.15 for offense and defense, respectively. Traveling 1,000 miles decreases a team's odds of winning by more than a quarter (.694). So, for example, if Duke and North Carolina were evenly matched when UNC traveled to Duke (odds of UNC win = 1 to 2), the odds of a UNC victory drop to .818 to 2 if they had to travel 1,000 miles for that same game. In this scenario, 1 out or every 5 games is determined by travel.
What does this amount to? About 1 game in every 11 games has a different outcome because of where the game was played. 38% of that influence is a product of the distance that teams travel to play their road games. That, to me, is a pretty big deal.
Friday, August 27, 2010
Toughest Places to Play: Big Ten
No conference in the country has bigger stadiums than the Big Ten and, if we exclude Northwestern's diminutive and sparsely population Ryan Field, the Big Ten tops all conferences in average attendance. (Otherwise, the SEC averages about 5,000 more in attendance per game.)
But even in the Big Ten, where average attendance ranges from over 100,000 to less than 30,000, more fans in the stands doesn't seem to help teams win. In conference games since 1994, home teams in the Big Ten have won 56.8% of conference games and have been about one touchdown better per game. Ohio St. has won 81% of their home games in this stretch, but this has little to do with a home field advantage - the Buckeyes also won 75% of road games. The Buckeyes were 6.25 points better at home than on the road, meaning the Buckeyes enjoyed less of a home field advantage than the conference average. Michigan, college football's attendance leader, got less of a boost at home - only 5.42 points per game.
The toughest place to play in the Big Ten has been Indiana's Memorial Stadium, capacity 52,000. The Hoosiers have been 9 points better and 2.5 times more likely to win at home. On the other hand, Illinois has seen no advantage to playing in their own Memorial Stadium (62,000 capacity). Illinois team's since 1994 have been 2.27 points better at home than on the road, but they actually have won more road games than home games in that period.
But even in the Big Ten, where average attendance ranges from over 100,000 to less than 30,000, more fans in the stands doesn't seem to help teams win. In conference games since 1994, home teams in the Big Ten have won 56.8% of conference games and have been about one touchdown better per game. Ohio St. has won 81% of their home games in this stretch, but this has little to do with a home field advantage - the Buckeyes also won 75% of road games. The Buckeyes were 6.25 points better at home than on the road, meaning the Buckeyes enjoyed less of a home field advantage than the conference average. Michigan, college football's attendance leader, got less of a boost at home - only 5.42 points per game.
The toughest place to play in the Big Ten has been Indiana's Memorial Stadium, capacity 52,000. The Hoosiers have been 9 points better and 2.5 times more likely to win at home. On the other hand, Illinois has seen no advantage to playing in their own Memorial Stadium (62,000 capacity). Illinois team's since 1994 have been 2.27 points better at home than on the road, but they actually have won more road games than home games in that period.
Thursday, August 26, 2010
Boise St vs. Virginia Tech
More information will be available in the expected box score as the season progresses.
Click Here to see a complete expected box score
Click here for an explanation
Click Here to see a complete expected box score
Click here for an explanation
America Wants a non-AQ Champion
Tweet
Dear BCS ranking gods,
Brevity is the soul of wit, so I'll be brief. Americans want to see Boise St. or TCU in the national championship game this year. And I don't mean a few Americans. I mean all Americans. Every single resident of this country (except Colin Cowherd).
Let me demonstrate.
1) Boise St. and TCU - true by definition
2) WAC and MWC - That which is good for one is good for all. Attention, exposure, revenue, and new opportunities. C-USA, MAC, Sunbelt have less to gain, but nothing to lose.
3) Alabama, Florida, Texas, OU, Ohio St. - The contenders want to see Boise St or TCU in the title game as well. Think about it. If you could choose the WAC champ or SEC champ, which would you want to see in January?
4) The rest of the BCS - If you're not going to be playing in January, don't you want Boise to get in, get stomped, and put the debate to rest? Get Orin Hatch off your back a little? Nothing was sweeter for the Cowherd's of the world than watching Georgia slam Hawaii in 2007.
5) Everyone else - Independents love Boise. The blue turf. Ian Johnson scoring on the Statue of Liberty and with the cheerleader. They mistakingly see Boise as the Pistol Pete of college football. And this isn't just my opinion. According to a recent ESPN poll, about half the country would prefer Boise St win the championship over any of the top-ranked traditional powers. Not just play for the championship, but actually win it all.
6) The media - Boise or TCU would draw huge ratings and interest. They don't have huge individual followings. They are more like the bearded lady - I'm not a fan in any sense, but you know I'm going to look.
Of course, TCU and Boise have to get the job done on the field. But one of the two will be undefeated 12 games from now, and when that happens, I hope you're ready to bestow your divine benevolence upon these lowly programs.
Sincerely,
Me
Dear BCS ranking gods,
Brevity is the soul of wit, so I'll be brief. Americans want to see Boise St. or TCU in the national championship game this year. And I don't mean a few Americans. I mean all Americans. Every single resident of this country (except Colin Cowherd).
Let me demonstrate.
1) Boise St. and TCU - true by definition
2) WAC and MWC - That which is good for one is good for all. Attention, exposure, revenue, and new opportunities. C-USA, MAC, Sunbelt have less to gain, but nothing to lose.
3) Alabama, Florida, Texas, OU, Ohio St. - The contenders want to see Boise St or TCU in the title game as well. Think about it. If you could choose the WAC champ or SEC champ, which would you want to see in January?
4) The rest of the BCS - If you're not going to be playing in January, don't you want Boise to get in, get stomped, and put the debate to rest? Get Orin Hatch off your back a little? Nothing was sweeter for the Cowherd's of the world than watching Georgia slam Hawaii in 2007.
5) Everyone else - Independents love Boise. The blue turf. Ian Johnson scoring on the Statue of Liberty and with the cheerleader. They mistakingly see Boise as the Pistol Pete of college football. And this isn't just my opinion. According to a recent ESPN poll, about half the country would prefer Boise St win the championship over any of the top-ranked traditional powers. Not just play for the championship, but actually win it all.
6) The media - Boise or TCU would draw huge ratings and interest. They don't have huge individual followings. They are more like the bearded lady - I'm not a fan in any sense, but you know I'm going to look.
Of course, TCU and Boise have to get the job done on the field. But one of the two will be undefeated 12 games from now, and when that happens, I hope you're ready to bestow your divine benevolence upon these lowly programs.
Sincerely,
Me
America Wants a non-AQ Champion
Tweet
Dear BCS ranking gods,
Brevity is the soul of wit, so I'll be brief. Americans want to see Boise St. or TCU in the national championship game this year. And I don't mean a few Americans. I mean all Americans. Every single resident of this country (except Colin Cowherd).
Let me demonstrate.
1) Boise St. and TCU - true by definition
2) WAC and MWC - That which is good for one is good for all. Attention, exposure, revenue, and new opportunities. C-USA, MAC, Sunbelt have less to gain, but nothing to lose.
3) Alabama, Florida, Texas, OU, Ohio St. - The contenders want to see Boise St or TCU in the title game as well. Think about it. If you could choose the WAC champ or SEC champ, which would you want to see in January?
4) The rest of the BCS - If you're not going to be playing in January, don't you want Boise to get in, get stomped, and put the debate to rest? Get Orin Hatch off your back a little? Nothing was sweeter for the Cowherd's of the world than watching Georgia slam Hawaii in 2007.
5) Everyone else - Independents love Boise. The blue turf. Ian Johnson scoring on the Statue of Liberty and then with the cheerleader. They mistakingly see Boise as the Pistol Pete of college football. And this isn't just my opinion. According to a recent ESPN poll, about half the country would prefer Boise St win the championship over any of the top-ranked traditional powers. Not just play for the championship, but actually win it all.
6) The media - Boise or TCU would draw huge ratings and interest. They don't have huge individual followings. They are more like the bearded lady - I'm not a fan in any sense, but you know I'm going to look.
Of course, TCU and Boise have to get the job done on the field. But one of the two will be undefeated 12 games from now, and when that happens, I hope you're ready to bestow your divine benevolence upon these lowly programs.
Sincerely,
Me
Dear BCS ranking gods,
Brevity is the soul of wit, so I'll be brief. Americans want to see Boise St. or TCU in the national championship game this year. And I don't mean a few Americans. I mean all Americans. Every single resident of this country (except Colin Cowherd).
Let me demonstrate.
1) Boise St. and TCU - true by definition
2) WAC and MWC - That which is good for one is good for all. Attention, exposure, revenue, and new opportunities. C-USA, MAC, Sunbelt have less to gain, but nothing to lose.
3) Alabama, Florida, Texas, OU, Ohio St. - The contenders want to see Boise St or TCU in the title game as well. Think about it. If you could choose the WAC champ or SEC champ, which would you want to see in January?
4) The rest of the BCS - If you're not going to be playing in January, don't you want Boise to get in, get stomped, and put the debate to rest? Get Orin Hatch off your back a little? Nothing was sweeter for the Cowherd's of the world than watching Georgia slam Hawaii in 2007.
5) Everyone else - Independents love Boise. The blue turf. Ian Johnson scoring on the Statue of Liberty and then with the cheerleader. They mistakingly see Boise as the Pistol Pete of college football. And this isn't just my opinion. According to a recent ESPN poll, about half the country would prefer Boise St win the championship over any of the top-ranked traditional powers. Not just play for the championship, but actually win it all.
6) The media - Boise or TCU would draw huge ratings and interest. They don't have huge individual followings. They are more like the bearded lady - I'm not a fan in any sense, but you know I'm going to look.
Of course, TCU and Boise have to get the job done on the field. But one of the two will be undefeated 12 games from now, and when that happens, I hope you're ready to bestow your divine benevolence upon these lowly programs.
Sincerely,
Me
Wednesday, August 25, 2010
SMU vs. Texas Tech
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Southern Miss. vs. South Carolina
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Texas vs. Rice
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Pitt vs. Utah
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TCU vs. Oregon St.
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Utah St. vs. Oklahoma
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Washington St. vs. Oklahoma St.
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