A few days ago Bill C looked into games states in college football:
As we all know, the score does change a team’s tactics. When a team is losing they must push forward and try to get the ball and keep possession. When a team is winning they are prone to sit deeper as defense become a priority.
Because there are so few scores in a given soccer match, your tactics will tend to shift dramatically if you’re up a goal, down a goal, up two, tied, etc. Obviously it’s a little bit different in college football — the average team scores around 27-28 points in a given game, so being up or down a single score probably won’t change much about your tactics, especially early on.
But those tactics do change at some point.
Out of pure curiosity, I pulled the average college football run rate by scoring margin and quarter from 2006 to present. At what point does play-calling begin to shift?
From this game state data, Bill looked at how run rates change depending on quarter and game state, as well as success rates by quarter and game state.
He found that teams typically run more often when they’re winning, especially later in the game, as well as some interesting baseline data for expected success rate in various situations, particularly for fourth quarter clock management.
Using Bill’s game state data I was able to do the same for Ohio State.
Run rates by game state
The first chart looks at run rates from the 2015 season up until the last game against Nebraska. The trend is obvious from the beginning: Ohio State runs more both when they’re winning and later in the game. Up by a single score in the first quarter, Ohio State runs 3.7% more. Up by a single score in the fourth quarter, Ohio State runs a whopping 18.2% more.
However, there are a few notable caveats:
- One of the big exceptions was if the Buckeyes started the second half with a big lead. Instead of running the ball, Ohio State looked like it would try to get some work in for the passing game — potentially with the second-team offense. If the Buckeyes were up by more than three scores in Q3, then they only ran the ball 54.3% of the time. But as you can see, if the Buckeyes found themselves up by more than three scores, the later the game went on, the more likely they were to run the ball, from 44.8% in Q2, up to 66.2% in Q4.
- Similarly, Q2 seems to be about getting a comfortable lead — or, if there already is a comfortable lead, then Ohio State felt comfortable throwing the ball more. If Ohio State was up by more than a score in Q2, then they were likely throwing the ball more than running: 46.2% up 9-14, 43.2% up 15-19, and 44.8% up by more than 20. Those run rates jump significantly in Q3 (though they were still more likely to pass the greater the lead in Q3).
- If Ohio State found themselves down by two scores in the first quarter, they generally stuck to the scripted game plan and didn’t try to pass more often to catch up — at least early on. The Q1 run rate down 9-14 points was 65% — actually more than if they were up 9-14 in Q1.
Another thing I looked at: the difference in run rates against top defenses. Ohio State has faced ten top-25 S&P+ defenses since the beginning of the 2015 season.
Here’s the 2016 season only:
The 2016 season was a little different than the full 2.5 years. In general, the first quarter was for running the ball, and the second quarter was for passing — unless the game was still tied.
Here’s 2017, up to the Nebraska game:
Obviously the sample sizes are much smaller with just 7 games to pull from.
Here things are a little different from 2016. Ohio State is much more often to throw the ball in the first quarter up by one or two scores: up 18.3% with a 1-8 point lead, and up 21.7% with a 9-14 point lead.
But like 2016, if Ohio State has more than a one score lead in Q2, then they’re likely to pass — 30.2% of the time up 9-14 (OSU has only run one pay with a 15-19 point lead in the second quarter, but it was a pass).
Due to small sample sizes: Ohio State has a big red upper-right corner, but they’ve only run a total of 18 Q4 plays while losing this season (to Oklahoma, obviously).
Speaking of Oklahoma, Ohio State really wanted to run the ball while the game was tied. Here are Ohio State’s run rates in the first through third quarters with the game tied: 54.6%, 60%, and 71.4%. The number of total plays per quarter were roughly the same, but Ohio State’s willingness to run increased significantly as the game went on — possibly because passing was ineffective and running was less risky: Ohio State’s rushing success rate was 53%, but the passing success rate was just 31% vs. Oklahoma.
Another interesting thing there: Ohio State’s RB:QB run ratio in the OU game was .89. Besides the 2015 Northern Illinois game where QBs only had two rushing attempts, their RB:QB run ratio since the beginning of the 2015 season has been 1.18 in losses or wins by only one score. In all other games, the RB:QB run ratio is 2.18.
Ohio State has run 195 second half plays with a lead by 20 or more points this season. Ohio State has run 274 total second half plays this year, meaning that about 71% of Ohio State’s second half plays have been with over a three score lead.
Success rates by game state
I also looked at success rates by game state.
The most interesting thing to me here is that that the Buckeyes have been poor in one-score games in the fourth quarter (plays in one-score games represent about 21% of all fourth quarter plays). Success rates range from just 23.3% down by one score in the fourth to 31.1% up by a score in the fourth.
Things get a little more comfortable when the Buckeyes are up by more than a single score in the fourth quarter. To me, the interesting question there is whether those poor success rates in Q4 are due to playing a talented opponent, or if it’s due to poor play calling in tight situations. Looking at the run rate data, Ohio State ran the ball 43.1% more with a tie in the fourth quarter compared to when they were losing by a score.
There’s not a ton you can take away from the 2017 success rate chart due to the limited data and because most of the data from Ohio State losing is limited to the Oklahoma game.
For example, Ohio State has only run 20 second half plays with a lead that was only 1-19 points, but 195 with a lead by over 20 points.
However, you can definitely see when the backups come in: with a Q4 lead by more than 20 points, the success rate drops from 55.9% in Q3 to 39.8% in Q4.
The most common game states for Ohio State in 2017, in order by most plays run are: Q4 lead up >20, Q3 lead up >20, Q2 lead up >20, tied in Q1, up by one score in Q1. Ohio State hasn’t run more than 27 plays (out of 548 total) in any other game state this season.