Beta_Rank: The negative sum of Offensive and Defensive Beta_Ranks. Defense is subtracted because very good defenses have negative Defensive Beta_Rank scores.
O_Score: The Offensive Beta_Rank score for a team. It is the sum of the teams scores on 4 measures of offensive performance, Drive Efficiency, Play Efficiency, Explosiveness, Avoiding Negative Drives.
D_Score: The Offensive Beta_Rank score for a team. It is the sum of the teams scores on 4 measures of offensive performance, Drive Efficiency, Play Efficiency, Explosiveness, Causing Negative Drives. Naturally for Defense the values are reversed.
Spcl_Tm_Score: The sum of offensive and defensive special teams regarding punts, punt retruns, punts inside the 20, kickoffs, and kick returns. Field Goals are included here, where I uses an expected points dependent variable subtracted from an actual points dependent variable.
Sched_Strength: The negative sum of Offensive and Defensive Schedule Strength divided by the number of games played. If you played a murder's row of Offenses your Offensive score would be very high, if you played a murder's row of Defenses you would have a very negative score. The sum of these scores is your total Sched_Strength. Takes into account where your games were played; home, road, neutral.
Record_Strength: The value of the games you actually won. This is just Schedule Strength for wins and without controlling for number of games played. If you win your conference championship game, this gives you an unweighted benefit. This can be a little confusing as a metric though because if your 6 wins mostly come against really bad teams, 2015 Arizona, you can have a worse Record_Strength than teams with one win, 2015 Oregon State. Beta_Rank looks a alot like a normal distribution with a whole lot of teams bunched around the middle and then fewer and fewer teams as you get exceptionally good or bad. If you rack up wins against the 70th ranked team and the 128th ranked team the hit to your score is not going to be linear since the scores are not linear. This metric really punishes teams that finish below .500 in conference play and top up their record with very bad non-conference opponents.
Drive_Efficiency: The team offensive and defensive residual in the model. This captures the point value left unexplained by the other components of the model (yards per play, explosive drives, negative drives, starting field position, special teams, home/away). In other words who still scores more points even when controlling for the other offensive factors.
Play_Efficiency: This is the effect of yards per play on all points on NCAA drives multiplied by the team specific yards per play controlling for opponent, starting field position, and home/away.
Explosiveness: This is the effect of a binary where yards per play >7.5 on all points on NCAA drives multiplied by the team offense and defense specific yards per play controlling for opponent, starting field position, and home/away. It corrects for multiple linear solutions to the yards per play to points relationship.
Negative Drives: This is the effect of a binary where yards per play < 3.3333 on all points on NCAA drives multiplied by the team offense and defense specific yards per play controlling for opponent, starting field position, and home/away. It corrects for multiple linear solutions to the yards per play to points relationship.
D-Plus Plays: the percentage of plays for an offense or a defense that resulted in a turnover, sack, QB hurry, tackle for loss, or pass breakup weighted by the unit's strength of schedule
3rd Down: the unit's success rate in gaining/preventing first downs on third down weighted by the unit's strength of schedule
O_Score: The Offensive Beta_Rank score for a team. It is the sum of the teams scores on 4 measures of offensive performance, Drive Efficiency, Play Efficiency, Explosiveness, Avoiding Negative Drives.
D_Score: The Offensive Beta_Rank score for a team. It is the sum of the teams scores on 4 measures of offensive performance, Drive Efficiency, Play Efficiency, Explosiveness, Causing Negative Drives. Naturally for Defense the values are reversed.
Spcl_Tm_Score: The sum of offensive and defensive special teams regarding punts, punt retruns, punts inside the 20, kickoffs, and kick returns. Field Goals are included here, where I uses an expected points dependent variable subtracted from an actual points dependent variable.
Sched_Strength: The negative sum of Offensive and Defensive Schedule Strength divided by the number of games played. If you played a murder's row of Offenses your Offensive score would be very high, if you played a murder's row of Defenses you would have a very negative score. The sum of these scores is your total Sched_Strength. Takes into account where your games were played; home, road, neutral.
Record_Strength: The value of the games you actually won. This is just Schedule Strength for wins and without controlling for number of games played. If you win your conference championship game, this gives you an unweighted benefit. This can be a little confusing as a metric though because if your 6 wins mostly come against really bad teams, 2015 Arizona, you can have a worse Record_Strength than teams with one win, 2015 Oregon State. Beta_Rank looks a alot like a normal distribution with a whole lot of teams bunched around the middle and then fewer and fewer teams as you get exceptionally good or bad. If you rack up wins against the 70th ranked team and the 128th ranked team the hit to your score is not going to be linear since the scores are not linear. This metric really punishes teams that finish below .500 in conference play and top up their record with very bad non-conference opponents.
Drive_Efficiency: The team offensive and defensive residual in the model. This captures the point value left unexplained by the other components of the model (yards per play, explosive drives, negative drives, starting field position, special teams, home/away). In other words who still scores more points even when controlling for the other offensive factors.
Play_Efficiency: This is the effect of yards per play on all points on NCAA drives multiplied by the team specific yards per play controlling for opponent, starting field position, and home/away.
Explosiveness: This is the effect of a binary where yards per play >7.5 on all points on NCAA drives multiplied by the team offense and defense specific yards per play controlling for opponent, starting field position, and home/away. It corrects for multiple linear solutions to the yards per play to points relationship.
Negative Drives: This is the effect of a binary where yards per play < 3.3333 on all points on NCAA drives multiplied by the team offense and defense specific yards per play controlling for opponent, starting field position, and home/away. It corrects for multiple linear solutions to the yards per play to points relationship.
D-Plus Plays: the percentage of plays for an offense or a defense that resulted in a turnover, sack, QB hurry, tackle for loss, or pass breakup weighted by the unit's strength of schedule
3rd Down: the unit's success rate in gaining/preventing first downs on third down weighted by the unit's strength of schedule
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