Rate of Moving the Chains – Wild Card Round

What is this? This is rate of moving the chains, which is my primary statistic for handicapping games. It holds the assumption that the goal of any team on any given 1st and 10 (or 1st and goal) is to move the chains (or score). In order to figure out how often teams meet that goal, I take first downs plus touchdowns and divide it by first downs plus touchdowns plus failures to move the chains (successes divided by attempts). Failures to move the chains include punts, turnovers, failed 4th downs, and field goal attempts (being forced to kick a field goal is a failure). I have this sorted by percent for (to evaluate offenses), percent against (to evaluate defenses), and differentials (to evaluate teams).

Offense

First Downs Touchdowns Field Goals Punts Turnovers Failed 4ths Safeties
1 GB 356 52 33 51 13 6 3 79.38%
2 NO 395 49 22 58 30 7 0 79.14%
3 PIT 379 43 32 62 21 5 0 77.86%
4 DAL 342 53 29 58 25 3 1 77.30%
5 DEN 360 55 29 69 20 7 0 76.85%
6 NE 361 47 37 67 13 6 0 76.84%
7 BAL 345 43 34 60 20 9 0 75.93%
8 MIA 361 39 37 59 23 12 0 75.33%
9 SEA 328 40 37 62 14 8 1 75.10%
10 IND 371 51 31 69 31 9 1 74.96%
11 ATL 330 39 32 67 23 8 1 73.80%
12 CAR 347 33 35 74 23 4 0 73.64%
13 SD 326 37 26 75 23 6 0 73.63%
14 KC 309 36 30 71 17 7 1 73.25%
15 CHI 322 38 16 72 29 15 0 73.17%
16 PHI 356 43 36 76 36 4 0 72.41%
17 NYG 336 43 26 81 28 11 0 72.19%
18 CIN 313 39 33 73 26 6 0 71.84%
19 DET 310 33 38 68 20 10 1 71.46%
20 SF 303 30 31 73 22 8 0 71.31%
21 WAS 318 33 27 78 31 12 0 70.34%
22 HOU 313 34 35 84 22 7 1 69.96%
23 ARZ 302 27 33 92 17 1 0 69.70%
24 MIN 288 29 35 76 20 6 2 69.52%
25 STL 288 31 30 81 27 6 0 68.90%
26 NYJ 289 27 39 79 24 7 1 67.81%
27 CLE 294 29 32 93 23 9 0 67.29%
28 TB 263 28 24 79 33 8 2 66.59%
29 BUF 273 30 38 86 23 8 2 65.87%
30 TEN 258 26 22 89 26 11 2 65.44%
31 JAX 271 24 26 96 26 12 2 64.55%
32 OAK 248 26 22 109 29 6 0 62.27%

 

Defense

First Downs Touchdowns Field Goals Punts Turnovers Failed 4ths Safeties
1 BUF 302 26 37 88 30 6 1 66.94%
2 SEA 277 25 24 83 24 6 1 68.64%
3 ARZ 300 31 32 78 25 8 0 69.83%
4 DEN 311 38 28 88 25 7 1 70.08%
5 STL 301 30 29 76 25 10 0 70.28%
6 IND 309 41 19 90 26 13 0 70.28%
7 KC 310 26 37 78 14 13 0 70.29%
8 BAL 311 30 36 76 22 9 1 70.31%
9 DET 310 31 23 82 27 9 1 70.60%
10 HOU 329 34 22 83 34 11 1 70.62%
11 CLE 348 35 34 86 29 7 1 70.93%
12 PHI 338 44 27 91 28 9 0 71.14%
13 NE 329 30 37 65 25 15 0 71.66%
14 CIN 337 34 32 75 26 9 3 71.90%
15 NYJ 300 41 32 81 13 4 1 72.25%
16 OAK 320 46 38 83 14 5 0 72.33%
17 SD 307 35 34 69 18 8 1 72.46%
18 CAR 309 39 28 72 26 6 0 72.50%
19 MIA 309 40 34 61 25 9 3 72.56%
20 SF 308 36 20 74 29 7 0 72.57%
21 NYG 326 40 31 75 26 6 0 72.62%
22 JAX 330 39 35 75 20 6 1 72.92%
23 MIN 321 36 31 76 19 5 0 73.16%
24 WAS 307 46 26 80 19 4 0 73.24%
25 PIT 314 39 32 68 21 4 1 73.70%
26 DAL 315 40 18 67 31 10 0 73.80%
27 GB 339 37 24 62 27 13 1 74.75%
28 TEN 357 45 39 73 16 6 1 74.86%
29 TB 353 43 39 64 25 4 0 75.00%
30 CHI 325 46 39 49 24 7 0 75.71%
31 ATL 358 41 38 56 28 4 0 76.00%
32 NO 345 43 32 63 17 4 2 76.68%

 

Differential

1 DEN 6.77%
2 SEA 6.47%
3 BAL 5.62%
4 NE 5.18%
5 IND 4.67%
6 GB 4.63%
7 PIT 4.16%
8 DAL 3.49%
9 KC 2.96%
10 MIA 2.77%
11 NO 2.46%
12 PHI 1.28%
13 SD 1.17%
14 CAR 1.14%
15 DET 0.86%
16 CIN -0.06%
17 ARZ -0.13%
18 NYG -0.43%
19 HOU -0.66%
20 BUF -1.07%
21 SF -1.27%
22 STL -1.38%
23 ATL -2.20%
24 CHI -2.54%
25 WAS -2.90%
26 CLE -3.63%
27 MIN -3.64%
28 NYJ -4.43%
29 JAX -8.37%
30 TB -8.41%
31 TEN -9.42%
32 OAK -10.06%

 

Playoff Team Differential

1 DEN 6.77%
2 SEA 6.47%
3 BAL 5.62%
4 NE 5.18%
5 IND 4.67%
6 GB 4.63%
7 PIT 4.16%
8 DAL 3.49%
9 CAR 1.14%
10 DET 0.86%
11 CIN -0.06%
12 ARZ -0.13%

 

One thing I did differently this week is I calculated rate of moving the chains differential for the playoff teams adjusted for strength of schedule. I took the combined rate of moving the chains differential of each playoff team’s 16 opponents and compared it with the playoff team’s differential to figure out what portion of a team’s success and failure can be attributed to their schedule to give us a differential over average. I also did the same with offenses and defenses.

Playoff Team Schedule Adjusted Differential

1 DEN 6.92%
2 SEA 6.78%
3 NE 5.40%
4 BAL 4.94%
5 GB 4.32%
6 IND 3.87%
7 PIT 3.24%
8 DAL 2.77%
9 CAR 1.16%
10 DET 0.56%
11 ARZ 0.49%
12 CIN 0.48%

 

Playoff Team Schedule Adjusted Offense

1 GB 6.68%
2 DEN 5.77%
3 PIT 5.47%
4 NE 5.27%
5 DAL 4.99%
6 SEA 3.31%
7 BAL 3.00%
8 IND 2.69%
9 CAR 0.08%
10 CIN -0.71%
11 DET -1.91%
12 ARZ -1.95%

 

Playoff Team Schedule Adjusted Defense

1 SEA 3.48%
2 DET 2.47%
3 ARZ 2.44%
4 BAL 1.94%
5 CIN 1.19%
6 IND 1.18%
7 DEN 1.15%
8 CAR 1.08%
9 NE 0.12%
10 DAL -2.22%
11 PIT -2.23%
12 GB -2.36%

 

Another new thing I did this week is I broke out schedule adjusted differential into a team’s last 4 games and into a team’s last 8 weeks instead of just the whole season. The motivation for this is because I started the season 100-60 against the spread in the first 11 weeks of the season, but just 43-49 in the final 6 weeks. A similar thing happened over the last 2 seasons and I think part of it is because I’m putting too much stock into old data. This allows me to find out which teams are “hot” at the moment, something that might be masked by the season long data.

Playoff Team Schedule Adjusted Differential (last 4 weeks)

1 SEA 16.11%
2 CAR 15.06%
3 DAL 10.84%
4 BAL 10.56%
5 NE 6.82%
6 CIN 6.77%
7 PIT 6.20%
8 GB 5.76%
9 DEN 3.00%
10 IND 1.55%
11 DET 0.05%
12 ARZ -3.17%

 

Playoff Team Schedule Adjusted Differential (last 8 weeks)

1 SEA 11.68%
2 NE 11.27%
3 GB 8.08%
4 DEN 6.67%
5 PIT 5.44%
6 BAL 4.60%
7 CAR 4.59%
8 CIN 3.12%
9 DAL 1.02%
10 ARZ 0.22%
11 IND -0.21%
12 DET -1.18%

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