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%