Season Win Projections Week 10

Season win totals and division standing projections are listed below. As before, projections are based on each team's opponent-adjusted generic win probability (GWP). The projections account for future opponent strength, and total wins account for current and projected wins. Methodology is described here.

Team	Rank	Proj GWP	Fut Opp	Proj W
AFC E
NE	1	0.91	0.50	15.4
BUF	17	0.40	0.57	7.8
NYJ	28	0.22	0.60	2.6
MIA	27	0.26	0.56	1.9
AFC N
PIT	4	0.81	0.46	12.7
CLE	20	0.55	0.38	8.8
CIN	16	0.56	0.41	6.9
BAL	22	0.26	0.64	5.8
AFC S
IND	2	0.92	0.42	13.4
JAX	9	0.58	0.53	10.0
TEN	11	0.57	0.49	10.0
HOU	18	0.36	0.59	6.5
AFC W
SD	13	0.61	0.42	9.3
DEN	15	0.58	0.40	8.1
KC	26	0.36	0.48	6.5
OAK	31	0.16	0.56	3.1
Team	Rank	Proj GWP	Fut Opp	Proj W
NFC E
DAL	3	0.88	0.48	14.1
NYG	8	0.61	0.51	10.3
WAS	12	0.42	0.62	7.9
PHI	10	0.49	0.60	7.5
NFC N
GB	7	0.74	0.37	13.2
DET	25	0.29	0.58	8.0
MIN	14	0.61	0.37	7.3
CHI	30	0.20	0.54	5.4
NFC S
TB	5	0.85	0.39	10.9
NO	23	0.41	0.47	6.9
CAR	24	0.30	0.58	6.1
ATL	19	0.34	0.59	5.4
NFC W
SEA	6	0.76	0.38	10.3
ARI	21	0.51	0.39	7.6
SF	32	0.19	0.45	3.4
STL	29	0.22	0.51	2.6

QB Rating Week 10

The QB Wins Added Per 16 Games stat (+WP16) estimates how many wins a quarterback adds to his team's record over the course of a 16-game season. +WP16 is explained here and here. Last year's ratings can be found in the second link. Here is the list of 2007 QBs and their vital stats through week 10.

Rank	Player	QBRat	Att	Yds	Air Yds	YAC	Int	Rush	Yds	Sk Yds	Fum	+WP16
1	Brady	131.8	299	2686	1559	1127	4	17	39	62	4	3.30
2	Garrard	102.9	148	1141	680	461	0	30	134	73	2	2.57
3	Roethlisberger	110.2	242	2020	1281	739	7	18	135	177	5	2.01
4	Manning P	90.8	315	2386	1541	845	10	10	-6	63	3	2.00
5	Romo	103.3	292	2555	1473	1082	11	15	81	89	4	1.97
6	Anderson	90.7	292	2231	1393	838	9	20	55	75	3	1.91
7	Palmer	91.1	328	2464	1509	955	10	13	16	90	3	1.56
8	Garcia	95.5	258	1967	981	986	3	30	111	71	3	1.40
9	Schaub	85.0	215	1658	1084	574	7	14	38	94	7	1.33
10	Hasselbeck	89.3	320	2301	1289	1012	8	22	47	84	2	1.05
11	Warner	86.2	178	1314	852	462	6	9	-2	45	6	1.03
12	Delhomme	111.8	86	624	311	313	1	6	26	46	1	0.76
13	Cutler	84.8	248	1882	1041	841	9	22	102	76	6	0.61
14	McNabb	91.7	315	2295	1152	1143	4	28	107	151	6	0.55
15	Losman	80.8	109	820	449	371	3	13	73	73	3	0.48
16	Boller	74.6	134	772	459	313	3	7	22	37	1	0.37
17	Favre	96.2	354	2757	1293	1464	8	17	-2	85	6	0.32
18	Brees	84.8	371	2447	1336	1111	12	14	38	45	5	0.30
19	Pennington	87.5	190	1317	819	498	7	17	23	102	2	0.25
20	Leinart	61.9	112	647	374	273	4	11	42	23	0	0.10
21	Kitna	92.9	298	2294	1335	959	8	19	46	211	11	0.10
22	Campbell	79.9	261	1735	906	829	7	27	147	81	9	-0.04
23	Harrington	81.0	264	1737	856	881	5	12	30	145	0	-0.15
24	Bulger	73.1	242	1602	971	631	8	6	15	152	4	-0.19
25	Manning E	78.6	283	1820	1007	813	11	15	41	91	5	-0.53
26	Holcomb	73.1	83	515	288	227	1	0	0	87	1	-0.64
27	Lemon	69.4	166	923	482	441	4	18	70	86	2	-0.69
28	Green	72.6	141	987	515	472	7	7	32	53	2	-0.77
29	Smith	57.2	193	914	595	319	4	13	89	121	6	-0.79
30	Young	62.2	192	1112	636	476	10	55	217	79	5	-0.93
31	Huard	74.7	262	1766	951	815	11	9	-1	166	3	-1.14
32	Rivers	77.9	255	1743	917	826	10	19	12	107	10	-1.31
33	McNair	73.9	205	1113	568	545	4	10	32	85	8	-1.37
34	Edwards	69.9	121	790	385	405	5	4	7	71	1	-1.48
35	Carr	65.7	114	540	260	280	3	15	54	65	1	-1.64
36	Griese	77.1	217	1508	730	778	10	9	16	101	6	-1.67
37	Culpepper	73.3	125	817	399	418	4	15	36	82	6	-1.86
38	Grossman	53.9	103	642	376	266	6	5	9	96	3	-2.53
39	McCown J	59.5	122	760	348	412	9	18	105	84	8	-3.67

Advance Game Predictions Weeks 12-17

Here is a list of the win probabilities of all remaining games in the 2007 NFL schedule. These will be continue to be updated as the season progresses.

Game Predictions Week 11

Game probabilities for week 11 NFL games are listed below. The probabilities are based on an efficiency win model explained here and here. The model considers offensive and defensive efficiency stats including running, passing, sacks, turnover rates, and penalty rates. Team stats are adjusted for previous opponent strength. Games in which the model disagrees with consensus favorites are highlighted in red.

Vprob	Visitor	Home	Hprob
0.35	ARI	CIN	0.65
0.20	CAR	GB	0.80
0.45	CLE	BAL	0.55
0.04	KC	IND	0.96
0.18	MIA	PHI	0.82
0.89	NE	BUF	0.11
0.35	NO	HOU	0.65
0.16	OAK	MIN	0.84
0.86	PIT	NYJ	0.14
0.35	SD	JAX	0.65
0.78	TB	ATL	0.22
0.11	WAS	DAL	0.89
0.67	NYG	DET	0.33
0.51	STL	SF	0.49
0.10	CHI	SEA	0.90
0.50	TEN	DEN	0.50

It seems as if the consensus favorites and the mathematical models have converged. Only one game difference between them the past two weeks. I would not be confident in the Baltimore prediction without knowing the injury status of their secondary. Without a healthy McAlister, Rolle, and Reed, I don't see how they could be the favorite.

Week 10 Efficiency Rankings

NFL team efficiency rankings are listed below in terms of generic winning probability. The GWP is the probability a team would beat the league average team at a neutral site. Each team's opponent's average GWP is also listed, which can be considered to-date strength of schedule. GWP modifies the generic win probability to reflect the strength of past opponents. Offensive ranking (O Rank) is based on each team's offensive GWP, i.e. it's the team's GWP assuming it had a league-average defense. D Rank is vice-versa. Rankings are based on a logistic regression model applied to data through week 10. A full explanation of the methodology can be found here.

RANK	TEAM	Last Wk	GWP	Opp GWP	O Rank	D Rank
1	NE	2	0.91	0.53	1	3
2	IND	1	0.89	0.56	4	1
3	DAL	3	0.86	0.50	2	4
4	PIT	5	0.79	0.43	7	5
5	TB	4	0.78	0.50	3	8
6	SEA	6	0.66	0.42	12	16
7	GB	12	0.63	0.48	9	14
8	NYG	7	0.62	0.52	16	6
9	JAX	9	0.60	0.54	6	21
10	PHI	10	0.60	0.51	5	22
11	TEN	8	0.56	0.52	27	2
12	WAS	11	0.53	0.53	22	7
13	SD	19	0.53	0.51	18	9
14	MIN	15	0.48	0.51	13	17
15	DEN	24	0.48	0.53	10	25
16	CIN	14	0.48	0.52	8	26
17	BUF	13	0.47	0.54	20	11
18	HOU	16	0.45	0.47	15	28
19	ATL	25	0.43	0.45	19	19
20	CLE	17	0.43	0.53	11	27
21	ARI	22	0.41	0.48	24	15
22	BAL	21	0.39	0.42	29	10
23	NO	18	0.38	0.52	14	32
24	CAR	20	0.37	0.51	23	18
25	DET	23	0.37	0.44	25	12
26	KC	26	0.33	0.45	28	13
27	MIA	28	0.32	0.53	17	30
28	NYJ	27	0.30	0.53	21	31
29	STL	30	0.23	0.49	26	29
30	CHI	31	0.22	0.49	30	24
31	OAK	29	0.20	0.41	31	23
32	SF	32	0.17	0.51	32	20

Weather and Home Field Advantage

Someone recently pointed out a study that indicated home field advantage (HFA) is not the same for every stadium. While that's certainly true, it's very hard to quantify. By definition, the same team is always the home team when measuring a particular location's HFA, so in any given year there would be a lot of team strength captured in a variable accounting for the field's HFA.

The efficiency model I've used includes a factor for HFA, but it is the same regardless of climate. This is the beginning of an effort to quantify the effect of climate on HFA and to see how much of HFA is due to climate differences and how much is due to other factors such as crowd noise, referee psychology, or travel.

The table below lists each home team along with their average December weather. Click on the table headers to sort

Team	Avg Dec T	Avg Dec Wind	Wind Chill
GB	29	10.5	19.7
BUF	36	13.3	27.3
CLE	37	12.1	29.0
CHI	37	11.0	29.5
NE	42	12.2	35.3
KC	42	11.2	35.7
PIT	42	10.4	36.0
NYG	44	10.8	38.3
NYJ	44	10.8	38.3
CIN	44	10.2	38.5
PHI	44	10.1	38.6
DEN	44	8.4	39.3
SEA	46	9.5	41.3
WAS	46	7.8	42.0
BAL	49	9.3	45.0
TEN	49	8.9	45.2
CAR	54	7.4	51.9
SF	56	7.1	54.4
DAL	57	10.8	54.5
OAK	58	7.1	56.8
HOU	65	8.0	65.0
ARI	65	5.1	65.8
JAX	66	7.8	66.3
SD	66	5.6	66.8
TB	72	8.4	73.5
MIA	75	9.2	77.1
ATL	70	0.0	79.2
DET	70	0.0	79.2
IND	70	0.0	79.2
MIN	70	0.0	79.2
NO	70	0.0	79.2
STL	70	0.0	79.2

It's not a surprise that Green Bay is coldest by far, followed by places such as Buffalo, Cleveland, and Chicago. Green Bay would even qualify as a cold climate through November with an average 36 deg wind chill. But I was surprised by how much colder (and windier) a place like Kansas City is than Baltimore or Washington. I'm still considering how to classify each city. Domes are easy, but where is the line drawn between cold and moderate? Should there be cold, moderate, and "warm" classes? For now I'd put the line between cold and moderate at 40 deg wind chill, between DEN and SEA. I'd also define warm weather teams starting at 60 deg between OAK and HOU.

Continue reading this article here.

Season Win Projections Week 9

Season win totals and division standing projections are listed below. As before, projections are based on each team's opponent-adjusted generic win probability (GWP). The projections account for future opponent strength, and total wins account for current and projected wins. Methodology is described here.

Team	Rank	Proj GWP	Fut Opp	Proj W
AFC E
NE	2	0.91	0.50	15.4
BUF	13	0.45	0.53	7.6
NYJ	27	0.22	0.61	2.5
MIA	28	0.25	0.56	2.0
AFC N
PIT	5	0.81	0.46	12.5
CLE	17	0.51	0.44	9.1
BAL	21	0.32	0.62	7.5
CIN	14	0.56	0.42	6.4
AFC S
IND	1	0.93	0.44	14.5
TEN	8	0.61	0.49	10.9
JAX	9	0.53	0.55	9.2
HOU	16	0.36	0.60	7.5
AFC W
SD	19	0.46	0.49	7.7
DEN	24	0.52	0.39	7.1
KC	26	0.38	0.46	7.0
OAK	29	0.26	0.48	4.0
Team	Rank	Proj GWP	Fut Opp	Proj W
NFC E
DAL	3	0.85	0.50	13.8
NYG	7	0.57	0.55	10.6
WAS	11	0.46	0.60	8.7
PHI	10	0.46	0.61	6.7
NFC N
GB	12	0.64	0.40	11.1
DET	23	0.38	0.53	8.1
MIN	15	0.57	0.39	7.6
CHI	31	0.19	0.50	4.5
NFC S
TB	4	0.85	0.41	11.0
NO	18	0.51	0.43	8.1
CAR	20	0.38	0.56	7.0
ATL	25	0.32	0.59	4.5
NFC W
SEA	6	0.80	0.35	10.4
ARI	22	0.52	0.40	7.1
SF	32	0.17	0.49	3.3
STL	30	0.21	0.49	1.7

Advance Game Predictions Weeks 11-17

As requested, here is a list of the win probabilities of all remaining games in the 2007 NFL schedule. These will be continue to be updated as the season progresses. I posted them off the front page of the site because it's such a long and ugly table.