by A.J. Coltrane

Over time I’ve decided that NFL outcomes are more random than I prefer to be involved with (read: gamble on). There are too few possessions per team, and too few scores — if the NFL awarded one point for a touchdown instead of seven a “normal” result would be something like 4 points to 2. Turnovers have a huge impact on the end result. Fumbles happen at random times. Which team recovers the fumble is basically a coin flip… as of today I think there’s too much granularity all around to try to predict outcomes with any accuracy.

With that in mind, Bill Barnwell’s playoff preview included this little gem:

Since 1990, teams that have won the turnover battle in a given game during the regular season have won that game 79.1 percent of the time. In the playoffs, that figure climbs to 84.2 percent. Of course, everybody knows that winning the turnover battle is important; it’s figuring out how to win the turnover battle that’s the hard part.

So there’s that. Yikes.

Maybe my current feeling about predictably predicting NFL results is party based around having seen so much unpredictability. When I was (much) younger the randomness issue didn’t concern me that much. Probably because it was difficult to quantify much of anything from a 1980’s box score. (And that includes baseball — in the 80’s there was no walk info, or ball-strike, or total pitches..) Even back then I couldn’t find a reason for 8-10% of the NFL results.

Maybe I’m older and wiser.

Nah.

But at least I know to avoid the NFL.

By Blaidd Drwg

The great thing about baseball is that you can generally use advanced metrics to make a prediction about the performance of a team in an upcoming season with reasonable accuracy. There are certainly things you can’t predict (injuries, guys significantly over/under performing, luck, etc.) but those metrics have been tested and tweaked to give you a pretty reasonable picture of what will happen in the upcoming season.

Football, for whatever reason, doesn’t seem to enjoy the same level of prediction accuracy. Back in August, ESPN had their NFL preview and included projected standings based on a computer simulation. Here is what we got:

Team	Overall W-L	Home W-L	Road W-L
MIA	10-6	7-1	3-5
NE	9-7	8-0	1-7
BUF	5-11	5-3	0-8
NYJ	4-12	4-4	0-8
CIN	11-5	7-1	4-4
BAL	9-7	8-0	1-7
PIT	9-7	7-1	2-6
CLE	5-11	4-4	1-7
HOU	11-5	8-0	3-5
IND	8-8	6-2	2-6
TEN	6-10	6-2	0-8
JAX	4-12	4-4	0-8
DEN	13-3	8-0	5-3
KC	10-6	7-1	3-5
SD	5-11	5-3	0-8
OAK	4-12	4-4	0-8
WAS	10-6	8-0	2-6
DAL	8-8	7-1	1-7
NYG	8-8	7-1	1-7
PHI	6-10	6-2	0-8
GB	11-5	8-0	3-5
CHI	9-7	8-0	1-7
MIN	7-9	7-1	0-8
DET	5-11	4-4	1-7
ATL	11-5	8-0	3-5
TB	9-7	7-1	2-6
CAR	7-9	7-1	0-8
NO	6-10	6-2	0-8
SEA	13-3	8-0	5-3
SF	13-3	8-0	5-3
STL	7-9	7-1	0-8
AZ	3-13	3-5	0-8

 

It wasn’t the most accurate prediction as they only got 4 out of the 8 division winners correct and 2 out of the 4 Wild Card winners correct. The win totals look reasonable on a cursory level until I actually looked at what made up the records. According to the simulation, 10 teams would go undefeated at home in 2013, 10 teams would go 7-1 and only 6 teams would be .500 or worse. On the flip side, they predicted that only 4 teams would be at least .500 on the road (with no one going better than 5-3) and 19 teams would be either 1-7 or 0-8 away from home.

Now I don’t know exactly what went into the programming of the simulation, but let me tell you, this just looks wrong. It seems that the programmers put too much emphasis on home field advantage and caused some whacky results. I am surprised that they let this be published, given that any average football fan would realize these numbers just look wrong. Just how wrong are they? Well, I decided to look at the road records and over the past 11 NFL Seasons (2002 – 2012), there have been 13 teams that have failed to win a game on the road, which is about 4% of the teams. The prediction for 2013 was for 10 teams to go winless away from home, or 37%. On the flip, over the same period, 46% of NFL teams played at least .500 ball on the road. The computer for 2013? Just 12%. Um, I am pretty sure that you have a significant error in the calculation here.

In some ways, I am comparing apples to oranges by looking at the historical numbers. How did the computer actually do with its predictions? Well, here you go:

Number of Wins	Home Prediction	Home Actual	Road Prediction	Road Actual
0	0	0	12	1
1	0	2	7	6
2	0	1	4	4
3	1	5	5	8
4	5	6	1	6
5	2	7	3	2
6	4	5	0	5
7	10	3	0	0
8	10	3	0	0

 

Those numbers look pretty bad in comparison, especially at the upper and lower ends of the spectrum.

How about total wins? Well, that looks a little better, but only because the increased number of bands flattens out the distribution:

Number of Wins	Projected	Total
13	3	2
12	0	3
11	4	4
10	3	2
9	5	1
8	3	7
7	3	4
6	3	1
5	4	1
4	3	5
3	1	1
2	0	1

 

The moral of this story is if you are trying to figure out how many games your team will win in 2014, take a look at their schedule, go through it game by game and predict a winner. My guess is that you will be more accurate than the computer.

by A.J. Coltrane

2013 NFL MVP Odds at ESPN.

Rank	Candidate	Odds
1	Peyton Manning	5-1
2	Aaron Rodgers	13-2
3	Colin Kaepernick	10-1
3	Drew Brees	10-1
5	Adrian Peterson	12-1
5	Tom Brady	12-1
7	Matt Ryan	15-1
8	Robert Griffin III	18-1
8	Russell Wilson	18-1
10	Andrew Luck	25-1
10	Calvin Johnson	25-1
10	Eli Manning	25-1
Source: @BovadaLV

 

I think the best value is Matt Ryan. Atlanta has two outstanding wide receivers and they’re going to have to throw to win. It’s an interesting look at who’s considered “hot” right now.

by A.J. Coltrane

I’m playing in a restaurant pool where contestants pick the winner of each NFL game. The restaurant awards gift certs if you have the best weekly record, or the best record at the end of the season. Underdogs won 10 out of 14 games outright last week. I didn’t pick anything like 10 underdogs last week, so this was me: