2015 NFL Playoffs, Super Bowl Odds

Odds for the 2015 NFL playoff final, presented from the AFC team’s point of view:

SuperBowl Playoff Odds
Prediction Method	AFC Team	NFC Team	Score Diff	Win Prob	Est. Point Spread
C&F Playoff Model	Denver Broncos	Carolina Panthers	2.097	0.891	15.5
Pythagorean Expectations	Denver Broncos	Carolina Panthers	-0.173	0.295	-6.4
Simple Ranking	Denver Broncos	Carolina Panthers	-2.3	0.423	-2.3
Median Point Spread	Denver Broncos	Carolina Panthers	-5.0	0.337	-5.0

 

Last week the system went 1-1, for a total record of 6-4. The system favors Denver more than any other team, and does not like Carolina at all. Understand, when a team makes it to the Super Bowl easily, and a predictive system gave them about a 3% chance to get there in the first place, it’s reasonable to assume that in that instance, the system really isn’t working.

So we’re going to modify our table a little bit and give some other predictions and predictive methods. The first is the good old Pythagorean formula. We best fit the Pythagorean exponent to the data for the year, so there is good reason to believe that it is more accurate than the old 2.37. It favors Carolina by a little more than six points. SRS directly gives point spread, which can be back calculated into a 57.7% chance of Carolina winning. Likewise, using median point spreads to predict the Denver-Carolina game gives Carolina a 66.3% chance of winning.

Note that none of these systems predicted the outcome of the Carolina – Arizona game. Arizona played a tougher schedule and was more of a regular season statistical powerhouse than Carolina. Arizona, however, began to lose poise as it worked its way through the playoffs. And it lost a lot of poise in the NFC championship game.

 

Conference Championship Round, 2015 NFL playoffs

Odds for the third week of the 2015 playoffs, presented from the home team’s point of view:

Conference Championship Playoff Odds
Home Team	Visiting Team	Score Diff	Win Prob	Est. Point Spread
Carolina Panthers	Arizona Cardinals	-1.40	0.198	-10.4
Denver Broncos	New England Patriots	1.972	0.879	14.6

 

Last week the system went 2-2, for a total record of 5-3. The system favors Arizona markedly, and Denver by an even larger margin. That said, the teams my system does not like have already won one game. There have been years when a team my system didn’t like much won anyway. That was the case in 2009, when my system favored the Colts over the Saints. The system isn’t perfect, and the system is static. It does not take into account critical injuries, morale, better coaching, etc.

 

Second Round, 2015 NFL Playoffs

Odds for the second week of the 2015 playoffs, presented from the home team’s point of view:

Second Round Playoff Odds
Home Team	Visiting Team	Score Diff	Win Prob	Est. Point Spread
Carolina Panthers	Seattle Seahawks	-1.713	0.153	-12.7
Arizona Cardinals	Green Bay Packers	-0.001	0.500	0.0
Denver Broncos	Pittsburgh Steelers	0.437	0.608	3.2
New England Patriots	Kansas City Chiefs	-0.563	0.363	-4.2

 

Last week the system went 3-1 and perhaps would have gone 4-0 if after the Burflict interception, Cincinnati had just killed three plays and kicked a field goal.

The system currently gives Seattle a massive advantage in the playoffs. It says that Green Bay/Arizona is effectively an even match up, and that both the AFC games are pretty close. It favors Denver in their matchup, and the Chiefs in theirs.

One last comment about last week’s games. The Cincinnati-Pitt game was the most depressing playoff game I’ve seen in a long time, both for the dirty play on both sides of the ball, and the end being decided by stupid play on Cincinnati’s part.  It took away from the good parts of the game, the tough defense when people weren’t pushing the edges of the rules, and the gritty play on the part of McCarron and Roethlisberger. There was some heroic play on both their parts, in pouring rain.

But for me, watching Ryan Shazier leading with the crown of his helmet and then listening to officials explain away what is obvious on video more or less took the cake. If in any way shape or form, this kind of hit is legal, then the NFL rules system is busted.

 

2014 playoff notes

To start, a summary of the 2014 regular season data:

This gives us the basis to generate playoff values based on my playoff formula. Playoff Odds are calculated according to this model:

logit P = 0.668 + 0.348*(delta SOS) + 0.434*(delta Playoff Experience)

and the results are:

2014 NFL Playoff Teams, C&F Playoff Model Worksheet.
NFC
Rank	Name	Home Field Advantage	Prev. Playoff Experience	Strength of Schedule	Total Score
1	Seattle Seahawks	0.406	0.434	0.275	1.115
2	Green Bay Packers	0.406	0.434	-0.118	0.722
3	Dallas Cowboys	0.406	0.0	-0.630	-0.224
4	Carolina Panthers	0.406	0.434	-0.292	0.548
5	Arizona Cardinals	0.0	0.0	0.449	0.449
6	Detroit Lions	0.0	0.0	-0.132	-0.132
AFC
1	NE Patriots	0.406	0.434	0.438	1.278
2	Denver Broncos	0.406	0.434	0.550	1.390
3	Pittsburgh Steelers	0.406	0.0	-0.703	-0.297
4	Indianapolis Colts	0.406	0.434	-0.393	0.447
5	Cinncinnati Bengals	0.0	0.434	-0.202	-0.602
6	Baltimore Ravens	0.0	0.0	-0.724	-0.724

 

The total score of a particular team is used as a base. Subtract the score of the opponent and the result is the logit of the win probability for that game. You can use the inverse logit (see Wolfram Alpha to do this easily) to get the probability, and you can multiply the logit of the win probability by 7.4 to get the estimated point spread.

For the second week of the 2014 playoffs, I’ve done all this for you, in the table below. Odds are presented from the home team’s point of view.

Second Round Playoff Odds
Home Team	Visiting Team	Score Diff	Win Prob	Est. Point Spread
Seattle Seahawks	Carolina Panthers	0.567	0.638	4.2
Green Bay Packers	Dallas Cowboys	1.352	0.795	10.0
New England Patriots	Baltimore Ravens	2.002	0.881	14.8
Denver Broncos	Indianapolis Colts	1.349	0.794	10.0

 

Baltimore is not given much of a chance by these techniques, but an interesting analysis by Benjamin Morris of Skeptical Sports (featured now on fivethirtyeight.com) is worth paying attention to. Though the divisional round is hard on teams without a bye, those that survive appear to have a superior chance to go forward in the playoffs. Benjamin has always struck me as an incisive analyst, so he’s absolutely worth paying attention to.

 

2014 – 2nd round of NFL Playoffs

My system went 3-0-1 last weekend (Or 3-1 if you consider my prediction in the Bengals – Chargers game a loss, as opposed to “too close to pick”), so time to present playoff odds for the second round of the playoffs.

Divisional Round Playoff Odds
Home Team	Visiting Team	Score Diff	Win Prob	Est. Point Spread
Seattle Seahawks	New Orleans Saints	0.676	0.663	5.0
Carolina Panthers	SF 49ers	-0.157	0.461	-1.2
Denver Broncos	San Diego Chargers	0.411	0.601	3.0
New England Patriots	Indianapolis Colts	-0.060	0.485	-0.4

 

Odds that differ by less than a point in estimated point spread are probably not significant, and from my POV, a suggestion that you don’t bet that particular game.

 

Week 17 stats, and first round NFL Playoff Odds

The regular season has ended and the playoffs have begun. It would be useful to have a set of playoff grade data to do playoff probabilities, and though I’ve been down and out this season (no job at times, foot stress fracture at times, and a bad right shoulder), I currently have some time off my new job, a new laptop, and enough time to grind through some playoff numbers.

NFL stats at the end of the regular season:

To explain the columns above, Median is a median point spread, and can be used to get a feel for how good a team is without overly weighting a blowout win or blowout loss. HS is Brian Burke’s Homemade Sagarin, as implemented in Maggie Xiong’s PDL::Stats. Pred is the predicted Pythagorean expectation. The exponent for this measure is fitted to the data set itself. SOS, SRS, and MOV are the simple ranking components, analyzed via this Perl implementation. MOV is margin of victory, or point spread divided by games played. SOS is strength of schedule. SRS is the simple ranking.

Playoff Odds are calculated according to this model:

logit P  =  0.668 + 0.348*(delta SOS) + 0.434*(delta Playoff Experience)

The results are given below, as a “score” in logits:

2013 NFL Playoff Teams, C&F Playoff Model Worksheet.
NFC
Rank	Name	Home Field Advantage	Prev. Playoff Experience	Strength of Schedule	Total Score
1	Seattle Seahawks	0.406	0.434	0.494	1.334
2	Carolina Panthers	0.406	0.0	0.484	0.889
3	Philadelphia Eagles	0.406	0.0	-0.661	-0.256
4	Green Bay Packers	0.406	0.434	-0.842	-0.003
5	San Francisco 49ers	0.0	0.434	0.612	1.046
6	New Orleans Saints	0.0	0.0	0.658	0.658
AFC
1	Denver Broncos	0.406	0.434	-0.546	0.293
2	NE Patriots	0.406	0.434	-0.258	0.582
3	Cancinnati Bengals	0.406	0.434	-0.856	-0.017
4	Indianapolis Colts	0.406	0.434	0.209	1.048
5	Kansas City Chiefs	0.0	0.0	-0.602	-0.602
6	San Diego Chargers	0.0	0.0	-0.118	-0.118

 

The total score of a particular team is used as a base. Subtract the score of the opponent and the result is the logit of the win probability for that game. You can use the inverse logit (see Wolfram Alpha to do this easily) to get the probability, and you can multiply the logit of the win probability by 7.4 to get the estimated point spread.

For the first week of the playoffs, I’ve done all this for you, in the table below. Odds are presented from the home team’s point of view.

First Round Playoff Odds
Home Team	Visiting Team	Score Diff	Win Prob	Est. Point Spread
Philadelphia Eagles	New Orleans Saints	-0.914	0.286	-6.8
Green Bay Packers	SF 49ers	-1.049	0.259	-7.8
Cincinnati Bengals	San Diego Chargers	0.101	0.525	0.7
Indianapolis Colts	Kansas City Chiefs	1.650	0.839	12.2

 

Some general conclusions from the data above: the teams my model favors most are the Seattle Seahawks, the Indianapolis Colts, the 49ers, the Carolina Panthers, and then the New Orleans Saints, mostly NFC teams. Since the Super Bowl itself does not have a home team, the odds change once you actually reach the Super Bowl. The sum of the SOS column and the Previous Playoff Experience column can be used to estimate odds of winning “the big one”. The strongest team in a Super Bowl setting would be the San Francisco 49ers, with a total score, less HFA, of 1.049. The Indianapolis Colts, with a total score of 0.643 less HFA, would be the strongest possible AFC contender.

A point I’d like the reader to consider is this question: should the New Orleans Saints be granted an exception to the previous playoff experience rule of “last year only counts” and given the 0.434 advantage of a playoff team? 2012 was an aberration as the coach was suspended. I’m not calculating this variation into the formula at this point, but I’ll note that this is an issue that you, the reader, need to resolve for yourself.

The road to the playoffs is not easy, a topic that can be studied by trying to calculate the path to the playoffs of the Indianapolis colts, a team that would be favored in every matchup along the way. Let’s calculate the odds of Indianapolis actually winning all three games.

Odds of Indianapolis reaching the Super Bowl
WP versus Kansas City	WP versus Denver Broncos	WP versus NE Pats	Cume Probability
0.839	0.586	0.515	0.253

 

Three teams from the NFC would be favored over any possible AFC contender. Those are San Francisco, Seattle, and the New Orleans Saints. Carolina would be favored over any AFC contender except the Indianapolis Colts.

 

Baltimore; the perfect playoff model; conference championship odds.

I suspect  to a first approximation almost no one other than Baltimore fans, such as Brian Burke, and this blog really believed that Baltimore had much of a chance(+). Well, I should mention Aaron Freeman of Falc Fans, who was rooting for Baltimore but still felt Denver would win. Looking, his article is no longer on the Falcfans site. Pity..

WP graph of Baltimore versus Denver. I tweeted that this graph was going to resemble a seismic chart of an earthquake. Not my work, just a screen shot off the excellent site Advanced NFL Stats.

After a double overtime victory by 3 points, it’s awfully tempting to say, “I predicted this”, and if you look at the teams I’ve  favored, to this point* the streak of picks is 6-0. Let me point out though, that you can make a limiting assumption and from that assumption figure out how accurate I should have been. The limiting assumption is to assume the playoff model is 100% accurate** and see how well it predicted play. If the model is 100% accurate, the real results and the predicted results should merge.

I can tell you without adding up anything that only one of my favored picks had more than a 70% chance, and at least two were around 52-53%. So 6 times 70 percent is 4.2, and my model, in a perfect world, should have picked no more than 4 winners and 2 losers. A perfect model in a probabilistic world, where teams rarely have 65% chances to win, much less 100%, should be wrong sometimes. Instead, so far it’s on a 6-0 run. That means that luck is driving my success so far.

Is it possible, as I have argued, that strength of schedule is an under appreciated playoff stat, a playoff “Moneyball” stat, that teams that go through tough times are better than their offense and defensive stats suggest? It’s possible at this point. It’s also without question that I’ve been lucky in both the 2012 playoffs and the 2013 playoffs so far.

Potential Championship Scenarios:

 

Conference Championship Possibilities
Home Team	Visiting Team	Home Win Pct	Est. Point Spread
NE	BAL	0.523	0.7
HOU	BAL	0.383	-3.5
ATL	SF	0.306	-6.1
SF	SEA	0.745	7.9

 

My model likes Seattle, which has the second best strength of schedule metric of all the playoff teams, but it absolutely loves San Francisco. It also likes Baltimore,  but not enough to say it has a free run throughout the playoffs. Like many modelers, I’m predicting that Atlanta and Seattle will be a close game.

~~~

+ I should also mention  that Bryan  Broaddus tweeted about a colleague of his who predicted a BAL victory.

* Sunday, January 13, 2013, about 10:00am.

** Such a limiting assumption is similar to assuming the NFL draft is rational; that the customers (NFL teams) have all the information they should, that they understand everything about the product they consume  (draft picks), and that their estimates of draft value thus form a normal distribution around the real value of draft picks, and that irrational exuberance, or trends, or GMs falling in love with players play no role in picking players. This, it turns out, makes model simulations much easier.