2019 Season Super Bowl prediction

The methodology for this prediction is here.

I managed to watch big chunks of both conference games. The Titans made a game of it for one half. They ran out of steam in the third quarter and ended up losing, but the team overall looked good. The Packers were crushed. The score doesn’t really show how bad the game actually was.

Last I read, Kansas City was favored by one point in the odds. My system favors them by a lot more, more like 5 points.

Super Bowl Odds
Home Team	Visiting Team	Score Diff	Win Prob	Est. Point Spread
Kansas City Chiefs	San Francisco 49ers	0.683	0.66	5.1

 

2019 Season. Conference Championship Odds.

Conventional wisdom went 3-1 and my picks went 2-2; perhaps I would have done better if the Seahawks hadn’t suffered so many injuries at the end of the season. The Titans continue their upset ways while Green Bay, Kansas City, and San Francisco won as favorites.

The methodology of how we pick is given here.

Conference (NFC/AFC) Playoff Odds
Home Team	Visiting Team	Score Diff	Win Prob	Est. Point Spread
San Francisco 49ers	Green Bay Packers	0.263	0.56	2.0
Kansas City Chiefs	Tennessee Titans	1.031	0.74	7.6

 

2019 Season. Second Round Odds.

The first round of the playoffs were full of upsets. The Titans upset the Patriots and the Vikings upset the Saints. Both upsets were driven by ground games that both scored and consumed the clock.

The methodology of how we pick is given here.

Second Round Playoff Odds
Home Team	Visiting Team	Score Diff	Win Prob	Est. Point Spread
San Francisco 49ers	Minnesota Vikings	0.372	0.59	2.8
Green Bay Packers	Seattle Seahawks	-0.194	0.45	-1.4
Baltimore Ravens	Tennessee Titans	0.985	0.73	7.3
Kansas City Chiefs	Houston Texans	0.429	0.61	3.2

 

2019 NFL Playoff Season. Playoff Worksheet. First round playoff odds.

The methodology of this work is described here.

This year, the formulas favor the Baltimore Ravens and the Seattle Seahawks. Baltimore has the advantage in any possible encounter in the AFC. Seattle has the advantage over any team not named the New Orleans Saints. As the Saints lose their HFA against Green Bay, they are not favored against Green Bay. The odds of a Seattle-New Orleans matchup are small.

2019 NFL Playoff Teams, C&F Worksheet.
NFC
Rank	Name	Home Field Adv	Playoff Experience	SOS	Total Score
1	San Francisco 49ers	0.660	0	0.125	0.785
2	Green Bay Packers	0.660	0.747	-0.225	1.182
3	New Orleans Saints	0.660	0.747	0.015	1.422
4	Philadelphia Eagles	0.660	0.747	-0.511	0.896
5	Seattle Seahawks	0.0	0.747	0.690	1.376
6	Minnesota Vikings	0.0	0.747	-0.334	0.413
AFC
1	Baltimore Ravens	0.660	0.747	0.015	1.422
2	Kansas City Chiefs	0.660	0.747	0.061	1.468
3	New England Patriots	0.660	0.747	-0.535	0.872
4	Houston Texans	0.660	0.747	0.292	1.699
5	Buffalo Bills	0.0	0.747	-0.380	0.367
6	Tennessee Titans	0.0	0.747	-0.310	0.437

 

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.

Because the worksheet above can be hard to decipher, for the first week of the 2019 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
New Orleans Saints	Minnesota Vikings	1.009	0.733	7.5
Philadelphia Eagles	Seattle Seahawks	-0.541	0.368	-4.0
New England Patriots	Tennessee Titans	0.435	0.607	3.2
Houston Texans	Buffalo Bills	1.332	0.791	9.9

 

The break even point of the three major 2017 QB draft trades

This would have been done earlier, but Pro Football Reference dropped its very handy chart of draft position versus AV. I started missing it more and more, and using the Wayback Machine I found it here.

The three major QB trades of 2017 were the trade for Mitch Trubisky, Patrick Mahomes, and Deshaun Watson. We will analyze them in sequence.

Mitchell Trubisky Trade
Chicago Bears		49ers		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
2	46	3	45
		67	19
		111	12
		(71)	21
Total	46	Total	97
				51	2.11

 

The Bears have a trade risk comparable to a typical trade for a #1 draft choice and a quarterback at that. The trade has less fundamental risk than Goff or Wentz. The comparable that comes to mind is Eli Manning. By contrast, the delta AV of the other two trades are substantially less.

Patrick Mahomes Trade
Chiefs		Bills		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
10	41	27	25
		91	17
		(25)	24
Total	41	Total	66
				25	1.61

 
Mahomes merely has to give six seven good years, and the trade ends up warranted. The issue in the case of Deshaun Watson is keeping him upright. A fistful of whole years almost as good as his freshman year in the NFL and he would end up bordering on Hall of Fame numbers.

Deshaun Watson Trade
Texans		Browns		Results
Pick	Average AV	Pick	Average AV	Delta AV	Risk Ratio
12	35	25	24
		4	44
Total	35	Total	68
				33	1.94

 

So here is wishing Deshaun Watson a healthy career from now on.

 

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.

 

Thoughts on NFL week 11

Over some five years, the whole of the Matt Ryan – Mike Smith era, Atlanta has had a habit of outperforming its Pythagoreans:

Atlanta outperforming its Pythagoreans
Year	WL%	Pythag	Delta
2008	69	62	7
2009	56	56	0
2010	81	72	9
2011	63	59	4
2012 (to date)	90	71	19

 

But they’ve never outperformed their Pythagoreans as substantially as they have this year. It can’t be blamed on early season New Orleans collapse, as their only loss was inflicted by New Orleans. New Orleans has only hindered this process. Is it turnover that are causing all this? While the 2010 team had a +14 turnover ratio and the 2011 team had a +8 turnover ratio, the 2012 team has only a +5 turnover ratio at this point and the 2008 team had a -3 turnover ratio. No, it’s something else. For now, perhaps noting that this team tends to outperform its Pythagoreans is enough.

Week 11 scoring stats:

Chicago’s biggest weakness was on display this Monday night, as Aldon Smith had a career day. Aaron Schatz (@FO_Schatz) has sent digging into his archives for the biggest DVOA blowouts of all time. The 32-7 demolition of the Bears by the 49ers wasn’t the worst, but it clearly evoked the worst.

The game plan was heavy on traps and wham blocks, and would have warmed the hearts of anyone who ever played NFL Strategy against a blitz heavy opponent.

It does lead to the question of whether Chicago is in the same downward spiral they experienced last year. At this point, however, you would expect Jay Cutler to return and thus slow down the bleeding.

 

2011 Season Conference Championship Round: NY Giants favored throughout playoffs

After the Giants victory over the Packers, I finally got up the nerve to say what my system has been saying from the start, that my predictive system markedly favors the Giants throughout the entire playoffs.

Going all the way?

The deal, of course, is a heavily favored team can lose. A team seeded 1 or 2 and favored by 70% in every game only has a 34% chance of making it through 3 games. The nature of the playoffs make it difficult for any team, even a really good team, to win it all.

That said, the Giants are favored by 75% over the San Francisco 49ers. The only advantage the 49ers hold is home field advantage. The Giants have to be considered a playoff experienced team, and they have a massive strength of schedule advantage, the same advantage that will give them precendence over either New England or Baltimore. If you choose to treat the Giants as having no playoff experience, that lowers their odds to win to a mere 58%.

Favored in the Conference Championship Round:

Giants over 49ers: 75%
NE over Ravens: 59%

Favored in the Super Bowl:

Giants over NE: 66%
Giants over Ravens: 64%
NE over 49ers: 64%
Ravens over 49ers: 65%

Odds of winning the Super Bowl:

Giants: 49%
NE: 24%
Ravens: 18%
49ers: 9%

For contrast, we’ll calculate the Pythagorean odds for these teams as well, ignoring the effects of strength of schedule, and playoff experience.

49ers over Giants: 86%

NE over Ravens: 61%

49ers over NE: 61%

And the 49ers are favored to win the Super Bowl, via Pythagoreans, by 52%.

Of course, if you’re taking these kinds of offensive metrics seriously, please note the odds of the Giants having made it this far was only 7.4% (Originally calculated as 5.4%). Consider those odds, please, before writing my little predictive system off.

 

NFL Playoffs 2012: 3 Seeds at 2 seeds

The wins by Houston and New Orleans ensure that the #3 NFC and AFC seeds will be playing the #2 seeds, and that the #1 seeds will be playing the winner of the #4-#5 game. For now we’ll simply ask: if a team has playoff experience, but a rookie quarterback, does the rookie negate that experience advantage? Houston certainly looked good in their game.

Odds:

In San Francisco-New Orleans, the Saints have the advantage of playoff experience, but San Francisco has home field and a tough schedule. My code suggests the odds in this game are 50-50. In Baltimore-Houston, Baltimore has all three advantages, and is favored to the tune of a 81% chance to win.