We can’t work with my playoff model without having a set of week 17 strength of schedule numbers, so we’ll present those first.

Between a difficult work schedule this last December and a very welcome vacation (I keep my stats on a stay at home machine), I haven’t been giving weekly updates recently. Hopefully some of my various thoughts will begin to make up for that.

Though with SOS values, you could crunch all the playoff numbers yourselves, this set of data should help in working out the possibilities:

What I find interesting is the difference between Vegas style lines, and my numbers, and the numbers recently posted by Brian Burke on the New York Times Fifth Down blog. My model is very different from Brian’s, but in three of the four wild card games, our percentage odds to win are within 2-3 percent of each other.

Point spreads were estimated as follows: if an effect of 60% were valued at 3 points (i.e. playoff home field advantage is about 60% and home field advantage is usually judged to be worth 3 points), then two effects of that magnitude should be worth 6 points. But it’s only on a logit scale that these effects can be added, so it only makes sense to relate probabilities of winning through their logits. As the logit of 0.60 is about 0.405465, then an estimated point spread can be had with the formula

*point spread = 3.0*logit(win probability)/0.405465*

Update (1/9/2012) – even simpler is:

*est. point spread = 7.4*logit(win probability)*

A simplified table of the wild card games, with percentages and estimated point spreads is:

Wild Card Playoff Round | |||
---|---|---|---|

Home Team | Visiting Team | Home Win Pct | Est. Point Spread |

GB | MIN | 0.682 | 5.6 |

WAS | SEA | 0.482 | -0.5 |

HOU | CIN | 0.642 | 4.3 |

BAL | IND | 0.841 | 12.3 |

**How many successes is a touchdown worth?**

We’ve spoken about the potential relationships between success rates, adjusted yards per attempt, and stats like DVOA here, but to make any progress, you need to consider possible relationships between successes and yards. Let me point out the lower bound of the relationship is known, as 3 consecutive successes must yield at least 10 yards, and 30 consecutive successes must end up scoring a touchdown. In this case, the relationship is 1 success is equal to or greater than 3 1/3 yards.

Thus, if the surplus value of a touchdown is 20 yards, that’s 6 successes. If a turnover is worth 45 yards, that’s about 13.5 successes.

A smarter way to get at the mean value of this kind of relationship, as opposed to a limiting value, would be to add up the yards of all successful plays in the NFL and divide by the number of those plays. For now, that’s something to be pursued later.

January 7, 2013 at 9:45 am

[…] the results for the divisional round are embedded in the image of my playoff spreadsheet in my previous article, the table below is certainly easier to […]

October 20, 2013 at 12:50 pm

[…] For a simple relationship between point spreads and winning percentages, look here. A different approach is given in the book “Mathletics“, worth reading if you’re […]

December 30, 2013 at 10:59 am

[…] 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 […]

January 2, 2017 at 12:28 pm

[…] 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 […]

January 2, 2018 at 8:01 pm

[…] 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 […]