A couple of months ago I saw a YouTube video on Downey Games’ Game Winning Drive.

GWD is what you might call a quick simulation game. In about 10 minutes, you can roll up an entire football game, ending up with a final score and certain basic team statistics (rushing touchdowns, passing touchdowns, field goals, interceptions and fumbles lost).

It doesn’t do individual statistics, although it’s not too difficult to rig something up if you want to know *who*, for example, scored a particular touchdown.

That’s not really the point of the game engine, of course. The point is to allow you to roll up an entire week’s worth of NFL games in 3-4 hours and therefore make it plausible to simulate an entire season over the course of a few weeks or month.

I was taken with the idea and found it pretty interesting, so I went ahead and picked up a copy. An e-book version of the game is only $10 for a season, which isn’t shabby. For $15 you can get a printed copy delivered to your door front along with the four 6-sided dice required to play the game. I have enough dice lying around, so I didn’t really need that.

I got to rolling games from the season I purchased (1985) and about 8 games in started noticing something peculiar. My games were, in general, running pretty high in the scoring department.

The historical season averaged 21.5 points per team-game and I was just a hair over 24.

That’s not colossally larger, but it’s noticeable.

As I do with pretty much every card & dice game I’ve ever purchased, I started to reverse engineer the game and try to figure out what the hell might be going on.

At this point, I’ll need to offer a quick breakdown of the game.

A game is broken down into 20 possessions. So, generally speaking, each team gets 10 per game.

For each possession, you roll four dice. Two of the dice are used to determine whether a team records a Score or a Turnover. The other two dice are then used to break down either that Score (Run TD, Pass TD or Field Goal) or Turnover (Fumble Lost, Interception, Punt or Missed Field Goal).

Pretty simple.

I started taking a guess at how they might come up with the range of rolls required for the Score rating for each team and went through things.

Example #1: Atlanta

In 1985, they scored 14 rushing touchdowns, 13 passing touchdowns and 24 field goals. So my math figured the following: 16 games multiplied by 10 possessions per game equals 160 total possessions for the season. 14 rushing touchdowns plus 13 passing touchdowns plus 24 field goals equals 51 scores in those 160 possessions. 51 divided by 160 is 0.31875. Multiply that by the 36 combinations you get from rolling a pair of 6-sided dice and you get 11.475, so you might guess that their range for Score is from 11 to 25. And, in fact, that’s what the official season book reads. Eureka!

Just guessing a little more, I’m looking at 14 rushing touchdowns divided by the 51 total scores for a total of (roughly) 0.2745, multiplying that again by 36 to get to 9.88 and guessing that the “TD Run” listing within score will list 11-24. What do you know? It does! And, similarly, 13 passing touchdowns divided by 51 total scores, multiplying by 36 to get to 9.18 and I’m guessing there will be 9 total “TD Pass” listings on their card. Again, there was.

I repeated this process with 3 other teams just to take a guess at how they were doing things and every time came up correct. So I think we’ve got that.

So why are game scores running high? That seems correct.

Here’s the problem. It’s something I haven’t pointed out about the rules yet.

If a team recovers a fumble or intercepts the opponent, they get a +6 bonus towards their Score range for the ensuing roll. In other words, instead of Atlanta needing a roll of 11-25 to score, they instead need a roll of 11-35.

Atlanta’s defense had 34 turnovers in 1985 – more than 2 per game.

So, in an average game of GWD, Atlanta will have 8 possessions where they score on an 11-25 and 2 where they score on an 11-35. Instead of averaging 11/36 on their chance to Score per possession (as they should), they instead average 12.2/36, an increase of 11%.

(Not coincidentally, I’m also running about 12% over right now…)

So while the game engine itself is pretty solid for what it’s trying to accomplish, there is a flaw in the way the charts are put together. They don’t factor in the “+6” bonus when coming off of a turnover.

If, in Atlanta’s example, we change their Score range from 11-25 to 11-24, they now have 8 possessions per game with 10/36 chance of scoring and 2 with a 16/36 chance of scoring, that comes out to an average of 11.2/36, which is more what we want.

I went ahead and plugged everything into a spreadsheet and verified that my guess at the Score reading was correct in 100% of the cases.

For most teams, it turned out where you’d have to adjust their Score range down just 1 chance. For example, instead of 11-25 they should be 11-24. Instead of 11-31 they should be 11-26.

Some teams that had an extraordinary number of turnovers, however, like that vaunted Bears’ defense, should be adjusted from an 11-35 to an 11-33. They’re going to get over 3 scoring chances off of turnovers per game.

All told from the 1985 season, 20 teams were adjusted down 1 chance and 8 were adjusted down 2 chances.

If folks are interested in this kind of work, I’m more than happy to post the spreadsheet so you can do the same with re-calculating other seasons.

It’s a neat game engine and I rather like the game itself for what it is.

It just has a few things that it didn’t consider.

Time to zero out my scoreboard and standings and start all over again.

I’d be interested in the spreadsheet that you use to adjust scoring for turnovers.

I would be interested in the spreadsheet also. Another interest. Can you reverse engineer another game that I play?

Hey Mike. I appreciate your writing. Unfortunately, right now I’ve been really busy on a few other gaming endeavors and likely won’t have any time to reverse engineer anything. It’s always tempting to do so, believe me! :-) But it’s just not in the cards right now.

I am interested as well. Any ideas on doing defensive ratings?

Hey Travis, thanks for posting. What did you mean by doing defensive ratings?

How do you figure out +and – ratings for defense? How do you determine how a teams run rating is -1 and so on?

That should be pretty simple. I haven’t gone ahead and checked it but my guess is that you would just take the league rate of Rushing TD per Drive, then the team rate of Rushing TD allowed per Drive, take the difference and multiply it by 36.

For example, right now in the 2016 season there have been 416 team games played and 346 rushing touchdowns. By GWD game mechanics, that’s 4,160 “drives”, .083 of which have ended in a rushing touchdown.

The 2016 Patriots have thus far allowed 6 rushing touchdowns in 13 games (i.e. 130 drives). So they are allowing a rushing touchdown on .046 of all drives.

Take .046, subtract .083, multiply that total by 36, and round it off.

I get -1.

My guess would be that, right now, the 2016 Patriots defense would have a TD Run listing of -1.

Hi nice article about GWD that makes a lot of sense. I would be interested in your spreadsheet. Do you still have it?

Thanks

Gabriel

I will give some rough information that I considered without sharing the actual spreadsheet.

First off, GWD is broken down into 10 drives per team per game, right?

So it’s pretty easy to figure out from there how many scoring chances a team will get.

Consider the 2016 Patriots so far.

They’ve played 13 games. By GWD game mechanics, that’s 130 drives. (13 games * 10 drives per game = 130 drives)

They’ve scored 15 rushing touchdowns, 26 passing touchdowns and 20 field goals. That’s a total of 61 scores.

So in GWD, where you roll two six-sided dice and have 36 possible readings, you can figure their scoring chances by doing 36 * Scoring Drives / Total Drives, and round off.

In the case of the 2016 Patriots, that’s 36 * 61 / 130, rounded off to 17.

So the current 2016 Patriots would score on a roll of 11-35.

The “catch” I’m pointing out in this article is that the game engine calls for adding 6 chances to Score when coming off of a Fumble or Interception.

Again, using the 2016 Patriots for an example, they have recorded 14 turnovers on defense.

Since their opponents have had 130 drives (see above), that means that they will record a turnover in roughly 10.8% of all of their opponent’s drives. (14 / 130)

Here’s where it gets pretty “mathy”… We’re going to define some variables.

“TO Drive %” = the percentage of drives that the team has that comes off of turnovers. For the 2016 Patriots, that’s .108.

“Non-TO Drive %” = the percentage of drives that the team has that do NOT come off of turnovers. Simply put, it’s 1 – “TO Drive %”. So for the 2016 Patriots, that’s .892.

“Score %” = the percentage of drives that *should* end up with a score. For the 2016 Patriots, as calculated above, that’s .469.

“Actual Score %” = the percentage of drives that will *actually* end up with a score, based on the improved chances of scoring when coming off of a turnover. This is:

(“Non-TO Drive %” * “Score %”) + (“TO Drive %” * (“Score %” + (1 / 6)))

For the 2016 Patriots, this is going to be:

(.892 * .469) + (.108 * (.469 + (1/6))) = .418 + (.108 * .636) = .418 + .069 = .487

“Adjusted Score %” = the Score chance they *should* be getting, once accounting for the chances they’ll get off of turnovers. This is:

“Score %” * “Score %” / “Actual Score %”

So for the 2016 Patriots right now, that would be:

..469 * .469 / .487 = .452

Then take 36 and multiply it by .452 and – viola! – you’ve got 16. So the 2016 Patriots *should* have a Score reading of 11-34, NOT 11-35.

This is as far as I’ll get into this, by the way. I’m not planning on making any further comments.

It’s a really fun game and you’ll get plenty accurate results without my changes. I’m only suggesting that there are a few tweaks that don’t seem to be in the game engine which should be, otherwise you’re going to end up with higher-scoring games. Not *much* higher scoring. Just a little.

My intention here isn’t to teach folks how to create their own seasons. It’s not a very elaborate game engine. It’s pretty quick and dirty and easy to figure out how their ratings are done, but that’s sort of the fun of the game. It’s not as complicated as figuring out card patterns in a Strat-O-Matic batting card, for example! Anybody with spreadsheet skills could pretty easily create other seasons on their own.

But if you enjoy the game, you should still go off and buy it and support the game designers.My *quick fix* suggestion, however, might be to drop every team’s Score reading by 1. (i.e. 11-31 becomes 11-26, 11-23 becomes 11-22, etc.) That will get you in the ballpark.

All of your articles, reviews and projects to reverse engineer are top notch! Enjoy reading.

If ever you steer towards another baseball game, please consider Statis Pro Advanced for a review and reverse engineer.

Thanks,

Mike

Oh, thanks Mike! I have so many blog posts in my head I just haven’t gotten around to writing yet.

Of all the games I have never played, Statis Pro is probably the most popular. Keep meaning to try and pick up a copy of it on eBay or something someday. I’ve got a bit of a tabletop sports museum going and that one’s missing!