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.