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January 15, 2007


Can the Yanks March to 1000 Runs in 2007?
by SG

One of the things we tried tracking last season was the 2006 Yankees and their March to 1000 runs™. Unfortunately for the Yanks, injuries ended the march before it had a chance to really get going.

Through Game 29, the Yankees were on pace to score 1022. Then came a DL stint for Gary Sheffield, and Hideki Matsui breaking his wrist on May 11. The Yankees fell to a 992 run pace the day of Matsui's injury, and from there they never really approached a legitimate shot at it, finishing at a very respectable 930 runs scored.

So what about 2007? What are the odds/chances of the Yankees scoring 1000 runs? Funny you should ask...

Sean Smith e-mailed me last week to let me know that he'd just posted his final version of his Chone projections. So I updated my Diamond Mind program and kicked off a new set of simulations. I ran these 1000 times. It's still to soon for the standings results to mean much, so I won't post them here. This was primarily to look at the Yankee offense specifically.

In 1000 seasons, the Yankees scored an average of 943 runs, and won an average of 97 games. Out of those 1000 seasons, they scored 1000 or more runs 102 times. Frankly, the whole purpose of writing about this is to bring back the pie chart, so here we are...



So assuming the CHONE projections are a reasonable baseline for the Yankees' expected performance, they have a 1 in 10 chance at it.

Part of the reason I like taking these projections and running them through Diamond Mind is it gives us an idea of the volatility of a team's performance in any single season. We can look at the average results to get an idea of the rough talent of the team, but in any given seasons things can happen to skew the results positively or negatively. To illistrate that, here's a graph of the frequencies of the different amounts of runs scored over those 1000 seasons. (Click on the pictures below this line to enlarge them)



Unsurprisingly, it's a bell-shaped curve. The Yankees' standard deviation for runs scored was 46, and 663 of their runs scored totals fell within one standard deviation of their mean 943 runs (898 - 989).

Predicting playing time is probably the most important part of making these simulations as realistic as possible. The projectors don't do it, so I try to use Diamond Mind to do it. So here's how the Yankees performed on average over those 1000 seasons, which led to their mean offensive output of 943 runs.



That should give you an idea of how I allocated playing time. I tried to be somewhat realistic here, as opposed to penciling in the best 9 players for 162 games each.

Let's compare that to the averages over just the seasons where the Yankees scored 1000 runs. Incidentally, the Yankees averaged 103 wins in those seasons.



Here's where the differences showed up.



There's no real magic formula there. They hit for a higher average, hit for more power, and drew more walks. The three players whose performance seemed to drive the offense the most in those seasons were unsurprisingly Bobby Abreu, Jason Giambi, and Alex Rodriguez.

So, according to CHONE the Yankees do have a chance at doing it, but of course injuries will be the key. It'll be interesting to see what the other projection systems say.