|First Place||Last Place||Me (Place)||Std Dev|
|Batting Average||0.2724||0.2366||.2543 (15th)||0.0097|
|Home Runs||165||91||131 (7th)||22|
|Stolen Bases||110||35||67 (9th)||23|
|Wins||61||24||40 (T 14th)||10|
As you can see, there's a whole lot of mediocre going on there with my squad. But being that low in so many categories just gives me more opportunities to gain standings points, right? Well, not necessarily. That's where the standard deviations come in.
Let's say, for the sake of argument, that I have a very good second half and make up an entire standard deviation's worth of ground in batting average, getting me all the way up to .2640. You know where that would put me in the standings? 13th. I'd gain a whole two points. Yeesh. But wait, it gets worse. Calling the period after the All-Star break the second half is just lazy shorthand. There were actually only about 67 games left in the season when I pulled these numbers (the average MLB team had played about 95 games), or about 40% of the season left. Factoring that into it, and I really can only reasonably expect to gain one standings point (the team two places above me is just out of reach at .2619). Double yeesh.
Other categories, though, look much more fruitful for me using this method. A three-point leap appears possible in HR, a massive five in RBI (second place is at just 551, 27 ribbies ahead of me), another three in runs, three in ERA, four in K's. What's more, the one category I'm rocking in (saves) poses very little risk. Second place is right on my heels at 61, but third is at a distant 52 and I could normally expect to lose at most one standings point if I drop one standard deviation's worth.
Now, is it possible to rise more than one standard deviation in a category? Of course! Miracles do happen. If you clear out your farm system to add every elite starting pitcher you can lay your hands on, you could see some incredible rises in ERA, WHIP, K's and wins, for instance. But it's not very likely at all, and would take an incredible set of circumstances to pull off. Remember, statistically speaking only about one in 20 data points lies more than two standard deviations away from the average. What we want to look at here is not the theoretically best possible outcomes, but merely the statistically likely positive outcomes.
Totalling it all up (gains in nine categories and a drop in saves) and the best I can reasonably expect to do this year if things go right is ... third place, from just shy of 100 standings points to the mid-120s. That's not bad given that the top six finish in the money, but it's certainly not what I was hoping for. More importantly, it's not a result that encourages me to go all-out this year and trade away a ton of keeper value for expiring and expensive contracts. I've got a solid shot at a money finish, but effectively zero chance at a title.
So, instead of pursuing players like Joey Votto (he's been dangled) to try and make up those precious HR/RBI/Runs points, I made a smaller deal to pick up Kendrys Morales in exchange for one of my three closers (Fernando Rodney). That, combined with better health and performance from players like Giancarlo Stanton, Brandon Beachy and Martin Prado, as well as further contributions from players picked up in a trade I made in June when I thought a title was still possible (Adrian Beltre, Lorenzo Cain and Zack Greinke, and yes I now feel sick about the massive amount of keeper value I paid for them), should hopefully be enough to climb that ladder.
Keep in mind, this isn't intended to be a predictive tool. Just because the standings gains are within reason doesn't mean they're necessarily within reach. You'll still need the players, and the luck, to pull it off. This method is simply a way to see what can be done, and thus give you a better perspective on how much of your keeper value stockpile you want to commit to the chase.
How to calculate standard deviation is Excel:
1) Copy the data set for one of your league's categories into a column of cells.
2) Select a different cell to display the standard deviation
3) Type '=STDEV(data set range)' into that cell
4) Repeat for each category
'Data set range' refers to the range of cells containing the data. So if you put the HR totals for a 12 team league right up in the top corner of a sheet, the data set range would be A1:A12. You can also just highlight the column of data as you are typing the equation, and Excel will figure it out for you.
Once you have the standard deviation for a category figured out, you'll want to use about two-thirds of it to reflect your reasonably possible gains in that category. That's because about 60% of the season is already in the books, and 40% divided by 60% is two-thirds. (You don't need to be exact, so don't worry too much about getting it down to the decimal.)