[Editor’s Note: This post originally published March 3, 2018, added back to link properly from Draft Buddy.]

Why do we play fantasy baseball? Is it the thrill of picking up that pitcher for a spot start and seeing him throw a gem? That’s part of it. Is it seeing that “sleeper” batter you drafted late put up a bunch of crooked numbers for you? That’s part of it. Another part might just be the love of the game and fantasy baseball gives us another way to express that love.

Now, these might just be enough for you and you’re content drafting your players and setting your lineups throughout the season and wherever you end up in the standings is okay. For those of you that like to salt your food with the tears of your enemies, this article about Target Percentages is for you!

If you don’t know where you are going, you might wind up someplace else.

Yogi Berra

## Setting Category Goals

In roto-scoring leagues, the goal is to finish with the best score in each category. Coming out of the draft, you want your squad to be in the best position to achieve that goal. Simple enough, right? How do you go about getting your squad in position to win?

First of all, you need to define the best score in each category. How do you do that? You look at last year’s standings. If those aren’t available, you look to the Internet! This process will not help you with establishing a ranking of players but it will help maintain your focus during the draft. What you will need:

- fantasy baseball projections (also available in Draft Buddy)
- spreadsheet skills
- color printer
- last year’s standings, or those from a similar league setup

In this example I am competing in a 12-team league, 5×5 roto with 13 hitters using 1 catcher and 5 outfielders, 9 pitchers and 3 bench spots. You can easily adapt this approach to different league configurations.

I am going to tell you right now that you are not going to be able to draft a squad that will achieve the absolute best score in each category, unless you are in a league of one, and, in that case, you are both a winner and a loser.

Take a look at the total points score that won your league. In most 12-team, 10-category leagues it was somewhere between 85 and 95 points. That breaks down to an average of 9 points in each category, or 4th best. So, if you aim to finish 4th in each category, you would end up with about 90 points and a good shot at winning your league. I recommend that you strive to finish 3rd in each category. That would put you on pace for 100 points, which should win your league.

How do you do that? If you have last year’s standings, find the third best score in each category. These will become your target for that stat category. For example, if the third best HR score was 356, then you would target 356 HR in your draft. This should all be pretty straight forward. For this article, I took the highest third best score from the final standings last year from my league:

R | HR | RBI | SB | AVG |
---|---|---|---|---|

1162 | 356 | 1127 | 159 | 0.2778 |

W | SV | K | ERA | WHIP |
---|---|---|---|---|

108 | 120 | 1568 | 3.626 | 1.212 |

To put my squad in the best position to succeed, I want the projections of the players I draft to add up to, or exceed, these target totals. Now, I could have a sheet of paper with my target totals at the top and when I draft a player, simply subtract his projections from these totals. I’ll keep a running tally throughout the draft.

This would work very easily for the counting stats, but what do you do about the ratio categories? Unless you have hits, at-bats, innings pitched, etc., you will have a hard time keeping track of those categories. This is where my Target Percentages method enters the picture!

## Introducing Target Percentages

In one sentence, target percentages are the percentage of the target total a player earns for you based on his projections. For simplicity’s sake, let’s look at Draft Buddy’s #1 ranked player, Mike Trout. We have Trout projected for 511 AB, .309 AVG, 111 R, 38 HR, 106 RBI and 20 SB.

If I divide his 38 HR by the target total of 356, I will see that Trout would give me 10.67% of my target HR total. I advise you to round all the numbers to the nearest whole number. Trust me on that. So, Trout’s target percentage for HR is 11%. Repeat this for the other three counting stats and you should get 9% for RBI, 10% for R and 13% for SB.

The ratio stats, like batting average, are a little bit trickier. The first step is to subtract the target batting average from Trout’s batting average and then multiply by Trout’s at-bats. This will give you the number of hits above the “target level hitter” that Trout is worth. So, we subtract 0.2778 from 0.309 to get 0.0312 and then multiply that by 511 to get 15.9432.

Now you need to take this “Hits-Above-Target-Level” (HATL) number and find out how many standard deviations the player is from the mean. This is where using a spreadsheet comes in really handy. Take Trout’s 15.943 HATL and divide it by the standard deviation of **every** hitter’s projected HATL score.

For this article, let’s say that there is a 6.249 standard deviation for all hitters. This would lead to Trout’s AVG percentage to be 2.551 (15.943/6.249). Over the past few years I’ve discovered the sweet spot for tracking throughout the draft is to round this number to the nearest 0.25 (this can be done using the FLOOR function in Excel) and formatting so negative numbers are in red to stand out.

So, put it all together for Trout and you get the results in the table below. I repeated the process for Draft Buddy’s top ten ranked batters:

Player | R | HR | RBI | SB | AVG |
---|---|---|---|---|---|

Mike Trout | 10% | 11% | 9% | 13% | 2.50 |

Giancarlo Stanton | 9% | 15% | 11% | 2% | 0.50 |

Trea Turner | 8% | 5% | 6% | 31% | 1.75 |

Nolan Arenado | 8% | 11% | 10% | 2% | 1.50 |

Mookie Betts | 9% | 7% | 8% | 13% | 2.00 |

Bryce Harper | 8% | 10% | 9% | 6% | 1.75 |

Manny Machado | 8% | 10% | 9% | 5% | 1.00 |

Paul Goldschmidt | 8% | 9% | 9% | 10% | 1.00 |

Jose Altuve | 8% | 5% | 8% | 15% | 2.75 |

Gary Sanchez | 6% | 8% | 7% | 2% | -0.75 |

I also did this so that you can get an idea of what your list will look like. To be effective, you have to do this for every possible player that you might draft because this will be your cheat sheet during the draft.

- Sanchez makes the list due to position scarcity at the catcher position but you need to keep in mind that you’re going to have to make up the weak catcher stats from another batter… the story since the dawn of time.
- Turner’s 31% stolen bases is a big chunk of what you need. You’ll find that with the speed merchants in the player pool. Big chunks of your SB can come from a few players. I, personally, like the 10%-15% guys.
- Who do you like better, Betts or Harper? I’m leaning towards Betts simply for the SB %.
- Who do you like better, Machado or Altuve? I’m going with Altuve and his 2.75 in AVG. Those positive numbers really help you in the later rounds when you are scraping the bottom of the barrel batters.

For the ratio stats of pitchers, the method is exactly like you did above when you found the batting average score for Trout, with one small exception. You will subtract the player’s projected ratio from the target. This is done to reflect the nature of the pitching ratios, that lower is better. Instead of finding the HATL, you will be finding the “Earned-Runs-Above-Target-Level” (ERATL) and “Walks + Hits-Above-Target-Level” (WHATL).

Here are our projections for the top 5 starting pitchers and top 5 closers. For example purposes, let’s say that the standard deviation for ERA is 61.861 and for WHIP is 11.048.

Player | W | SV | K | ERA | WHIP |
---|---|---|---|---|---|

Clayton Kershaw | 14% | 0% | 14% | 2.50 | 3.25 |

Chris Sale | 14% | 0% | 15% | 1.50 | 3.00 |

Max Scherzer | 14% | 0% | 16% | 0.75 | 2.25 |

Noah Syndergaard | 12% | 0% | 14% | 1.25 | 2.00 |

Corey Kluber | 13% | 0% | 14% | 1.00 | 2.00 |

Player | W | SV | K | ERA | WHIP |
---|---|---|---|---|---|

Kenley Jansen | 4% | 32% | 6% | 0.75 | 1.50 |

Craig Kimbrel | 4% | 28% | 6% | 1.00 | 1.00 |

Aroldis Chapman | 4% | 24% | 6% | 0.75 | 0.50 |

Ken Giles | 4% | 28% | 5% | 0.25 | 0.25 |

Edwin Diaz | 4% | 27% | 5% | 0.25 | 0.25 |

- Hard to argue with Kershaw as the top SP. Look at those ERA and WHIP numbers!
- Who do you like between Syndergaard and Kluber? Wins are so flaky that Kluber’s advantage doesn’t make up for the 0.25 ERA.
- Note how the closers (and other RP) help or hurt your ERA and WHIP but typically only a little bit.
- Regarding saves, I try to get three closers to get close to 100% and then sprinkle in a few other non-closing RP to get a few more saves to get to 100% and help ERA and WHIP.

## Enough with all the math! How do you use all of these numbers?

As the draft unfolds, you can keep track of how close you are getting to your target totals. Simply keep a running tally for each category. For example, let’s say (in some bizarre draft) you were able to draft Trout and Altuve with your first two picks. This would put you at 18% of your runs target already secured, 16% HR, 17% RBI, 28% SB, and a +5.25 AVG.

Player | R | HR | RBI | SB | AVG |
---|---|---|---|---|---|

Mike Trout | 10% | 11% | 9% | 13% | 2.50 |

Jose Altuve | 8% | 5% | 8% | 15% | 2.75 |

TOTAL | 18% | 16% | 17% | 28% | 5.25 |

Your goal is to get 100% for the counting stats and stay above ZERO in the ratio stats. I recommend formatting the ratio scores that represent negative numbers to show in red. This will help you to differentiate between the values that were rounded to zero, even though some will be negative.

As the draft progresses, you will see that you may be falling behind in a certain category and can target a player that helps you in that category. Also, if you fall short of 100% for any of the counting stats, you will know what type of player to target for bench spots.

Target Percentages are only meant to be used during your draft. Once the season starts, things will change and you have to act accordingly. This is just a tool to help you stay focused during your draft. This is Part 1 introducing and explaining Target Percentages, and in Part 2 I will demonstrate using this concept in a mock draft.