Category optimization

by BaseballHQ.com on April 28, 2009 @ 09:35:09 PDT

 


The Draft Day section of RotoHQ has described ways to optimize categories in order to finish at the top of your league. The Sweeney and Bernhard plans are two examples of optimization whose underlying strategy is to play for 75%, not 100% of total points.

Now that the draft is over, it is important to fertilize the seeds you have sown. Optimization is an important draft strategy, but it's an equally important in-season procedure. Those early standings and flashy names are seductive temptresses baiting you away from your better judgment.

Rotisserie baseball is, at its core, about making the most amount of money on your $260 investment. If you make a $70 profit on your initial outlay, you stand a very good chance of winning your league. The league as a whole must have a zero net profit/loss. Your earnings are relative to your opponents', and your categorical standing above the league average determines your profit. Throughout the season it is important to be consistently better than average in the categories you are optimizing.

Let's take a Sweeney plan and use it as an example. Alex Patton and Peter Kreutzer are playing an AL Tout Wars Sweeney. They're punting HR and RBI and optimizing their 75% of total points through the other six categories. The perfect Sweeney is a first place finish in those other six categories, so that's their goal.

One of their obstacles is the league they are playing in. The most competitive leagues will account for nearly 100% of the top 168 batters in the four hitting categories and top 108 pitchers in the four pitching categories. It is to their advantage to see a save go unclaimed by a competitor rather than match them one for one. The former gives them a higher percentage of the total league saves. The higher the percentage, the higher their profit in saves.

The following table tells a number of stories about competition. Ten 12-team, standard roto AL leagues were chosen at random from TQ Stats' 1997 archive. The total number of statistics in each category is added up, and listed in Row 2. The top 168 AL players in each hitting category and top 108 players in each pitching category are ranked, and their statistics added up. This is shown in Row 1.

The top 168 HR guys, for instance, accounted for 2313 trips to the moon. Next, we divide Row 2 by Row 1. The higher this quotient, the better the league has done at cornering the best available stats. Finally, the top, average, and bottom teams in each category are identified and their stats are averaged over all ten leagues. This provides a snapshot of what it took to win a 1997 category. For the sake of completeness, an NL table follows this essay.

1997 AL
BA
HR
RBI
SB
Top 168
0.293
2313
9569
1408
Roto Avg
0.272
2301
9645
1385
Total
N/A
99.5%
100.8%
98.4%
First place
0.284
244
986
171
Last place
0.261
137
594
69

1997 AL
W
SV
ERA
WHIP
Top 168
901
540
3.38
1.253
Roto Avg
857
517
4.35
1.402
Total
95.1%
95.7%
N/A
N/A
First place
91
74
3.68
1.298
Last place
45
13
5.07
1.515

If Tout Wars is like these ten leagues, Alex and Peter will have a 100% - 95.1% = 4.9% margin of error in wins. In other words, the average AL league will omit about 5% of the wins. These unclaimed wins work to their advantage. The same logic applies for the other cumulative categories. Note that most leagues will over-pursue HR and RBI, showing the unabatement of power overvaluation.

This logic does not apply to the variable categories (BA, ERA, and WHIP) because the AB and IP requirements make for infinite permutations. Was Homer Bush's 4 hits in 11 AB more valuable than Frank Thomas' .347 BA in 530 AB? No, because 14 Homer Bushes only get you 154 team AB. If there were no AB floor, Homer is more valuable in BA.

Great, but what does this have to do with running your team? It sets your weekly goals in each category. For the cumulative categories, divide the Top 168 sum (top row in table) by the Roto League Average total (Row 2). This gives you five multipliers that measure competition. For AL Tout Wars (table not shown), these multipliers were: HR-1.08, RBI-1.07, SB-1.06, W-1.26, SV-1.06.

Multiply these values by what the average first place team did last year. This provides a set of winning projections for the upcoming year. Divide by 27, the number of weeks in the baseball season. For the variable categories, simply set last year's first-place-team average as your goal. Feel free to tweak them if the bar seems too low or too high. Since this example is a Sweeney, we'll put a zero in the HR and RBI categories.

Finally, multiply by the number of weeks elapsed in the season (3.5 as of April 24). This provides the year to date pace values. Here's how the calculated targets match up with Patton/Kreutzer's realization:

Category
Target
P/K to date
BA
.284
.309
HR
0
9
RBI
0
51
SB
22
24
W
12
6
SV
10
10
ERA
3.68
5.23
Ratio
1.298
1.639

They're right on target with the bats and their closers. Slow starts by their starting pitchers throw the other three categories off. It's reasonable to expect that they'll come around, so the P/K team looks on track to get their 75% and be formidable Tout Warriors provided they get their strong innings.

What this exercise provides is the knowledge of how reasonable it is to continue your optimization. If you fall too far off the pace midway through the season, it's time to firesale. On the other hand, if you're off in only one category and own an excess in another, that could be the gateway for a deadline-eve trade. Weekly tracking may not be as much fun as reading a boxscore or perusing the roto standings, but it keeps the focus on profiteering, which is your ultimate Rotisserie goal.

1997 AL
BA
HR
RBI
SB
Top 168
0.293
2040
8818
1725
Roto Avg
0.274
1975
8746
1688
Total
N/A
96.8
99.2
97.9
First place
0.284
223
882
218
Last place
0.259
104
535
81

1997 AL
W
SV
ERA
WHIP
Top 168
935
563
3.30
1.213
Roto Avg
855
520
3.97
1.335
Total
91.4%
92.4%
N/A
N/A
First place
92
72
3.41
1.229
Last place
49
9
4.61
1.449
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