ROTISSERIE: Hitting ‘em where they ain’t, pt 1: A Contrarian roster construction strategy

Many roster construction strategies advocate building a balanced roster (pitching and hitting). There are exceptions (punting saves or SBs, for example), but these strategies have extreme risk embedded in them. If you get one point (last place) in a category, you have very little wiggle room in other categories. An injury or two to key players can sink your season.

A contrarian roster construction strategy is to build a roster focused on either hitting or pitching without punting any categories. In 2020, I experimented using two 12-team Draft Champion NFBC teams. This format is a 50-round draft-and-hold league using standard 5x5 rotisserie scoring. There are the standard 23 active roster slots (14 hitters and 9 pitchers) and no free agent pickups. Owners manage their rosters all season with the 50 players acquired during the draft.

In 2020, I tried two different strategies with different entries: The first, to draft a hitting-focused team with the goal of getting 90% of the hitting points; and the second, to draft a pitching-focused team with the goal of getting 90% of the pitching points. I tried to draft a team that would be at least competitive in all categories of the non-focus area—in other words, no punting of any categories.

To begin, I reviewed league results from 2019. I selected 30 leagues at random to estimate how many points are typically needed to finish first or second ("in the money" in a 12-team NFBC league). In the random sample, a median of 94.0 points (out of a possible 120) were needed to win a league and a median of 87.5 were needed to finish second. See Table 1.

TABLE 1: NFBC 2019 12-Team 50-Round Draft and Hold Results

         1st    2nd   1st Place  1st Place Hit-Pitch
League  Place  Place   Hit Pts  Pitch Pts   Delta
======  =====  =====  ========  =========  =========
  1     100.0   90.5     50.0      50.0       0.0
  2      98.0   89.0     42.0      56.0     -14.0
  3      94.0   93.5     47.0      47.0       0.0
  4      87.0   86.0     38.0      49.0     -11.0
  5      87.5   86.5     49.5      38.0      11.5
  6      92.0   81.0     49.0      43.0       6.0
  7      92.0   88.0     45.0      47.0      -2.0
  8      95.0   86.5     49.0      46.0       3.0
  9      95.0   85.0     54.0      41.0      13.0
 10      96.5   95.0     56.0      40.5      15.5
 11      95.5   79.5     59.0      36.5      22.5
 12      87.5   84.0     47.5      40.0       7.5
 13     100.0   82.0     48.0      52.0      -4.0
 14     109.5   98.4     52.0      57.5      -5.5
 15      96.0   84.5     59.0      37.0      22.0
 16      92.0   89.5     47.0      45.0       2.0
 17     105.5   80.0     47.5      58.0     -10.5
 18      91.0   90.5     38.0      53.0     -15.0
 19      91.5   91.0     43.0      48.5      -5.5
 20      88.0   83.5     54.0      34.0      20.0
 21      92.5   86.5     35.5      57.0     -21.5
 22      90.5   87.0     49.0      41.5       7.5
 23      98.0   92.0     52.0      46.0       6.0
 24      95.5   84.0     52.0      43.5       8.5
 25      94.0   86.5     50.0      44.0       6.0
 26     105.5   91.0     52.0      53.5      -1.5
 27      78.5   78.5     38.5      40.0      -1.5
 28      90.0   86.0     48.0      42.0       6.0
 29      94.5   87.5     44.5      50.0      -5.5
 30      94.0   93.5     42.0      52.0     -10.0
Avg      94.2   87.2     47.9      46.3       1.7
Median   94.0   86.5     48.5      46.0
High    109.5   98.4     59.0      58.0
Low      78.5   78.5     35.5      34.0

The overall point target was set at 94 (based on the median of 1st place teams). 90% of the hitting or pitching points is 54 points. A team that finishes 2nd (or an average of 2nd) in all five hitting or pitching categories would collect 55 points. To finish with 94 points, the de-emphasized half of the team would need to get 40 points (finish an average of 5th in those categories).

In the 30-team sample, 15 first-place teams collected more hitting than pitching points; 13 teams had more pitching than hitting points; and two teams had equal hitting and pitching points. This suggests that teams can win these leagues with a variety of roster construction strategies.

The 94-point target breakdown (54 points for the focus area; 40 points for the remaining categories) means we are planning to construct a roster with 14 more points in either the hitting or pitching categories than the opposite category. Is this a realistic plan? How many teams in our sample had more than a 14-point difference between hitting and pitching point totals?

Four 1st place teams had 14 or more points from hitting than pitching, and two 1st place teams had 14 or more points from pitching than hitting. While not common, 6 of 30 first place teams had hitting/pitching splits more extreme than our plan, suggesting that even those plans can work. Next, we’ll look at which individual categories were the lowest scoring for our winning teams.

TABLE 2. Lowest Category Finish For Each 1st Place Team

Runs  HR  RBI  SB  BA  Hitting Total
====  ==  ===  ==  ==  =============
   0   3    4   5   5       17

  K   W   S  ERA  WHIP  Pitching Total
===  ==  ==  ===  ====  ==============
  3   2  10    3    3       21

Note: The total is more than 30 because some teams had more than one 
category tied for the lowest finish.

Nine of the 10 scoring categories were represented among the lowest scoring categories. The only exception was Runs. The one outlier was Saves, which appeared 10 times among the 30 teams as their lowest category. Does this imply that Saves could be punted? We’ll next look at how many points each of the lowest scoring categories had.

TABLE 3. Lowest Number of Points for Lowest Category

1pt  2pt  3pt  4pt  5pt  6pt  7pt  8pt  9pt  10pt  11pt  12pt
===  ===  ===  ===  ===  ===  ===  ===  ===  ====  ====  ====
 1    2    5    5    7    7    2    0    0     1     0     0
Note 1: One team’s lowest category was 6.5 pts. This data point was placed in the
 6 pts category.
Note 2: Seven teams had more than one category tied for the lowest points, but each 
team only contributed one data point to Table 3. For example, one team had three 
categories tied with 10 pts as their low point category. That team provided the
 “1” data point in the 10-point category.

Table 3 shows the lowest scoring category for each of the 30 teams in the sample. Only one 1st place team finished last in any category in the 30-league sample. That team got one point in Saves, but a review of the draft doesn’t provide evidence that the manager planned to punt Saves. The manager drafted two likely closers in 2019 (Kimbrel and Bradley) and several set-up men. He didn’t punt Saves; the draft choices just didn’t work out. Seventeen of the 30 teams had a low category finish of 5 points or higher (at least 8th place or better) in their worst category. This implies team construction should not be too extreme between hitting and pitching.

Finally, let’s look at how the six teams in the sample that were most extreme in the differences between hitting and pitching points drafted their hitters and pitchers. How many hitters were drafted in the first 10 picks? The first 15? The four teams whose results leaned most heavily towards hitting (#10, #11, #15, and #20) drafted either six or seven hitters in the first 10 picks. Each drafted nine or 10 hitters among the first 15 picks. The two teams (#18 and #21) whose results leaned most heavily towards pitching drafted six and four pitchers in the first 10 rounds, and six and seven pitchers in the first 15. Our approach was be to be at least as aggressive in drafting our hitting-focused or pitching-focused teams as these teams did.

In summary, our strategy was to target 94 overall points with 54 point coming from either pitching or hitting categories. We targeted 40 points from our less emphasized categories. We did not plan to punt any categories, and in fact planned to finish an average of 5th in the less emphasized categories.

In part two of this series we will outline the remainder of the strategy and present the results of the experiment.


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  For more information about the terms used in this article, see our Glossary Primer.