The Z Files: Pilfering Points

The Z Files: Pilfering Points

This article is part of our The Z Files series.

Much of the early-season talk surrounds the record-setting home run pace, and rightfully so. On the flip side, stolen bases are down to fewer than one per game. The last time there were more games played than pilfers was 1972.

In rotisserie scoring, it doesn't matter that steals are dwindling. The category is worth the same as the others. Points-leagues players, however, may need to adjust expectations (a study for another day, to investigate if the decline is uniform or affects some players more than others).

It may not take as many steals to compete in today's game, but there's a smaller inventory to provide the necessary bags. Knowing where to look provides an edge. Today's discussion focuses on the teams most likely to supply the demand for those yearning to compete in the stolen base category.

Let's begin with a historical perspective. What team characteristics result in more running?

The study will look at several correlation coefficients, measuring the linear relationship between two sets of data. One input will be steals. The other will be factors with a chance to influence the level at which a team runs.

A correlation coefficient, denoted as "r", ranges from -1 to 1. Perfect positive linear correlation is 1. As one set of data increases, the other follows proportionately. When r is -1, there's a perfectly inverse relationship. That is, as one set grows, the other lessens proportionately. In terms of this study, those variables generating an r closest to -1 or 1

Much of the early-season talk surrounds the record-setting home run pace, and rightfully so. On the flip side, stolen bases are down to fewer than one per game. The last time there were more games played than pilfers was 1972.

In rotisserie scoring, it doesn't matter that steals are dwindling. The category is worth the same as the others. Points-leagues players, however, may need to adjust expectations (a study for another day, to investigate if the decline is uniform or affects some players more than others).

It may not take as many steals to compete in today's game, but there's a smaller inventory to provide the necessary bags. Knowing where to look provides an edge. Today's discussion focuses on the teams most likely to supply the demand for those yearning to compete in the stolen base category.

Let's begin with a historical perspective. What team characteristics result in more running?

The study will look at several correlation coefficients, measuring the linear relationship between two sets of data. One input will be steals. The other will be factors with a chance to influence the level at which a team runs.

A correlation coefficient, denoted as "r", ranges from -1 to 1. Perfect positive linear correlation is 1. As one set of data increases, the other follows proportionately. When r is -1, there's a perfectly inverse relationship. That is, as one set grows, the other lessens proportionately. In terms of this study, those variables generating an r closest to -1 or 1 affect steals the most.

The following team statistics over the previous four seasons will be analyzed:

·       Wins

·       Runs Scored

·       Runs Allowed

·       Run Differential

·       Success rate

·       Home runs

·       Previous season steals

Intuitively, an argument can be posed for each stat influencing how much a team runs. Here are the results:

YEAR

W

R scored

R Allowed

R Diff

SB%

HR

Prev Yr

2018

0.13

0.16

-0.62

0.19

0.75

0.37

0.37

2017

0.30

0.20

-0.41

0.30

0.62

0.30

0.64

2016

-0.26

-0.10

-0.10

-0.30

0.76

-0.30

0.52

2015

-0.16

0.08

-0.04

-0.05

0.60

-0.03

0.19

The factor most impacting stolen bases is the success rate of attempts. The second-best correlation is last year's total. Factors associated with scoring don't consistently line up with team steals.

So we have the data for reference, here's last season's ranking of steals by team.

Team

SB

Indians

135

Rays

128

Red Sox

125

Brewers

124

Nationals

119

Royals

117

White Sox

98

Rockies

95

Padres

95

Braves

90

Angels

89

Orioles

81

Mariners

79

Diamondbacks

79

Reds

77

Giants

77

Dodgers

75

Rangers

74

Astros

71

Mets

71

Pirates

70

Tigers

70

Phillies

69

Cubs

66

Yankees

63

Cardinals

63

Twins

47

Blue Jays

47

Marlins

45

Athletics

35

It's early, but here's the ranking of the 30 teams based on success rate. The idea being, teams with the lowest rate of caught stealing should be among the stolen base leaders by season's end, so they're excellent offenses to target for individual players.

Team

SB

CS

SB%

Tigers

7

1

87.5%

Rays

18

3

85.7%

White Sox

15

3

83.3%

Angels

5

1

83.3%

Diamondbacks

9

2

81.8%

Mariners

19

5

79.2%

Brewers

7

2

77.8%

Nationals

10

3

76.9%

Pirates

10

3

76.9%

Red Sox

10

3

76.9%

Indians

10

3

76.9%

Cubs

9

3

75.0%

Dodgers

5

2

71.4%

Mets

10

4

71.4%

Yankees

5

2

71.4%

Rangers

15

6

71.4%

Royals

20

8

71.4%

Giants

7

3

70.0%

Cardinals

9

4

69.2%

Athletics

7

4

63.6%

Padres

7

4

63.6%

Orioles

7

4

63.6%

Phillies

5

3

62.5%

Braves

8

5

61.5%

Rockies

8

5

61.5%

Astros

10

7

58.8%

Blue Jays

4

3

57.1%

Marlins

6

5

54.5%

Twins

3

3

50.0%

Reds

3

5

37.5%

The r for this data is 0.51. Based on recent campaigns, some teams with high success rates but limited swipes will administer the green light while those running with poorer results will begin to put up the stop sign. Obviously, there will be exceptions, lest the coefficient would be 1. Still, there's some actionable takeaways from the early-season data.

Teams Likely to Run More

Look for the Tigers, Angels, Diamondbacks and Dodgers to increase their thievery. Of course, some of the low attempts are due to personnel, but the numbers show as a team, the better the success, the more a team runs.

Given that there's roster turnover, rolling in last season's totals could help unearth teams to target. Of the above four offenses, the Angels (11th in 2018) and Diamondbacks (14th) are most likely to take off more. Possible beneficiaries from the Halos include David Fletcher and Andrelton Simmons while Christian Walker, Nick Ahmed and Ketel Marte are Snakes apt to slither more.

Teams Likely to Run Less

To this point of the season, the only club with double-digit steals but a poor success rate is the Astros. Off the field, Houston is analytically driven. Between the lines, they're a veteran club, just a year removed from winning it all. To date, both Jake Marisnick and Yuli Gurriel have been nabbed both times they've chanced a steal. Look for that duo to curtail future running with the likes of Jose Altuve, Alex Bregman, Michael Brantley, George Springer and Carlos Correa still trusted to pick and choose spots to run.

Thus far, the focus has been on the offense. The other side of the coin is defense. Intuitively, teams should temper attempts facing teams with batteries adept at controlling the running game. Here's the correlation between the rate of catching runners and attempts against over the past four seasons:

Year

r

2018

0.30

2017

0.57

2016

0.35

2015

0.32

Curiously, there's some connection, but it's not exceptionally strong. Teams confident in their running ability continue to take advantage. Still, it doesn't hurt to know how catchers are faring early, especially when considering marginal or middle-of-the-pack individual players. The following displays the number of steals attempted against and the success rate. That is, the lower the success rate, the better the team has been defensing steals:

Team

SB att

SB%

Orioles

11

36.4%

Rockies

11

54.5%

Giants

16

56.3%

Diamondbacks

7

57.1%

Rays

14

57.1%

Nationals

12

58.3%

Cubs

10

60.0%

Tigers

15

60.0%

Blue Jays

11

63.6%

Pirates

11

63.6%

Phillies

14

64.3%

Twins

9

66.7%

Indians

10

70.0%

Rangers

14

71.4%

Angels

15

73.3%

Padres

15

73.3%

Royals

12

75.0%

Brewers

13

76.9%

Athletics

18

77.8%

Braves

9

77.8%

Mariners

18

77.8%

Astros

14

78.6%

Red Sox

14

78.6%

Cardinals

5

80.0%

Reds

15

80.0%

Mets

16

81.3%

Marlins

6

83.3%

White Sox

14

85.7%

Yankees

18

88.9%

Dodgers

10

90.0%

The season is barely three weeks old, but so far, it's a mistake to run against Baltimore. Though, with the quality of their pitching staff, why would you? On the other hand, once word gets out, look for the Dodgers, Marlins and Cardinals to be challenged more often.

An argument can be tendered it's too early to base decisions on limited data. However, with fewer steals in today's game, every individual bag is that much more relevant. Gaining even the slightest of edges can be the difference between winning and losing. The data presented aids in unearthing players with a chance to run more, as well as a platform to help decide when to utilize them in your lineups.

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ABOUT THE AUTHOR
Todd Zola
Todd has been writing about fantasy baseball since 1997. He won NL Tout Wars and Mixed LABR in 2016 as well as a multi-time league winner in the National Fantasy Baseball Championship. Todd is now setting his sights even higher: The Rotowire Staff League. Lord Zola, as he's known in the industry, won the 2013 FSWA Fantasy Baseball Article of the Year award and was named the 2017 FSWA Fantasy Baseball Writer of the Year. Todd is a five-time FSWA awards finalist.
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