Temper Your Expectations: Boom/Bust All-Stars

Aug 12, 2014
Temper Your Expectations: Boom/Bust All-Stars

Part 2 of the “Temper Your Expectations” series explored how we can use standard deviation and scoring rates within 4for4's weekly projections to identify boom/bust candidates at running back and wide receiver. We uncovered specific players and player types that were projected to score more often than usual. Now we'll take a look at actual stats from the last two seasons to see if players that were highlighted by the projections actually do tend to score in bunches.

Running Backs

Expected Scoring Rates for Top-24 RBs, 2011-13

Fantasy Points/Touch (FP/t) Touches/TD (t/TD)

Average

0.69

30.54

Standard Deviation

0.12

13.17

Going back to our scoring rates, recent history suggests that most running backs score between 0.57 and 0.81 standard FP/t and find the end zone roughly once every 31 touches, but touchdown rate normally varies between 17.37 and 43.71 touches.

Recall that 4for4's week to week projected scoring rates suggested that pass catching backs with decent scoring opportunities, players like Danny Woodhead and Darren Sproles, were the best boom/bust running back candidates. Over the past two seasons, only six running backs scored fantasy points at a clip at least 1 standard deviation above the mean, and only one back scored at a rate 2 standard deviations above the mean.

RBs Scoring 2 STD Above Mean, 2012-13

Player FP/t t/TD

Darren Sproles

0.97

20.58

Shane Vereen

0.93

20.13

Danny Woodhead

0.88

19.87

Mike Tolbert

0.88

14.93

Marcel Reece

0.86

37.81

Roy Helu

0.82

23.25

Data from the past two years suggests that 4for4 has been able to accurately predict running backs that are going to score fantasy points at a higher rate than usual.

The term “goal-line” back is thrown around a lot in football circles, but from a touchdown rate and boom/bust perspective, Mike Tolbert may be the only true “goal-line” specialist in the league with 16 touchdowns on just 209 touches over the last two seasons. While Tolbert is the only back in this group that has a t/TD ratio more than 1 standard deviation below the mean, all of these running backs, except for Marcel Reece, score more often than usual and find the end zone at least 0.5 standard deviations better than expected.

Wide Receivers

Expected Scoring Rates for Top-36 WRs, 2011-13

Fantasy Points/Reception (FP/rec) Receptions/TD (TD Rate)

Average

2.03

10.24

Standard Deviation

0.38

9.1

There was little to no evidence in 4for4's projections that suggested specific player types as wide receiver boom/bust candidates, but Kenny Stills, Terrance Williams, and Justin Hunter were the most frequent boom/bust candidatesin 2013 according to 4for4 projections.

12 receivers over the past two seasons recorded FP/rec numbers at least 1 standard deviation above the mean, but just 3 came in 2 standard deviations higher. All of the wide receiver boom/bust all stars scored touchdowns at an above average rate.

WRs Scoring 1 STD Above Mean, 2012-13

Player FP/rec Receptions/TD

Justin Hunter

3.30

4.50

Aldrick Robinson

3.14

5.80

Kenny Stills

2.97

6.40

Marquise Goodwin

2.68

5.67

Jerricho Cotchery

2.61

4.60

Jermaine Kearse

2.57

5.50

Robert Meachem

2.55

7.50

Riley Cooper

2.51

6.36

Ted Ginn

2.46

7.20

Josh Gordon

2.45

9.79

Marvin Jones

2.44

6.27

Andre Caldwell

2.42

5.33

As was the case with running backs, 4for4 has done a good job of projecting wide receivers that tend to score at a higher rate.

Bottom Line

4for4 is known for having some of the most accurate projections in the industry, but by digging deeper into the numbers, projections found here seem to accurately predict scoring rates, as well. This information is especially useful when we are trying to decide between a consistent player or high variance option.

Standard deviation is a fantastic mathematical calculation that can give us a reasonable range of expectations for fantasy scoring. When targeting boom/bust players, we're especially interested in the boom side of the variance, realizing that these specific players could easily bottom out.

Given an increased workload, players that perform well outside of statistical normalcy will almost always regress to the mean, but for fantasy purposes we can take advantage of players that tend to get the ball in mostly favorable situations and target them as boom/bust candidates when necessary.

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