Value vs. ADP: Players 51 to 100

In my last article, I examined the potential value differences between the top-50 rank players and their average draft position (ADP). Today, I will examine the next 50. While the first list contained quite a few players moving up, today’s list is a little more balanced with over and undervalued players.

One of the biggest takeaways from the first article was the extra replacement value catchers receive in a 2-catcher format. To simply explain the idea, I will turn to Joe Bryant who goes through a fitting example but with football.

The league’s bottom catchers are so bad so any catcher who can hit has good value. Evan Gattis being ranked #17 got most of the scrutiny in the rankings. As was pointed out, the projection may be high on the plate appearances but the process was still sound. Here is how Gattis compares to the last catcher ranked (Yan Gomes) and Francisco Lindor compared with the last middle infielder (Kolten Wong).

Positional Scarcity Comparison
Evan Gattis 0.254 30 73 87 2
Yan Gomes 0.232 9 26 29 1
Difference 0.022 21 47 58 1
Francisco Lindor 0.292 26 96 90 14
Kolten Wong 0.268 12 58 56 9
Difference 0.024 14 38 34 5

Yan Gomes is such a sink, especially with a total of 55 Runs+RBIs. It’s imperative to understand and value catchers correctly for each league formats. It’s a potentially huge advantage for those owners who spend the time. Read the rest of this entry »

Reviewing 2017 Pod Projections: Keon Broxton

Today let’s continue recapping one of my 2017 Pod Projections, this time heading to Milwaukee to discuss Keon Broxton. Coming off an intriguing half-season in 2016 that featured an exciting blend of power and speed, along with some clear flaws, he was a popular sleeper for 2017 and one whose projections people couldn’t really settle on. So what was I projecting and how did that compare to his actual results? Let’s find out.

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Time of Reckoning: Who Loses the Most in a Pitch Clock World?

I have never been supportive of pitch clocks. In fact, the first ever thing I wrote about baseball (formally), was an article in the Journal of Sports Sciences, illustrating how pitch clocks could elevate muscle fatigue in pitchers, possible contributing to increased injury risk. I also came up with a workload metric which factors in the time between pitches when calculating the number of Fatigue Units a pitcher can accumulate. I was pleased to read Travis Sawchik’s article on pace of play solutions, focusing on how it may be more on the batters than the pitchers when it comes to speeding up the games. Well, I was pleased until the last paragraph, where he proposed the ol’ 15 second pitch clock – but we’ll get there.

Despite evidence that suggests Pitch Clocks will not actually help the game in any substantial way, MLB keeps bringing them up as the golden ticket to solving pace of play issues.

The paper I published relied on predicted fatigue levels, and was essentially a modelling exercise. While the models were extensively tested, and empirically validated, there is always some concern when applying these types of findings to living, breathing pitchers. Thankfully, Yang and colleagues conducted a similar study in 2016, and found a 12 second pitch clock, compared to a 20 second pitch clock, would lead to lasting fatigue effects days after a pitching performance. If I sound like I’m beating the same drum over and over again, it’s because evidence is being ignored.

But blah blah blah, scientists are giving warnings. It’s 2017, that doesn’t mean anything anymore. What impact might this have on pitchers?

Using Fatigue Units, what influence would possible Pitch Clock rules have on pitcher workloads?

The PitchF/X data can be a bit noisey, so I had to make a few assumptions to the database. This included making some modifications and some assumptions to pace data. I calculated the average pace per inning by looking at the time of the last pitch, and the time of the first pitch every inning. Then, I divided this total time in seconds by the number of pitches thrown. If a pace was less than 10 seconds, I set the value to that of the 10th %ile value from 2017 – to 21.3 seconds. If a value was greater than the 90th %ile pace (27.5 seconds), I set the value to 27.5 seconds.

To simulate the effect of pitch clocks, I reduced the maximum time value by approximately 5% (26.5 seconds) to simulate the 20 second clock, and to 25.5 seconds to simulate the 15 second pitch clock. Both of these are not very accurate with respect to the proposed pitch clock time – but take into account, if someone is on base, the clock is turned off. Furthermore, Jon’s tweet up above shows that the paces are not really influenced significantly by the pitch clock. So, instead of using 15 seconds, or 20 seconds in the pitch clock conditions, I reduced the 90th %ile time by 5% to reflect the 15 second pitch clock condition, and 4% to represent the 20 second pitch clock condition.

Now that the paces were defined, I calculated Fatigue Units for the 2017 regular season. Setting a minimum of 500 pitches thrown, who would have the greatest change in their workloads?

Simulated Pitch Clock Influence on Workloads
Rank Name Pace (from FG) Fatigue Units (self) Fatigue Units (20 PC) Fatigue Units (15 PC) Change from Self to 20 PC Change from Self to 15 PC Inning Appearances Pitch Total
1 Aaron Bummer 21.5 5.90 7.38 7.66 125.15% 129.83% 59 897
2 Silvino Bracho 27.3 3.89 4.70 4.87 120.73% 124.93% 36 550
3 Dan Jennings 26.8 16.58 19.39 19.99 116.97% 120.57% 170 2607
4 Boone Logan 24.2 6.79 7.89 8.12 116.25% 119.65% 57 801
5 Chase Bradford 25.1 6.72 7.80 8.04 116.18% 119.70% 37 549
6 Alex Wood 24 12.00 13.64 14.03 113.66% 116.93% 64 952
7 Dustin McGowan 24.5 15.72 17.82 18.33 113.40% 116.62% 162 2637
8 Keynan Middleton 27.6 14.79 16.61 17.05 112.27% 115.28% 61 971
9 Zack Greinke 24.7 16.10 18.05 18.55 112.11% 115.21% 103 1344
10 Jerry Blevins 26.7 12.99 14.56 14.98 112.07% 115.35% 137 2177
11 Pedro Baez 31.1 17.50 19.55 20.04 111.71% 114.56% 182 2673
12 Heath Hembree 26.4 15.23 17.00 17.47 111.58% 114.70% 151 2377
13 Josh Hader 23.7 8.37 9.33 9.60 111.53% 114.75% 50 667
14 Cory Gearrin 29.8 13.62 15.13 15.55 111.08% 114.19% 57 829
15 Addison Reed 22.4 18.88 20.95 21.52 110.99% 114.01% 100 1082
16 Matt Albers 26.3 14.21 15.77 16.19 110.98% 113.95% 139 2282
17 Cam Bedrosian 29.9 8.73 9.68 9.95 110.93% 113.95% 61 966
18 David Hernandez 25.6 11.52 12.78 13.12 110.90% 113.83% 105 1795
19 Chris Smith 24.5 6.57 7.27 7.45 110.71% 113.47% 62 1044
20 Rex Brothers 28 4.88 5.40 5.55 110.64% 113.67% 40 652
21 Juan Minaya 24.7 10.82 11.97 12.30 110.62% 113.66% 48 652
22 Ryan Tepera 28.4 19.84 21.94 22.46 110.58% 113.20% 209 3025
23 Joe Kelly 29.4 13.73 15.16 15.58 110.39% 113.47% 54 881
24 Sergio Romo 27.4 11.40 12.56 12.88 110.21% 113.00% 124 2015
25 Mike Dunn 28.6 13.13 14.47 14.85 110.21% 113.08% 73 1024


Ok let’s get this out of the way – this is a real Bummer of a list. Moving on. To be noticed on here is the fact that only 2 starting pitchers appear in the top 25 of most impacted pitchers – Alex Wood at number 6, and Zack Greinke at number 9. Increased workloads are associated with increased risk of injury, and given Alex Wood‘s history, the pitch clock isn’t going to do him any favours.

The rest of these pitchers are all relievers. Given the findings from Travis’s article on pitcher pace, this isn’t really shocking. However, knowing what we know about injury trends, particularly for Tommy John Surgery, relievers are at a higher risk of injury. The Pitch Clocks would impact them the most.

I am not arguing there are no ways that we could speed up the game. In fact, I’m all for pitchers throwing pitches in quicker succession – but, this has to be because the pitcher feels they are ready to throw, and not because they are forced to throw. In the field of ergonomics, we use a technique called psychophysics to determine when a worker feels they could perform an action without an increased level of fatigue, or risk of injury.

Forcing pitchers to throw when they have not fully recovered is going to lower velocities, and possibly lead to an increased of injury. Pitchers will become more fatigued, a known risk factor for injury, if pitch clocks are used. Speed the game up, but don’t do it at the expense of pitchers. If the pitch clocks are enacted, fantasy owners should expect reliever volatility to continue to rise.

Full list of pitcher workloads and simulations of pitch clocks

Buying and Selling Clayton Kershaw

A fantasy baseball roster is an exercise in educated gambles. There are some players, like Clayton Kershaw, who are capable of singlehandedly delivering your team to the promised land – especially in a format like ottoneu FG points.

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Paul Sporer Baseball Chat – December 1st, 2017

Thanks to everyone for coming out!


Paul Sporer: Good afternoon, everyone! Get your questions in and we’ll get going very soon


Don Mattingly‘s Sideburns: Draft and hold rankings: Ohtani, Paxton, Keuchel, Quintana to pair with Darvish.


Paul Sporer: Still want to see where Ohtani lands, but he’s right in the area of those 3. I have all four top 25 with Darvish at 11


Silly Beane: Does Ahmed Rosario have any fantasy value in keeper leagues, or does he project as too glove-reliant for IRL value?


Paul Sporer: Depends on league type, but he definitely strikes me as someone who will be a better real life player than fantasy for at least the first couple years of his career


Jordan: Let’s say you’ve already got Ohtani in a dynasty league. Do you shop him? Is he the rare guy that’s simply more fun to have, regardless of outcome?

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Top 50 Ranked Players: Value vs. ADP

“Long ago, Ben Graham taught me that ‘Price is what you pay; value is what you get.’ Whether we’re talking about socks or stocks,

… or fantasy baseball players

I like buying quality merchandise when it is marked down.” –Warren Buffett

Collecting as much value (talented players) from as little possible resources (draft picks or auction dollars) is the key to starting off a winning fantasy season. From now until each draft, owners should be trying to calculate player values and the possible range of outcomes. With these value ranges in mind, owners can use their draft resources to get the best deals. It’s time to start finding those deals.

To find the bargains, player values first need to be calculated. To create the values, I will use the average final standings from the 32 leagues in the 2017 NFBC Main Event (15 team, 5×5 roto with AVG).

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How To Talk Trade 2.0

I once took an excellent training course on effective communication.  At the beginning of the course, our teacher started with a game:

In my hand is an envelop with a $10 bill inside.  I want one of you in this room to take the deal I’m offering you.  I’m going to ask you a simple trivia question and, if you get it right, you get the ten dollars.  But if you get it wrong, you owe me two dollars.  However, if you don’t know the answer, you can ask one person in the room for help.  Who wants to volunteer?

After a few moments of people looking at each other wondering what the catch might be, I volunteered.  “How many states make up the United States?”, he asked.

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A Minor Review of 2017: Minnesota Twins

The Twins system maybe doesn’t have the best depth but it has some impact hitters on the way — especially up the middle — and some intriguing arms.

The Graduate: Trevor Hildenberger, RHP: More moxie than stuff, Hildenberger survived his first taste of the Majors with a fastball that sat 88-89 mph. His changeup was the nasty go-to offering and his slider had just enough to keep hitters honest. Most importantly, the right-hander threw strikes and kept the ball down in the zone which helped him generate a ground-ball rate of close to 60%. Hildenberger had similar success in the minors and the Twins began to trust him with some key pitching situations. He’s not a big name and he doesn’t throw hard but he could be a key arm for the Twins in 2018.

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Using Curveball Spin to Predict Blisters

Pitching blisters were an afterthought just two years ago but the reported instances have jumped the past two seasons. Detailed accounts were written by Eno Sarris here at FanGraphs and Ben Lindbergh at the Ringer.

Throwing a curveball may be to blame according to Sarris:

But we can’t dismiss that chart completely. The players who have gone down with blister problems have thrown curves 14.9% of the time, far above the 10-11% baseball as a whole averaged over that timeframe. The players who ended up on the list more than once averaged 18.9% curveballs. Enough to say there’s some smoke here.

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Never Rebuild

Never rebuild – that’s my mantra. As a hard and fast rule, it’s a little too rigid to work in reality. However, as a rule of thumb, it’s a useful code of conduct. I have six leagues that can be described as a dynasty format. Occasionally, I do rebuild. Rosters break. We’re here to talk about those scenarios as well as why I believe rebuilding is for suckers.

Perhaps I should begin with a caveat. Avoiding rebuilds works for me. It’s a battle tested strategy that maps to my strengths and weaknesses as a fantasy player. Not every owner is like me. It’s possible that you should rebuild because it better fits your personal approach.

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