With the season starting, new useful information will finally become available. Let me know if I can provide any hard to get information in which other analysts aren’t providing. I will continue trying to notice injured players, provide Quick Looks at new/suspect pitchers, give velocity updates, and prospect comparisons. Other writers can provide normal group-think information. Let me know where I can provide that early edge.

The principal shareholder in the Rays, Stuart Sternberg, discussed how finding and developing the new frontiers provides competitive advantages.

Maybe, Sternberg said, it’s by falling behind, taking a lead from companies that follow Starbucks into good locations, copy Apple electronics or make generic drugs.
“I think where the advantage for us is going forward — and it’s going to sound crazy — is to try to allow all, and I will say all, these other organizations to devote enormous resources, and that’s not just money but thinking, brain power and devotion, to things that will have very little payoff, while those resources, brainpower and money might be better spent somewhere else,” he said.

“You build it, you invest all the (research and development), you devote everything you can and like a drug company, I’ll do the generic version for nothing, and I’ll undersell you. And while you’re doing that, I’ll worry about some other stuff over here.

“Everything I’ve seen, it’s an arms race right now, and guys are using elephant guns to kill mosquitoes.”

No matter what the target, the Rays have to find a way to get back ahead.

“There’s always going to be new frontiers,” Bloom said. “If we don’t find them, somebody else will.”

Let me know which frontiers we can explore together.

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Roster moves are continuously happening. I know I’ll miss a few but here is some information on the more fantasy relevant moves. As more news comes out over the weekend and I find time, I will add to the list any information I find useful.

• Adalberto Mejia is the Twins fifth starter.

Early this offseason I stated:

A pitcher I am keeping my eye on is the Twins Adalberto Mejia. No one has reported any of the lefties pitches as plus but he may have four average pitches with above average control. He throws his lowest rated pitch, the curve, hard. Hard curves (80 mph plus) are more successful than slow curves so even his worst pitch can be useful. If he continues to post good minor league strikeout and walk numbers, he could move into a bad Twins rotation quickly.

He isn’t immediately rosterable in most leagues. I will though try to catch his first start and see what’s behind the 9.5 K/9 in AAA.

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A couple of weeks ago, I examined the prospect Hit tool grade and how it provides useless information as it is currently being distributed. It’s time to dive back in. First, I am going to answer a couple questions which have come up on the topic and then get into my recommended changes.

Are there any systematic differences between Baseball America’s grades and those from MLB.com?

This study was easy. I grouped all players who had grades from both sources in the same season and I found the average differences.  The following table contain the averaged difference of the Baseball America grade minus the MLB.com grade for the 154 matched pairs.

The final differences are small with Baseball American being higher on power while MLB.com is higher on Speed and Defense.

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Spring Training Velocity Extravaganza

After my Tout Wars weekend, I found time to update the spring training velocities. Here are some pitchers seeing significant changes.

Cole Hamels

Hamels’s fastball average 91.5 mph on the 21st and down to 90.8 mph on the 26th. Last season it averaged 92.6 mph. I would be diving in more on Hamels but his velocity starts low every season.

While he starts slow, owners should closely monitor his velocity to make sure it starts ticking up.

Jake Arrieta

I am less optimistic on Arrieta. He is seeing a similar drop in velocity to Hamels at ~2.0 mph.

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Tout Wars Weekend

This past weekend, I participated in the 15-team Tout Wars mixed auction. Participated is a misleading term. Survived is probably more accurate. The auctioneer, Jeff Erickson of Rotowire, keeps the auction moving along at a pace which barely allows a person to find a player’s bid value yet alone perform any in auction calculations. Most of the breaks aren’t breaks. They are used to catch up with your team and assess the rest of the league.

Additionally, the location added difficulty. We bid in an open New York City bar on a Saturday afternoon into the evening. It was not a quiet venue. Since I am about 3/4 deaf, it made hearing everything hard at times. Additionally, as the auction went from afternoon to evening, our location lost its window lighting and morphed into the bar’s dimly lit romantic location. It might be great for singles hoping to score but it forced me to read my printed rankings from my laptop’s light. Even with the challenging conditions, the auction process was great.

I came with a plan of taking Mike Trout and Clayton Kershaw and then filling in my team with $10 options and four $1 plays. With Trout and Kershaw, I found over the past three seasons, no owner has spent over $38 on Kershaw and $48 on Trout. My valuation had both valued more than those top values. These two were the only two top players who went close to their perceived values with heavy inflation for the top 30 or so stars. I devised a predraft plan on allocating the rest of my money on the other 21 players after dropping closing to $90 on just the two players. My backup plan was to just to go with my normal value centered approach. Within four nominations, the auction dictated I switch to the alternate plan.

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Somehow I weaseled myself out of doing 2016 BOLD predictions. No luck this year. Paul has implemented released his Shocky Monkeys and I am forced to make some sort of fact-based BOLD predictions.

Note: For ADP values, I used NFBC for this season and will use our auction calculator for end-of-season values.

BOLD prediction #1: Trea Turner will perform 20 spots worse than his ADP suggests.

I am not down on Turner one bit but nothing points to him being a top 10 fantasy hitter. Unless a person projects out his 2016 for a full season. I feel comfortable taking him around pick 20 overall but he will likely never last that long. I was going to say never but he has lasted to the 20 pick in at least one NFBC league.

I find the most projection variance with first or second-year players. It takes just one person of the 10 to 20 people in the draft to have an overly optimistic projection to bump up the value. Or they have a fear of missing out on the next big thing. Turner has a range of 1st overall to that 20th ranking. The two hitters going before or after Turner, Manny Machado (4th to 12th) Josh Donaldson (8th to 20th) have a tighter ADP range. Someone else can take the chance and I will grab last year’s 1st round phenom, Carlos Correa, a few picks later.

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Earlier in the offseason, I examined out how reported Hit tool grades compared to actual MLB batting averages. I called the process a “mess” but figured it had some value. When I implemented the formula on MLB.com’s 2017 grades, commenters had the following to say about the projected batting average values:

“… not enough differentiation there in my opinion”
“… adjust your outputs to create more difference..”
“… hoping the table would be more conclusive…”
“…way too tightly grouped to the mean…”
“…it’s better to have no projection than to project everyone to be average…”
“… regressing too much to the mean…”
“… hit tool grades should be ignored…”
“…hit tool is undervalued in prospect analysis…”

I have no issue with the hit values being regressed to the mean. What I do have a problem with is if the hit tool is not measuring the correct factors. I needed to find out if reported hit grades provide any value. The following is a detailed look at how the hit tool is graded and how it fails to predict one simple factor, a hitter’s ability to get hits.

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Quick looks

3/15 games

I had full game information and write-ups on each of the following three pitchers but my computer did a restart and the information was lost. Here are the condensed versions from what I remember.

• Lucas Giolito: He was a mess. His velocity is still down from his minor league reports by about 3 mph. He couldn’t throw his curveball near the strike zone. He only lasted 2/3rds of an inning with his replacement, Chris Beck, showing more promise. I am not rostering Giolito in any redraft league and recently traded Giolito for Reynaldo Lopez and Curtis Granderson in an industry 20-team dynasty league.
• James Paxton: Looked similar to 2016. No issues here.
• Cody Reed: Not ownable in redraft leagues. He throws, not pitches, with a low 3/4 arm angle which is devastating to lefties but righties can tee off on him (.131 ISO vs LHH, .385 ISO vs RHH in ‘16). Also, he can’t throw is his change for strikes (35% Zone%), so he will have issues keeping righties from waiting on the fastball. Now, if he can get ahead, his two breaking pitches, change and slider, can get some swings-and-misses so he’ll get some strikeouts. I can see the pieces which have scouts hoping but he has not put them together yet.

3/16 games Read the rest of this entry »

In the middle to late rounds of a draft, pitchers seem to blend together. Picking between two similar pitchers can be difficult. To help with these decisions, I have created a simple cheat sheet to determine which pitcher has an easier path to success based on several outside factors like schedule strength and bullpen quality.

The chart is simple. I went through each factor which may influence a pitcher’s prediction in which they have no control over. I collected projections on each metric and then found the z-score for each value. Greater than 0 is good, less than zero is bad. Then for each team, I added up the z-scores for a final overall value.

The cheat chart is not perfect. It’s to be used as a guide. For example, if a pitcher is a heavy groundball pitcher, the user may not want to add the team’s outfield defense and home park home run factor. A different user may have the perfect projection set except for bullpen and defense. They can ignore the rest of the information. Additionally, a user may want to create their own category weightings. Again, this is just a guide.

To start with, here are the categories and the where I got the values.

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• At Farnam Street, they recently quoted Richard Nisbett on how humans attribute blame.

Our susceptibility to the fundamental attribution error—overestimating the role of traits and underestimating the importance of situations—has implications for everything from how to select employees to how to teach moral behavior.

After covering injuries for years, I think this a great way to divide injury causes between factors out the player’s control (hit in the head with a pitch) to those he controls (hurting a back carrying deer up steps with Todd Helton).

Two hitters whose value has taken a hit from injuries are Bryce Harper and Giancarlo Stanton. Here’s how I would step through the procedure to divide the blame starting with Harper.

Here are his injuries over the past three seasons and how much blame I would give to him.

• ’13 Knee (DL): Ran into wall fielding ball. 60%
• ’14 Thumb (DL): Head first slide. 85%
• ’16 Shoulder (speculation): Unknown and head first slide. Too much unknown for much blame. 20%

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