This past weekend, I was in Phoenix for Baseball HQ’s First Pitch forum. It’s an intensive few days of catching up with old friends and focusing on the upcoming fantasy baseball season. There was an underlying theme of the weekend, the fantasy baseball game is being forced to change. Some game facets have experienced some massive adjustments. The following are some of the meta-trends which have quickly popped up over the past few seasons.

Home runs are way up

A few days ago I wrote the following incorrect statement about Carlos Martinez for a 2018 player preview.

His 1.19 HR/9 will likely drop back below the league average.

It was pointed out to me, his home run rate was below league average. I was for sure it was not near 1.20 but I was wrong. Here are the recent league-wide HR/9 values.

2014: 0.86
2015: 1.02
2016: 1.17
2017: 1.27

I remember when the HR/9 hovered around 1.0. Not anymore. Some other pitching stats are feeling the effects of the jump like ERA, but the root cause is more home runs.

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Last year I interviewed Brent Daily, winner of the 2016 Ottoneu Champions league.  This year I’ve done the same by  interviewing Keith Smith, who led his Harrisburg Mayflies to a dominant victory in 2017.

Q: Well done on a big victory in 2017.  How long have you been playing fantasy baseball?

I started playing in the late 80’s. I forget the exact year but I remember Carney Lansford dominating. Stepped away for a number of years but got hooked again when a friend introduced me to Ottoneu.

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Sunday, October 15th is a significant signpost for the fantasy baseball off-season as it marks the beginning of Ottoneu arbitration, the 30 day process that helps leagues maintain competitive, economic balance. Ottoneu offers a ton of great features in its standard platform, but there are few more intimidating to a brand new owner than this annual salary-sharing arbitration event. Here is a summary of the more popular “allocation” option:

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Dear Disengaged Owner,

This has been hard for you in the past, but please read carefully.  Today, we are officially ending our relationship.

I wish I could say it’s been fun, but I think we both know this is long overdue.  As good as your original intentions may have been when you first joined our league, this is no longer meant to be.  But don’t worry, it’s not me, it’s you.  

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Ownership percentages are from CBS leagues.

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We’ll be writing each day up again like last week, but here’s a quick primer on the pitching slate next week for possibly available arms.

*all stats cited for the 2nd half unless otherwise noted

Lefty

Tyler Anderson v. MIA – It is in Coors, but MIA has the 4th-worst wOBA v. lefties (.304) in the second half thanks to just a .126 ISO.

Brent Suter v. CIN – CIN has the 26th wOBA v. lefties (.305).

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Continuing our series of looking at widely available starters who might be worth a stream down the stretch, here is a look at Sunday. Tough slate with a general lack of really intriguing arms and then some of the ones who are appealing have to face very difficult matchups. These are ranked in order of how much I like them:

Luiz Gohara, ATL (4%) v. PHI (Pivetta)

He walked four in four during his MLB debut, but he’s been walk-free in his last two starts – both against Washington – allowing five earned in 12.3 IP with 10 K. Facing Texas and then Washington twice to open your MLB career is brutal, so this will be his best matchup by far. The Phillies are 27th in wOBA against lefties with a .308 mark. You might want to hang onto him for next week at Miami if this goes well.

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I’m continuing Jeff’s series of looking at widely available starters who might be worth a stream in the final days of the season. I think Jeff was using a 10% or lower threshold, but I bumped it to 20% for one guy because I think he’ll still be out there in a ton of leagues and worth a scoop. These are ranked in order of how much I like them, but I’ll have a concise ranking at the bottom that shows the drop offs in confidence:

Tyler Chatwood, COL (18%) at SF (Moore)

Chatwood on the road has been one of the more bankable streamers for the last two seasons. Last year, he posted a nice 1.69 ERA in 80 IP away from Coors, in spite of a meager 1.7 K/BB ratio. He’s up to 3.41 in 71.3 IP this year while actually lowering his K/BB down to 1.5. He has a career 1.67 ERA, 0.91 WHIP, and 3.0 K/BB ratio at AT&T Park over 43 IP, including just 1 ER in 22 IP there since the start of last year.

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Ottoneu, like most fantasy leagues, uses a soft innings cap. This is pretty standard. You have an innings limit of 1,500 IP, and the day that you go over that innings limit, you are able to exceed it by as many innings as possible. How can we use this rule in our pursuit of a league championship?

Looking at Ottoneu specifically, though easily adjustable to any league format, you would want to get as close as possible to your innings limit, then on the last day, fill out your pitching lineup with players who are pitching that day. For example, start the day you plan to go over with 1,499 IP and throw 5 starters that day, with 5 RP in your lineup as well. Practically, this could get you another ~25-40 innings. Even if these innings fell below replacement level, they are still valuable as they would not be points you would otherwise accrue. Even if your pitchers were terrible across the board you would be looking at a lower bound of around 50 points, with an upper limit in the 250 point range. That’s a big gain on competitors who may not deploy the same tactic.

This is the main reason I recommend pacing your innings at 1,550 to 1,600 all year. It allows the flexibility to wait a week or two to pick your last day to blow up your pitching totals. Read the rest of this entry »

Predicting bat speed using the publicly available Statcast data is easier said than done. For much of the past few years there was a section on Baseball Savant which displayed a bat speed number of each player, but without much explanation for how it may be calculated. I haven’t inquired for an explanation, but I feel rather comfortable saying it was probably a derived stat using a formula published by Alan Nathan.

This formula takes the pitch speed and batted ball speed, and manipulates them using laboratory tested values for the various relevant coefficients–basically the bounciness of the ball and the bounciness of the bat. If you assume values for those coefficients, you can get a rough estimate for bat speed by plugging in the pitch speed and batted ball speed.

I don’t have proof that this is how bat speed was being estimated by Baseball Savant, but I feel it is the most likely explanation for the numbers.

Two weeks ago I proposed a formula for estimating future exit velocity using past exit velocity and launch angles. This method is far from perfect, and there is a whole lot more research that can be conducted into this area.

Over the past week I have been thinking about what performance changes may or may not be predictable from one season to another. Part of the variance that we see from season to season are large dips or climbs in offensive production, which often in retrospect we might be able to explain. Maybe there were signs that pointed towards decline, but we overlooked them for one reason or another. Maybe we didn’t know what the signs meant until further research had been conducted.

No doubt, these mistakes are often due to a lack of information. In some cases it may be bat speed. We don’t really know how much of a role bat speed plays between seasons or during the course of a career. We don’t know how injury plays a role with bat speed, nor do we understand the aging curve. Read the rest of this entry »