A few weeks ago, I began the process of determining an underperformance metric. In the article, I laid out the groundwork determining the drop off in plate appearances (PA) and production (wOBA). With these thresholds, I created several metrics, each with its own advantages and disadvantages. I’m not setting the values into stone yet but I’m getting closer to a solution. I’ve found a few value I like better than others.

In the original article, I found fantasy owners considered a drop in 220 PA from 600 PA (37% drop) and of 0.035 wOBA from .350 wOBA (10%) to be the thresholds. I didn’t mess with these two values. Besides the pair, I wanted to know when both occurred. Additionally, from a discussion in the comments, I found when either PA or wOBA thresholds where met and when both dropped close to, but not over, the thresholds. This value (called Minor Drop) I found to provide the most overall value.

Read the rest of this entry »

Every year we have a number of players who make their debut towards the end of the season, wildly exceed expectations, and leave us wondering what the future may hold. Last year we had Gary Sanchez. This year, Rhys Hoskins.

Hoskins hit the ground running. I mean, how many guys reach double digit homers before they reach double digit singles? I could probably look it up, I’m not going to. I don’t want to know. Hoskins did it, and that’s good enough for me.

Read the rest of this entry »

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.

Read the rest of this entry »

I have spent the past few years creating a family of stats that I’ve called xStats. These stats use Statcast batted ball metrics to analyze each player, which I then manipulate and export in a manner I hope is useful for fans and analysts.

Exit Velocity and launch angle data are good, and I include those, but they aren’t yet intuitive for more baseball fans so I have set forth to display my data in terms of numbers that are more relatable. Namely the standard slash line numbers. I have expected batting average, on base percentage, slugging percentage, batting average on balls in play, and weighted on base average. For pitchers I have bbFIP, which is an ERA scalar. Today, though I’m only going to be looking at batters.

These stats are available, but they don’t help much unless you know how well they are working. To that end, I have created the following table, which compares the regular, standard slash line to the xStats slash line. Read the rest of this entry »

Happy Game 7 Day!

About a year ago I released my (2017) Top 50 Fantasy Prospect rankings using the Prospect Scorecard to weight a variety of important variables in the context of fantasy baseball.  Today I’m publishing an (early) expanded list of the Top 100 Fantasy Prospects for 2018 for both Ottoneu’s FanGraphs Points leagues (where wOBA is a key measure on offense) and Roto leagues (5 x 5).

A few quick notes before we begin:

• Since “Cost” is league-dependent (auction salary, keeper round, etc.), I’ve ignored it here for simplicity by keeping it constant for every prospect listed. Feel free to use the Scorecard to make changes that reflect true player costs for your league, which will impact these rankings.
• These rankings below are intended to represent the 100 most valuable prospects for fantasy leagues (depending on scoring format).
• It’s quite possible I’m missing an obvious player that should be ranked, so let me know in the comments.  We can discuss the specific rationale for player rankings in the comments, too.  Player ages are current ages.
• For a lot more prospect resources, check out the Ottoneu community.

Here are the (early) 2018 Top 100 prospects for the linear-weights-based FanGraphs Points scoring format (a good proxy for those in OBP leagues):

Read the rest of this entry »

Most fantasy owners expect drafted players to under and over perform some amount. When a player overperforms, the owner looks and feels great because they “knew” a breakout was coming. Owners hope they didn’t pick too many players on the other end of the spectrum. The underperformers are the ones who drag down a team and owners find as escape goats for a bad season. I’m going to start laying the groundwork to determine a hitter’s disappointment chances.

The first major step in finding a disappointing hitter is to define what is a disappointment. After owning too many fantasy teams over the years, I’ve had my share of disappointments (e.g. Brandon Webb in a 2009 first round) and feel they are just part of the game. This ambivalence doesn’t mean I shouldn’t know the breakout chances. Even small changes in the odds can make a major difference after rostering 20 or more players.

Read the rest of this entry »

Justin Vibber has released his final 2017 dollar values by player.  I’ve captured Ottoneu average player salaries as of the end of the season (prior to inflation and arbitration).  Let’s combine the two to determine which hitters were the best bargains of 2017, and take a quick look at what might be in the crystal ball for 2018.

Read the rest of this entry »

Last week I laid out my plans for combining prospect grades and “scoutable” traits to help project major league performance. Finally, I’m able to output projections with encouraging results. Just by using traits people can scout with their eyes, I created a set of projections which competes with Steamer projections. Additionally, it helps point to the traits people should look for in prospects.

Previously, I tried to use just the five traits prospects get graded on (Hit, Power, Speed, Field, and Arm) to come up with a player’s value. I found the Speed and Power grades useful but came to the following conclusion on the Hit grade:

Basically, the Hit tool is a useless component to determine hitter value as it’s currently being distributed.

The more I thought about the Hit tool, the more I concluded that it’s trying to evaluate too much information (examples of different Hit tool definitions).

For these projections, I matched up the traits hitters display with common stats. To start with, here are the core traits I decided to utilize:
Read the rest of this entry »

Last offseason I committed to finding if there was any information to be gleaned from prospect grades. Sometimes the grades were useful. Other times not at all. While I made some conclusions, many are still unanswered. Over the next few weeks, I going to try to find those answers.

I’m heading down the path with an unknown timetable or conclusion. My goal is to take scoutable hitter traits and come up with a usable projection system. For inputs, I will use the standard five 20-80 scouting traits of Bat, Power, Speed, Defense, and Arm. Using just these factors last year, I found an OK estimate of a player’s projection.

Read the rest of this entry »

(10/9: Thanks to everyone for the additions.)

One player class I target for potential bargains are hitters who played through injuries. These injuries drag down a player’s production as they and their team struggle with the tradeoff of a regular player at 80% or a replacement at 100%. With the season just ending and drafts months away, I want to create a draft season reference list while people still remember parts of the 2017 season.

A few years back, I examined the negative effects of playing through injuries, mainly power. In the following season, those effects are gone for hitters.

Read the rest of this entry »