Hittertron FAQ

Updated: | Maintained by

What is Hittertron?

Hittertron is the ultimate tool for identifing attractive short-term hitter pickups (aka streaming hitters) and to determine when to start/sit hitters on your roster. There are Daily and Weekly versions for both Roto and Points leagues.

Daily (Roto)

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Daily (Points)

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Do I need to be good at math to use it?


How many games do you project/value?

All MLB games for today + the next 6 days. Projections for next week (Mon-Sun) are available beginning on the preceding Friday.

What stats are projected?

The Roto version has Plate Appearances, At Bats, Hits, Runs, HR, RBIs, Stolen Bases, Walks, Strikeouts, AVG, OBP, SLG, OPS. The H2H version removes the ratio stats and adds 1B, 2B, 3B, and HBP. At Bats, Runs, HR, RBI, SB, and AVG Wins are then used to determine the value of each start in 5×5 12-team MLB fantasy baseball auction dollars (AB are used for valuing AVG – a 4 for 6 is more valuable than a 2 for 3).

What does $ represent?

12-team mixed league fantasy baseball auction dollars. Note that position eligibility is disregarded (i.e., catchers are not adjusted up, 1B are not adjusted down, etc).

Why do you rank players based on fantasy baseball auction dollars?

We feel auction dollars work well because they can be directly compared to pre-season $ values (for 12-team ESPN leagues) and our in-season and rest-of-season player raters.

We use a fantasy point formula for the Points version.

What does GT mean?

Game Time. It is set at Eastern Standard Time – e.g., 1 = 1PM EST. Any game times prior to 1PM are made negative (e.g., -12 for noon) for easier sorting.

What does %St mean?

The estimated likelihood that a player will start that day (e.g., 95 = 95% chance).

For today’s games, we re-run multiple times per day to factor in projected lineups. Players confirmed in today’s lineup are at 100 for today’s projections. Any players not in today’s lineup are removed from today’s projections.

How do you estimate playing time both for single games and for future games/next week?

There are several factors taken into consideration including: 1) The player’s role with the team (starter, platoon, utility, etc.), 2) Recent playing time, 3) Opposing pitcher (e.g., Jonny Gomes will have a much higher projected %St against LHP than RHP), and 4) Player’s roster status (if on DL or in minor leagues, not projected).

For single day $ values, the St% plays NO impact on the $ value. His value is binary – either he starts and is projected at that full $ value or he is sitting and worth $0. There is no point to discounting the $ value based on playing time (note: for leagues where you must pick up a player the night before, you typically would not bet on any hitter <75%).

This is not the case with weekly leagues where there are multiple playing time outcomes (e.g., play 7 games, play 5 games, etc.). To ensure that likelihood to start is accounted for, weekly projected stats are the sum of each day’s stats multiplied by the St%. For example, let’s say that Jarrod Dyson is projected to steal 0.4 bases each game for the next 7 days. That would sum up to 2.8 (7*0.4) in the weekly projections IF he was a 100% lock to start each game. If that projection is 50%, the projected SB would fall to 1.4 (7*0.4*0.5).

How do I sort by stat?

Click the column name to sort in descending order (most to least). Click a second time to sort in ascending order.

What are the text boxes under the column header for?

These are for filtering reports. Report filters allow you to limit the rows to only those that meet your criteria.

You can filter multiple fields at the same time.  Below are some examples:

Function Symbol Example Explanation
ANY MATCH ‘COL’ in Team field This would filter the results to only Colorado Rockie hitters.
OR | Edwin Encarnacion|Jose Bautistar in ‘Name’ This would display the stats only for Edwin Encarnacion and Jose Bautista.
NOT ! !SF in Opponent This would remove all hitters facing the Giants.
NOR ! | !SD|SF in ‘Team’ This would display the stats for all hitters EXCEPT Giants and Padres.
GREATER THAN > >10 in $U This would only display rows for hitters whose projected $ is greater than 10.
LESS THAN < <10 in $U This would only display rows for hitters whose projected $ is less than 10.
GREATER THAN OR EQUAL TO >= >=10 in $U This would only display rows for hitters whose projected $ is greater than or equal to 10.
LESS THAN OR EQUAL TO <= <=10 in $U This would only display rows for hitters whose projected $ is less than or equal to 10.

How do you project these stats?

The projections start with Steamer Rest of Season projections that are updated daily.  This is used for setting each player’s park-neutral baseline for HR/PA, BABIP, 1B/2B/3B rates, BB-rate, K-rate, HBP-rate and SB-rate based on how the hitter perform against the average lefty or righty (depending on the probable pitcher).

These stats are then adjusted by Razzball based on the following factors:  1) Quality of opposing pitching (both starter and projected relievers), 2) Park Factors, and 3) Whether the start is home vs away (hitters perform better at home than road). In addition, some of today’s stats are adjusted based on weather conditions. The primary method for balancing hitter and pitcher is the Odds Ratios devised by Bill James.

These ratios are multiplied into projected PA. These are based on last 15-30 days and adjust based on handedness of starting pitcher (e.g., Rajai Davis might hit higher in lineup vs LHP than RHP) as well as the quality of the pitchers and lineup (e.g., the worse the pitcher, more projected PAs for the team).

Runs and RBI projections factor projected lineup position, lineup strength, and opposing pitcher strength.

What is a good $ value for streaming a hitter?

This value will vary greatly based on the amount of players in your league’s waiver wire (driven by # of teams + bench sizes), how active your leaguemates are on the waiver wire, the MLB schedule, and the quality of the probable pitchers.

For 12-team mixed leagues, $10-$20 options for OF and Utility are common.

What gameday factors drive hitter $ values the most?

The #1 factor is if there is a game in Colorado. Mediocre hitters become $20+ hitters in Colorado.

The handedness of the pitcher and hitter play a notable role – LHP starting pitchers lead to both bigger boosts for righty hitters and plummeting $ for lefty hitters. (Vice versa for RHP but to a lesser extent). RH platoon hitters are almost always available on waivers since they get the short end of the playing time stick vs their lefty counterpart.

How do I identify hitters available in my league?

The ‘%OWN’ is based on our ultra-competitive 12-team MLB Razzball Commenter League ownership rates. Filtering this column to include only hitters owned in less than 80% of leagues (<80) is typically a good way to get rid of owned hitters.

How accurate are Hittertron projections?

This is a great question and the most difficult one to answer.

Our goal is to be the most honest, transparent projections on the Internet. We appointed a dedicated robot (the Ombotsman) to provide daily updates on our accuracy. Here are the results for every day of 2015 and every day from May to September 2014. There is a link on that page that provides instructions on how to read the results on that page.

We are confident enough (based on a significant amount of testing) that we put out an accuracy challenge to anyone who does Daily Fantasy Sports projections in mid-July 2015 (no takers to date).

There is a lot of noise when looking at accuracy at the daily level because there is huge volatility in day-by-day performance. Mike Trout will go 0-for-4 several games throughout the year. A #8 hitter will have a couple games where they get multiple R/RBI. But, over time, it is fair to hypothesize that this volatility averages out and it should be straightforward to demonstrate accuracy.

Here is the easiest way we have figured out how to demonstrate our accuracy.

Below is a distribution that includes every projected hitter start from July through September of 2015. The average projected $ value in Hittertron (HON_AVG$) projected for each bucket correlates nearly perfectly (0.953) with the $ average in each bucket.

Download Table as CSV
Note: Filters and sorting in the table below apply to the output!

# $Range Count HON_AVG$ ACT_AVG$ HON_STDDEV$ ACT_STDDEV$ <-7 -7-0 0-7 7-14 14-21 21-28 28-34 35+
$-7 to $0 924 -3.3 -3.48 2.03 93.28 57.8 6.9 3.1 1.2 1.2 1.7 2.6 25.4
$0 to $3.5 531 1.7 -1.02 1.02 98.01 57.6 7.2 4.3 1.1 0.9 2.4 2.1 24.3
$10.5 to $14 389 12.2 4.77 1.01 97.32 54.5 7.2 2.3 1.3 0.8 1.5 2.1 30.3
$14 to $17.5 350 15.7 17.40 1.02 107.16 50.9 8.9 2.9 0.6 0.3 1.4 1.1 34.0
$17.5 to $21 317 19.2 29.29 1.05 128.12 48.9 5.7 2.5 0.6 0.6 2.2 1.3 38.2
$21 to $28 503 24.3 25.87 2.01 121.62 49.3 6.6 2.8 0.6 1.2 2.6 2.4 34.6
$28 to $35 331 31.1 24.42 1.99 122.58 53.5 5.1 3.0 0.3 0.6 2.1 0.6 34.7
$3.5 to $7 487 5.2 8.14 0.98 102.06 55.4 4.9 3.3 0.6 0.4 0.8 3.1 31.4
$35+ 459 47.2 40.29 12.03 133.29 45.8 6.8 2.4 1.3 0.7 3.1 1.3 38.8
$7 to $10.5 451 8.7 8.07 0.98 107.94 55.7 5.5 4.9 0.7 0.4 0.7 2.4 29.7
<-$7 1265 -14.8 -14.22 6.01 91.06 64.3 6.0 5.1 1.4 0.9 1.5 0.8 20.1

The ACT_STDEV_PTS column underscores the crazy volatility found in hitter performances. The standard deviations for each range fall between $90-$130 which means that 68% of the time. A hitter projected at $20 is projected to fall between -$108 and $148. This is illustrated by the distribution showing the percent of time each hitter projection bucket (e.g., $10.5 to $14) fell into each actual $ bucket. As you can see, even the top hitting tier are worth negative value 45+% of the time.

There is nothing a daily projection system can do about this inherent volatility – the best measure of its success is how well it performs against the average. And Hittertron does well in that regard.

How do Hittertron projections compare to other projection sources?

Um, great!  Stupendous!

Honestly, hard to say. We do not have access to other subscription services. Googling uncovers the occasional  study that seems pretty favorable.

Here are some favorable results for the underlying Steamer/Razzball projections:

How often do you update/upgrade the methodology behind Hittertron?

We are constantly looking for ways to improve the projections. The extent we update/upgrade the methodology will vary based on 1) our access to additional data sets (e.g., weather), 2) free time to research and test any additions/changes and 3) inspiration.

2015 marked a huge year in terms of overhauling/upgrading the methodology and one of the key reasons why the accuracy (as measured by the Ombotsman) improved throughout 2015.

Can I customize the $ values to meet my league settings?

We are working on this for 2016.

Can I customize the $ values based on how I weight each category (e.g., I value K’s more than Win percentage because it is more reliable)?

We are working on this for 2016.


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