﻿ Rotisserie Category Aging Patterns | The Hardball Times

# Rotisserie Category Aging Patterns

Projecting aging patterns helps teams and fans understand when a player’s talent peaks. Most aging studies measure a player’s overall talent, while fantasy owners care less about real-life talent, with stolen bases and pitcher wins dominating the discussion. For this article, I’m going to examine how standard Rotisserie league stats age.

Knowing aging patterns and weighting them correctly can give a fantasy owner an advantage when valuing players for a single season or for keeper or dynasty leagues. I’ll be using just one type of league setup, which can be frustrating to some owners as hundreds of different leagues types exist. I can’t cover every option, so I’m going with the most common. The following information can still be used in a wide variety of formats to get a reasonable idea of how players age.

### Technical Stuff

For the few readers who care about the math behind the procedure, it’s in this section. For the sane individuals, skip ahead to the Results section.

First, here are the standard 5×5 roto categories to be aged:

Hitters

• Runs Scored (R)
• Home Runs (HR)
• Runs Batted In (RBI)
• Batting Average (AVG)
• Stolen Bases (SB)

Pitchers

• Wins (W)
• Strikeouts (K)
• Walks plus hits per inning pitched (WHIP)
• Earned Runs Allowed (ERA)
• Saves are ignored. Saves are only given out to those pitchers whom the manager deems worthy of pitching the last inning of a close game. Since a pitcher has no control over this category, it will not be evaluated.

For the aging curves, I used a rate of change with 600 plate appearances for hitters and 160 innings for pitchers.

Additionally, the individual aging factors are combined into a single all-encompassing metric. Standing Gain Points (SGP) is used since it takes the five separate roto values and combines them into a single value-based number. For my equation, I calculated it using the 2017 15-team, NFBC Main Event standings. Here are the two equations.

• Hitter SGP: HR/5.77+R/12.6+RBI/13.5+SB/4.4+ ((((1703 +H)/(6,292+ AB))- .2706)/.00124)
• Pitcher SGP: W/2.25+SV/4.87+K/14.57+((3.83- ((ER+590)*(9/(IP+1,385))))/.0450)+((1.241-((1,719+H+BB)/(IP+1385)))/.0091))

Finally, the aging curves were created by the delta method, which weights plate appearances using their harmonic means. With this method, there’s a small survivor bias summarized by Mitchel Lichtman at The Hardball Times:

… survivor bias, an inherent defect in the delta method, which is that the pool of players who see the light of day at the end of a season (and live to play another day the following year) tend to have gotten lucky in Year 1 and will see a “false” drop in Year 2 even if their true talent were to remain the same. This survivor bias will tend to push down the overall peak age and magnify the decrease in performance (or mitigate the increase) at all age intervals.

Additionally, to mitigate the effects a changing environment (e.g. juiced ball), a small adjustment was added to balance out league-wide trends.

### Hitter Results

With the technicalities out of the way, here are the hitter aging curves, with analysis following the graphs.

Individual curves: On-base percentage curve added for reference.

A Hardball Times Update
Goodbye for now.

Of these curves, two major factors are in play: speed and power. A human’s sprint speed begins a free fall with a peak around age 22. This slowing down obviously affects stolen bases. Speed also influences the run-RBI mix and batting average. Young, fast hitters will hit near the top of the lineup to start their careers, generating more runs than RBI. As they age and get more power, they tend to move down the lineup into a more run-producing slot. With AVG, the additional speed helps hitters leg out a few more infield hits.

With the standard five hitting categories, speed is a larger factor than in real life. The other disparity between the real-life aging and fantasy curves is walks. Hitters peak with walks later in their career (see OBP curve).

By using the above aging levels, projecting a hitter at 600 PA, and using this year’s SGP formula, here’s the overall aging curve:

After a small early bump up, 5×5 standard roto hitters start an immediate decline. Power may peak later, but on average it’s all downhill, with the slope getting steeper and steeper each year.

These curves project aging for the average player, but most batters will not be balanced. They’ll lean to either end of the speed-power spectrum. For those hitters who rely on their speed, the talent drop likely will be steeper (e.g. Andrew McCutchen) than for power-only hitters (e.g. Edwin Encarnacion). This difference can lead to a better player targeting strategy in all league types.

The key, while intuitive, is this: Owners can focus their resources on older power hitters. When it comes to speed and batting average, look to younger hitters. In keeper and dynasty leagues, owners may want to trade “balanced” hitters for power-only guys, as the power hitters are likely to keep more of their value as they age.

## Pitcher Results

Individual curves from starting pitchers.

Two offsetting factors–declining strikeouts and walks–help prop up a pitcher’s fantasy until around age 27. Injuries and age start costing a pitcher velocity and strikeouts almost immediately. These losses are offset by an improved walk rate. Once a pitcher’s WHIP starts increasing, there is nothing to hold up his value, and it’s basically a free-fall from there. Fewer strikeouts and walks lead to a higher ERA and fewer wins.

The overall curve is fairly projectable, and here is how the various factors work together using the above mentioned SGP formula.

The roto-aging curve shape is like the overall pitcher-aging curves. On average, it’s a steep decline, but it may not be steady for each individual pitcher because the talent drop is injury and/or velocity related.

To mitigate the drop effects, fantasy owners constantly need to focus on young pitching. While it may be ideal to own only pitchers 27 years old or younger, it may not be feasible. I usually set a limit at 30 years old for my top three to four starting pitchers. This talent drop is why of the top four starting pitcher targets (Clayton Kershaw, Max Scherzer, Chris Sale and Corey Kluber), I prefer Sale because he’s the youngest (and healthiest).

Fantasy owners have baked this aging pattern into their disdain for pitchers. Pitchers rarely go in the first round of drafts. (This year is an exception.) In standard auctions, pitchers should be priced at an average of about \$11.5 (\$260/23 total players), but examining historical leagues, the actual average cost is closer to \$9.5.

To help show the increased decline for pitchers, here are both the hitter and pitcher SGP curves.

While hitters start the decline earlier, pitchers drop faster once their talent heads south. This difference leads to owners in keeper or dynasty leagues targeting hitters and scrounging for pitchers.

To wrap up the findings, here are the major points for owners to focus on:

1. In 5×5 roto leagues that count batting average, speed is a major factor. Hitters don’t peak; they start at a plateau and steadily decline.
2. Target sluggers in keeper or dynasty league formats to limit the speed decline effects.
3. With strikeouts and walks offsetting each other, pitchers maintain a relatively constant value until their age-27 season, and then a major decline starts.

Getting old sucks just as much for baseball players as it does for the rest of us mortals. While hitters are able to gain strength and pitchers quit walking batters for a few seasons, their fantasy values start a downward trend by their mid-to-late 20s. The biggest difference between these Roto and normal aging curves is the absence of walks for hitters. Knowing this difference can help owners gain a small advantage, especially in keeper and dynasty league where any edge can help.

### References and Resources

Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.
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Ryan Brockmember
6 years ago

https://www.fangraphs.com/community/on-the-use-of-aging-curves-for-fantasy-baseball/ Back in ’16 I looked at this and broke it down further into aging curves for Playing Time vs. Rate Stats vs. Overall. One interesting finding was that IP was a major factor for starters, so when you separate starters and relievers, you see that starters’ fantasy values drop off much more rapidly in their 30’s as they lose time to injury/become bullpen guys.

Pirates Hurdles
6 years ago

I still feel like this is biased at the young ages, as the only players good enough to play full time at age 22 or 23 are stars. Where as the mid to late 20s are bogged down by more ordinary players. The only way to do this would be to look at individual player curves then do some type of paired analysis, unless that is what you are doing but is not apparent. A lot of this doesnt pass the smell test. Why would pitcher wins drop steadily at age 26, never to recover? Same for batting average that we know has a ton of variability?

Ryan Brockmember
6 years ago

Things tend not to pass the smell test when you make bad assumptions/don’t read the methodology. For example, why do you think pitchers *wouldn’t* drop steadily from age 26 onward?