Breaking Down the Aging Curve: Early 20s

If you missed the first part and want a little more explanation about what I am doing click here.  I am going to start getting into the meat today with larger sample sizes and more typical groups of players.

Age 21 cohort:

There were 102 players in this group, three played only 1 season and were removed.  This is not as necessary with this group, but it becomes pretty important in the later cohorts as you will see.  The main thing is that for the max % part it is automatically 100% for the first year for any player with only one full season.  The 99 players left have an average number of 10.3 full seasons in the majors, so less than the previous cohorts as expected but still long careers on average.  There were 10 players that posted their max wRC+ in that first full season, and 9 posted their max WAR.  Said another way, about 90% of the players went on to have their best season later in their careers making it unlikely that a 21 year-old reaching the 300 PA plateau minimum is showing you a career year.  Again, part of this is that they on average have 9+ seasons to go so they have a lot of opportunities to have better years which the older cohorts will not have.

We also start to see something else I was expecting.  The players who max out in their first year tend to have shorter careers because they are not as good of players on average and that first year max was not very high.  Those that maxed wRC+ averaged only slightly over 4 years of 300+ PAs, and the ones that maxed WAR were only 3.25 years on average (with one active player in the group.  There is some overlap, but the two groups are different and will be for every cohort.  It is likely the trend here continues as well.  If you max WAR your first season it means you are not showing overall improvement later and leave the league quickly.  Those that max wRC+ but not WAR are likely getting more playing time later due to defense or other peripheral skills that are making them better players overall.  On to the max % chart:
 photo 21percentofmaxchart_zps33a3ba20.jpg

It looks like there is some slight improvement in the first couple of years in hitting.  The increase is more drastic in WAR, partly because those that stick in the majors get more playing time and thus accumulate more WAR, but the increase might be more than that especially if the slight uptick in hitting is for real, though I will spend more time trying to tease that out after I have this base run through all the cohorts done.  You will notice that these players peak younger than our traditional understanding of peaks.  The group peak is around 24 and hitting stays around that level until their early 30s, but the WAR starts dropping the next season.

Age 22 cohort:

This group started with 200 players of which 41 only played 1 season and were removed.  The one season group in this case held a lot of current young players such as Wil Myers and Yasiel Puig, so this might be an interesting group to follow over the coming years.  The average tenure of the remaining 159 players was 8.6 full seasons.  Of those 159, 27 had their best wRC+ in their first season and 26 had their best WAR.  Now instead of 90% having better seasons later in their careers, we are down to 83 or 84%.  About one out of every six 22 year-olds never improve on their first full season.  The average number of full seasons for those that did max in year 1 was 4 years for both wRC+ max and the WAR max group with the second being only a few hundredths of years below the first.
 photo 22percentofmaxchart_zps34ed058b.jpg

The chart shows a less distinct increase in the first few seasons, but is upward sloping for both wRC+ and WAR until the age 26 season.  There is a similar decline pattern to the 21 year-old group.  The 21 cohort just had a steeper early incline and younger peak.

Age 23 cohort:

Now we start getting into the largest cohorts.  The most likely time for a player to get their first full season is from ages 23 through 25, and if you haven’t made it by then your odds as a player of ever getting a full season in the majors start to drop off.  This age group started with 320 players total and 43 were removed as one year players like before 7 of which are active players.  Of the 277 left they average number of full seasons played was 7.6 and now 56 had max wRC+ in year 1 and 52 a max WAR.  That is nearing the mark where a full quarter of the players are never better than their first full season.  Of those that maxed in year 1, the wRC+ group had an average of 4.3 full seasons and the WAR group was 3.9 years.  Frank Thomas was in the max WAR group, so despite playing 14 more seasons above the 300+ PA  level after 1991 (only 240 PAs in 1990) he never posted a higher WAR.  He had 2 seasons where is wRC+ were equal or greater than that first one, but didn’t amass enough PAs to accumulate more WAR, though in 1997 he tied the WAR and wRC+ of that first full season.  Anyway, chart time:

 photo 23percentofmaxchart_zps2715039d.jpg

It’s harder to see much of any improvement in hitting with this group. There might be a slight improvement peaking in the 26 season again.  WAR shows an increase that is fairly steady until age 27 and then another similar decline phase.  Another thing to note, the hitting % of peak average at its peak is consistently in the low 80%.  For WAR it is declining so far.  If you look at the WAR line on the three charts, the first hits a peak of 60.3%, the second at 56.4%, and the third at 55.8% and might be worth keeping an eye on as we go on to the next set of cohorts.  For now though I will wrap it up rather than going on for the 3 or 4 thousand words all of the cohorts and summaries might take.

Newest Most Voted
Inline Feedbacks
View all comments
9 years ago

The case of Albert Pujols still seems unbelievable in how he came up at age 21 and immediately dominated Major League pitching then continued doing so for the next decade.

9 years ago

I think this is a very interesting series you are putting together, as I would like to know how players peak relative to their entrance into the league. That being said, I think that by using a rate stat for hitting and a counting stat for overall performance isn’t the best way to go about showing that. I’d like to see percent of max WAR per PA used as well, because I think that at least part of the increase in performance you are seeing is due to increased playing time.

9 years ago
Reply to  Brian Henry

Thanks for responding, I’m looking forward to seeing where you go with this project.