I’m not here to bring any answers, only to provide some degree of entertainment for those who like numbers.
A question that frequently that frequently comes up is our coaches’ ability to develop hitters, especially over the recent past. There are a thousand ways to look at this, but one theory is that, if we are able to develop hitters, then our better players should have improved statistics over their careers. The reason I say better players is that even the best recruiters swing and miss.
This is how I tried to take a first look at this. To define our ‘better’ players, I used all of our players who played at least one season in the CCBL since 2014 and played at least 2 seasons at VU (so that we could identify a change from year to year). The best I can tell, there are 22 of them.
Then, I divided them into two groups: those who played their last season at VU during or before 2019, and those who played their last season during or after 2021. I did this for a couple reasons. For one, I believe we all see that our offense has fallen off after 2019. This also divides them into those who played > 2 years under Baxter (he became hitting coach in 2018).
Below are the batting averages, OBP, SLG, and OPS by year of eligibility for all 22 players, and then for the two groups. I should say that the unit of analysis is the at bat, not the player (this way, a player who got only 10 at bats his freshman year doesn’t have equal weight as one who got 100, although I do understand that both views have their merits).
Anyhow, below are the data. I will not make any comments until later, because I do have my (absolutely useless) opinion. I know this isn’t the easiest or best way to look at the data, but I know some of you like to play with it yourself.
Included players:
2021+
Espinal (4), Holcomb (2), Diaz(3), Keegan (3), Bradfield Jr( 3), Bulger (4), Delay (3), Vaz (2), Davis (2), Rogers (3), Vastine (4), Austin (3)
2019
Reynolds (3), Kaiser (3), Paul (4), Kendall (3), Bleday (3), Infante (4), DeMarco (2), Clarke (2), Scott (4), Toffey (3)
A question that frequently that frequently comes up is our coaches’ ability to develop hitters, especially over the recent past. There are a thousand ways to look at this, but one theory is that, if we are able to develop hitters, then our better players should have improved statistics over their careers. The reason I say better players is that even the best recruiters swing and miss.
This is how I tried to take a first look at this. To define our ‘better’ players, I used all of our players who played at least one season in the CCBL since 2014 and played at least 2 seasons at VU (so that we could identify a change from year to year). The best I can tell, there are 22 of them.
Then, I divided them into two groups: those who played their last season at VU during or before 2019, and those who played their last season during or after 2021. I did this for a couple reasons. For one, I believe we all see that our offense has fallen off after 2019. This also divides them into those who played > 2 years under Baxter (he became hitting coach in 2018).
Below are the batting averages, OBP, SLG, and OPS by year of eligibility for all 22 players, and then for the two groups. I should say that the unit of analysis is the at bat, not the player (this way, a player who got only 10 at bats his freshman year doesn’t have equal weight as one who got 100, although I do understand that both views have their merits).
Anyhow, below are the data. I will not make any comments until later, because I do have my (absolutely useless) opinion. I know this isn’t the easiest or best way to look at the data, but I know some of you like to play with it yourself.
Included players:
2021+
Espinal (4), Holcomb (2), Diaz(3), Keegan (3), Bradfield Jr( 3), Bulger (4), Delay (3), Vaz (2), Davis (2), Rogers (3), Vastine (4), Austin (3)
2019
Reynolds (3), Kaiser (3), Paul (4), Kendall (3), Bleday (3), Infante (4), DeMarco (2), Clarke (2), Scott (4), Toffey (3)
All | At Bats | AVG | OBP | SLG | OPS |
| Yr 1 | 3083 | 0.281 | 0.376 | 0.417 | 0.794 |
| Yr 2 | 4006 | 0.293 | 0.383 | 0.462 | 0.844 |
| Yr 3 | 3285 | 0.288 | 0.394 | 0.498 | 0.892 |
| Yr 4 | 1220 | 0.290 | 0.386 | 0.504 | 0.890 |
| Ending 2019 | |||||
| Yr 1 | 1737 | 0.290 | 0.377 | 0.448 | 0.825 |
| Yr 2 | 2119 | 0.290 | 0.381 | 0.444 | 0.824 |
| Yr 3 | 1744 | 0.296 | 0.409 | 0.538 | 0.947 |
| Yr 4 | 737 | 0.296 | 0.391 | 0.516 | 0.907 |
| Ending 2021+ | |||||
| Yr 1 | 1346 | 0.270 | 0.375 | 0.377 | 0.753 |
| Yr 2 | 1887 | 0.297 | 0.385 | 0.482 | 0.867 |
| Yr 3 | 1541 | 0.279 | 0.376 | 0.453 | 0.829 |
| Yr 4 | 483 | 0.282 | 0.378 | 0.487 | 0.864 |
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