Injury risk has, and will, continue to play a role for LA as it does for all clubs. Yet, LA continues to compete at a very high level despite that. It's really an underappreciated story. Look at last year's decimation of the pitching staff. Add on the loss of Turner, Lux and Seager a year earlier....yet, LA still won an astounding 100 games.
Much is always made of their big trades and FA signings, but I've always been more impressed by their stellar player development efforts. They can identify talent and develop it with few equals outside of Tampa and perhaps a handful of others. Oh, and let's remember that the Dodgers rarely have a high Draft slot to help - other than Clayton Kershaw at #7
The young players continually in their pipeline provide capital for trades and replacements when overpriced free agents are allowed to walk. They give the front office incredible flexibility and a huge competitive advantage. Consider how many LA prospects get traded...and how many never really seem to meet expectations once they leave the Dodger system. Reclamation projects like Max Muncy further prove the point. A reject from the A's system, once subject to the Dodger development system Muncy quickly blossomed into a star.
The Dodgers demonstrate that sustained success at the major league level is arguably less about how much you spend, and more about what you invest in. Sure, winning high profile trades and free agent signings certainly helps, but those only work as a result of the grunt work of relentlessly identifying and developing top young talent...and not rushing it to the majors until it is ready.
Or, you can just ask my friend who is a diehard Mets fan...
Oh for sure. It's become a joke by now, "ho-hum, the Dodgers just churned out another ace pitching prospect and a position player who can play 7 different positions and have an .850 OPS". Their player development is unreal. But they do need to translate all of those great process-y things into postseason wins. That's the part they haven't figured out, although maybe it's an intractable problem.
I'll offer a theory, although, it will be wildly unpopular here. Here goes.
The Dodgers strike me as overly consumed by following crude averages for post-season in-game decisions. This has hurt them repeatedly as well known to Dodger fans - though there is some irony discussed below. It's been a frequent criticism of Roberts that he is robot-like in following the "averages." It is often suggested that Roberts remains the manager because he invariably does whatever the front office says in games.
Is a large sample ensemble average predictive of a single specific in-game decision at hand i.e. the single use case in front of you? Others will disagree, but I firmly believe it often is not - averages (e.g. the mean) are descriptive of how a specific data cohort has performed over time and is often not necessarily predictive. For example, understanding what Aaron Judge's batting average is year over year - the same data cohort i.e. Aaron Judge - is descriptive of his career, but not necessarily predictive of his 2024...and that's a narrow sample of one. The penumbra of a larger sample average might provide some predictive insight, but far less for a single in-game decision than is believed in my view.
Large sample averages invariably includes use cases that are irrelevant to the present in-game situation and are not easily corrected through a larger sample size comprised of even more irrelevant use cases. In this year's World Series, will what Oakland did in Miami in June or what Cincinnati did on a rainy April night in Colorado be relevant to a post-season game decision from say the Yankees against the Dodgers? It has been noted:
"...It is statistical error to apply the average of a group of data points to a single point and assume it to be true. Even assuming data is normally distributed (a “bell curve”), the probability that any one data point will be the same as the average is 50% — the same as a random guess." (See Eric Luellen, “Why Averages Are Often Wrong.” Medium, 24 Oct. 2018, towardsdatascience.com/why-averages-are-often-wrong-1ff08e409a5b.).
The irony was 2020. In the World Series, Tampa Bay manager Kevin Cash famously removed starter Blake Snell from a game to insert a reliever. Cash was relying on large crude averages (the third time through the lineup penalty over all games) in making his decision, but Snell had been unhittable, having thrown only seventy-eight pitches over 5-1/3 innings while allowing only one earned run, two hits, no walks, and nine strikeouts. Snell was dealing, and his pitch count suggested at least seven innings with the Dodgers who were in danger of losing a crucial Game 6.
Not surprisingly – as evidenced by the exuberance of the Dodgers in the dugout - the decision immediately blew up on Cash, and the Rays never recovered. Part of the problem was that for the use case in front him, the Cash seemed to have forgotten that the real "third time through the lineup penalty" was in using reliever Nick Anderson whose multiple appearances in THAT SERIES - made him very familiar to LA's hitters. The Dodgers won - ironically - by finding a more robotic manager mindlessly worshiping at the altar of averages.
Averages are great at a high strategic level for the bell curve of games during the regular season. They fall off quickly in the post-season where the teams are limited and much higher performing that seasonal averages reflect. The post-season involves teams sometimes described as “data outliers” relative the average - and their data and your post-season match ups and decisions are too.
When the post-season hits, the Dodgers need a manager who is sees the post-season as fundamentally different than the regular season. One who is able to use his experience and judgment to make the best decision from the single use case in front of him and not simply reading it off a sheet and hoping for the best all while weakly arguing in the post-game presser he made the "right" decision because "the analytics" says so.
More specifically perhaps, the Dodgers need a manager who might - I don't know - decide to go off script and pinch hit a limping Kirk Gibson in the 9th in a World Series because of the specific match up in front of him - I suspect that ain't Dave Roberts.
Injury risk has, and will, continue to play a role for LA as it does for all clubs. Yet, LA continues to compete at a very high level despite that. It's really an underappreciated story. Look at last year's decimation of the pitching staff. Add on the loss of Turner, Lux and Seager a year earlier....yet, LA still won an astounding 100 games.
Much is always made of their big trades and FA signings, but I've always been more impressed by their stellar player development efforts. They can identify talent and develop it with few equals outside of Tampa and perhaps a handful of others. Oh, and let's remember that the Dodgers rarely have a high Draft slot to help - other than Clayton Kershaw at #7
The young players continually in their pipeline provide capital for trades and replacements when overpriced free agents are allowed to walk. They give the front office incredible flexibility and a huge competitive advantage. Consider how many LA prospects get traded...and how many never really seem to meet expectations once they leave the Dodger system. Reclamation projects like Max Muncy further prove the point. A reject from the A's system, once subject to the Dodger development system Muncy quickly blossomed into a star.
The Dodgers demonstrate that sustained success at the major league level is arguably less about how much you spend, and more about what you invest in. Sure, winning high profile trades and free agent signings certainly helps, but those only work as a result of the grunt work of relentlessly identifying and developing top young talent...and not rushing it to the majors until it is ready.
Or, you can just ask my friend who is a diehard Mets fan...
Oh for sure. It's become a joke by now, "ho-hum, the Dodgers just churned out another ace pitching prospect and a position player who can play 7 different positions and have an .850 OPS". Their player development is unreal. But they do need to translate all of those great process-y things into postseason wins. That's the part they haven't figured out, although maybe it's an intractable problem.
I'll offer a theory, although, it will be wildly unpopular here. Here goes.
The Dodgers strike me as overly consumed by following crude averages for post-season in-game decisions. This has hurt them repeatedly as well known to Dodger fans - though there is some irony discussed below. It's been a frequent criticism of Roberts that he is robot-like in following the "averages." It is often suggested that Roberts remains the manager because he invariably does whatever the front office says in games.
Is a large sample ensemble average predictive of a single specific in-game decision at hand i.e. the single use case in front of you? Others will disagree, but I firmly believe it often is not - averages (e.g. the mean) are descriptive of how a specific data cohort has performed over time and is often not necessarily predictive. For example, understanding what Aaron Judge's batting average is year over year - the same data cohort i.e. Aaron Judge - is descriptive of his career, but not necessarily predictive of his 2024...and that's a narrow sample of one. The penumbra of a larger sample average might provide some predictive insight, but far less for a single in-game decision than is believed in my view.
Large sample averages invariably includes use cases that are irrelevant to the present in-game situation and are not easily corrected through a larger sample size comprised of even more irrelevant use cases. In this year's World Series, will what Oakland did in Miami in June or what Cincinnati did on a rainy April night in Colorado be relevant to a post-season game decision from say the Yankees against the Dodgers? It has been noted:
"...It is statistical error to apply the average of a group of data points to a single point and assume it to be true. Even assuming data is normally distributed (a “bell curve”), the probability that any one data point will be the same as the average is 50% — the same as a random guess." (See Eric Luellen, “Why Averages Are Often Wrong.” Medium, 24 Oct. 2018, towardsdatascience.com/why-averages-are-often-wrong-1ff08e409a5b.).
The irony was 2020. In the World Series, Tampa Bay manager Kevin Cash famously removed starter Blake Snell from a game to insert a reliever. Cash was relying on large crude averages (the third time through the lineup penalty over all games) in making his decision, but Snell had been unhittable, having thrown only seventy-eight pitches over 5-1/3 innings while allowing only one earned run, two hits, no walks, and nine strikeouts. Snell was dealing, and his pitch count suggested at least seven innings with the Dodgers who were in danger of losing a crucial Game 6.
Not surprisingly – as evidenced by the exuberance of the Dodgers in the dugout - the decision immediately blew up on Cash, and the Rays never recovered. Part of the problem was that for the use case in front him, the Cash seemed to have forgotten that the real "third time through the lineup penalty" was in using reliever Nick Anderson whose multiple appearances in THAT SERIES - made him very familiar to LA's hitters. The Dodgers won - ironically - by finding a more robotic manager mindlessly worshiping at the altar of averages.
Averages are great at a high strategic level for the bell curve of games during the regular season. They fall off quickly in the post-season where the teams are limited and much higher performing that seasonal averages reflect. The post-season involves teams sometimes described as “data outliers” relative the average - and their data and your post-season match ups and decisions are too.
When the post-season hits, the Dodgers need a manager who is sees the post-season as fundamentally different than the regular season. One who is able to use his experience and judgment to make the best decision from the single use case in front of him and not simply reading it off a sheet and hoping for the best all while weakly arguing in the post-game presser he made the "right" decision because "the analytics" says so.
More specifically perhaps, the Dodgers need a manager who might - I don't know - decide to go off script and pinch hit a limping Kirk Gibson in the 9th in a World Series because of the specific match up in front of him - I suspect that ain't Dave Roberts.