Trick question. Think outside the box.BTW-Who threw the first no-hitter at Dodgers Stadium?
I don't want to give it away but don't answer with the obvious Sandy Koufax.
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Trick question. Think outside the box.BTW-Who threw the first no-hitter at Dodgers Stadium?
I know the answer but like you said, people need to look outside the box. Hint 3. He was an LA player.Hint 1: The first two to throw no-nos were Jewish
Hint 2: Bo Knows Baseball
Very tricky WhiteBus! Well done.I know the answer but like you said, people need to look outside the box. Hint 3. He was an LA player.
I think it's where I remember the answer. Rookie. Got his no-no in his 4th or 5th start.Bo Belinsky - LA Angels
I think I asked this question last season.
Richie Allen?Incorrect.
As I said the former Phillie is hard.
I certainly understand why a Padres fan like you would think Soto is overrated. But he's in pretty good company on your 20/80 question, so maybe he's better than you give him credit for.Heard this one during the Phillies game the other day.
Juan Soto, who IMHO is the most overrated player in the game, is only the fourth player in MLB history to have 20 doubles and 80 walks at the All Star break. Name the other three.
Hints: They are all post 1950 so no really old timers.
Two are in the HOF.
The third is hard but he is a former Phillie.
Soto is an analytics dream. Mostly because he walks all the time. He probably walks too much. He takes borderline pitches that he needs to swing at in clutch situations. I watch at least 155 Padre games a year and you have to see him every day to see what I mean.I certainly understand why a Padres fan like you would think Soto is overrated. But he's in pretty good company on your 20/80 question, so maybe he's better than you give him credit for.
Bobby Abreau is the correct answer.Richie Allen?
This an issue I have with on-base-percentage. It treats a walk as being as good a hit. Sometimes that's true but not when there are runners in scoring position, two out, and a weaker hitter behind you. I understand the criticism of batting average -- it treats a walk as nothing, although at least it treats a walk better than an out. But equating a walk to a hit is not a perfect answer.Soto is an analytics dream. Mostly because he walks all the time. He probably walks too much. He takes borderline pitches that he needs to swing at in clutch situations. I watch at least 155 Padre games a year and you have to see him every day to see what I mean.
Is he a good player? Yes. Is he the generational type player some people have called him? No way.
This an issue I have with on-base-percentage. It treats a walk as being as good a hit. Sometimes that's true but not when there are runners in scoring position, two out, and a weaker hitter behind you. I understand the criticism of batting average -- it treats a walk as nothing, although at least it treats a walk better than an out. But equating a walk to a hit is not a perfect answer.
Re the Royals or other WS winners, the ‘80 hockey team, Buster Douglas, etc….why would prior metrics always match real time performance? They are just averages. The best on one day or week aren’t always the best the week, month or season before.
Because weaknesses are factored into the metrics too. If metrics say it's better to swing for the fences (hit HRs) and your lineup is only 10th or 20th best at it, opting to play small ball instead is a disadvantage. That's baked into the metrics.Agreed, sometimes a team catches lightning in a bottle. However, over the course of a season (vs a boxing match) results will skew towards the teams that are very good at something. The issue for me is that analytics has all of the teams trying to be good at the same thing.
If every team in basketball is launching threes for example, naturally the teams that are best at that will win the most.
Some would argue: why try to win any other way when the three point shot is the most efficient play in basketball? The home run most efficient in baseball? Etc
My answer would be that if other teams are significantly better at shooting threes or home runs, why would I try to be 10th or 20th best at it? Why not try something else that exploits their weakness?
(For example, although teams haven’t really started to return to a ground and pound game in football, I heard a stat last season that yards per carry up the middle were trending higher because teams aren’t signing big run stuff DTs in an era of pass offenses. Sure the passing attack is more efficient, but more teams that lack franchise QBs should be exploiting the relative cheapness of run blocking guards and RBs to push a dominating ground game that benefits from an era of defenses trying to protect against the air attack)
Because weaknesses are factored into the metrics too. If metrics say it's better to swing for the fences (hit HRs) and your lineup is only 10th or 20th best at it, opting to play small ball instead is a disadvantage. That's baked into the metrics.
Metrics say it wouldn't help you to shoot more 2s. Instead, focus on getting better at 3s.
The best militaries in the world have x fighter jets. Rather than increase jet spending to reach only #20 in jet counts, lets ramp up production instead on propeller aircraft !
You see, the favored approach is that for a reason. Metrics say it doesn't help to pursue a weaker strategy.
The best militaries in the world have more fighter jets. Rather than increase jet spending to reach only #20 in jet counts, lets ramp up production instead on propeller aircraft !
That's Soto. He drives in runs but mostly at meaningless times in games.that's true but not when there are runners in scoring position,
In his career or this year? His clutch stats this year look pretty good to me.That's Soto. He drives in runs but mostly at meaningless times in games.
Plus he's an absolute butcher in LF
Split | G | PA | AB | R | H | 2B | 3B | HR | RBI | SB | CS | BB | SO | BA | OBP | SLG | OPS | TB | GDP | HBP | SH | SF | IBB | ROE | BAbip | tOPS+ | sOPS+ |
2 outs, RISP | 38 | 46 | 34 | 15 | 10 | 2 | 0 | 1 | 14 | 1 | 0 | 12 | 7 | 0.294 | 0.478 | 0.441 | 0.92 | 15 | 0 | 0 | 0 | 0 | 4 | 1 | 0.346 | 104 | 152 |
Late & Close | 47 | 62 | 47 | 8 | 12 | 2 | 0 | 2 | 5 | 3 | 0 | 14 | 13 | 0.255 | 0.419 | 0.426 | 0.845 | 20 | 0 | 0 | 0 | 1 | 4 | 0 | 0.303 | 87 | 147 |
Tie Game | 83 | 135 | 103 | 17 | 28 | 7 | 0 | 9 | 22 | 3 | 0 | 29 | 31 | 0.272 | 0.43 | 0.602 | 1.032 | 62 | 3 | 1 | 0 | 2 | 5 | 1 | 0.292 | 126 | 183 |
Within 1 R | 91 | 220 | 174 | 27 | 45 | 13 | 0 | 10 | 27 | 4 | 3 | 42 | 55 | 0.259 | 0.4 | 0.506 | 0.906 | 88 | 3 | 1 | 0 | 3 | 5 | 1 | 0.313 | 99 | 148 |
Within 2 R | 94 | 302 | 236 | 35 | 58 | 16 | 0 | 11 | 32 | 5 | 3 | 62 | 69 | 0.246 | 0.401 | 0.453 | 0.854 | 107 | 5 | 1 | 0 | 3 | 5 | 1 | 0.296 | 89 | 137 |
Within 3 R | 94 | 353 | 275 | 43 | 69 | 18 | 0 | 15 | 39 | 6 | 3 | 74 | 78 | 0.251 | 0.408 | 0.48 | 0.888 | 132 | 5 | 1 | 0 | 3 | 7 | 1 | 0.292 | 96 | 145 |
Within 4 R | 96 | 375 | 290 | 47 | 74 | 18 | 0 | 15 | 40 | 6 | 3 | 81 | 79 | 0.255 | 0.416 | 0.472 | 0.888 | 137 | 5 | 1 | 0 | 3 | 7 | 1 | 0.297 | 96 | 146 |
Margin > 4 R | 31 | 50 | 40 | 8 | 13 | 5 | 0 | 2 | 14 | 0 | 0 | 9 | 7 | 0.325 | 0.44 | 0.6 | 1.04 | 24 | 1 | 0 | 0 | 1 | 1 | 1 | 0.344 | 128 | 177 |
Ahead | 58 | 164 | 126 | 26 | 34 | 11 | 0 | 5 | 21 | 1 | 1 | 37 | 33 | 0.27 | 0.433 | 0.476 | 0.909 | 60 | 1 | 0 | 0 | 1 | 3 | 1 | 0.326 | 101 | 147 |
Behind | 55 | 126 | 101 | 12 | 25 | 5 | 0 | 3 | 11 | 2 | 2 | 24 | 22 | 0.248 | 0.389 | 0.386 | 0.775 | 39 | 2 | 0 | 0 | 1 | 0 | 0 | 0.286 | 72 | 118 |
At the end of the day, every instance (every AB, every running play, etc) has a positive or negative outcome. Metrics tell you the percentages of each outcome.
You are suggesting to try other things that metrics doesn't suggest is the optimal approach. 'Exploiting weaknesses' is already factored into the math.
I did not know that Soto is a poor fielder. As you can see from the link, that was a problem at Washington. And, as you can also see from the link, lack of effort is a big part of the problem. https://www.talknats.com/2022/05/24/time-move-juan-soto-back-lf/That's Soto. He drives in runs but mostly at meaningless times in games.
Plus he's an absolute butcher in LF
What's considered the best medical treatment today may not be the best tomorrow, as more research is done and advances are discovered. Maybe someday all cancer will be curable. If you are saying that as different strategies are tried and new data are compiled, perhaps new strategies will prove best. Sure, of course. It's not a card game. Probabilities aren't fixed. Fences are moved in and out. Balls are juiced, then not juiced. Rules are changed.Yes I totally believe that’s true regarding outcomes. And I’m not anti-analytics as stated earlier in this thread. If I had to win a baseball game, and had infinite resources at my disposal to do so, I’d be layering OPS, exit velo hitters and high velo, high spin rate, high k rate pitchers. I believe the analytics when they say that would give me the best chance of success to win.
However, to your second point, we’re not talking about card games. All else being equal, your chance of drawing an ace from a deck of cards was the same 100 years ago as it is today. Backward looking is forward looking so long as the card dynamics remain the same. Not true in sports.
This is where the self-fulfilling prophecy comes in: metrics suggested station to station, home run dependent baseball 20 years ago based on the probability of scoring and frequency of home runs, therefore teams ran less while further increasing home run % and carried fewer players with speed / base running in their core skill sets…all of which only reinforces the statistical disadvantage to stealing bases. However, outside of the stole base data set is the reality that pitchers are tending to throw more breaking pitches than before, are employing max effort (often slowing down deliveries as they torque up for velocity), and so there may be significant upside vs the statistical probabilities if you can exploit these changes to the game with skilled base runners. And of course now with the bigger bases teams are taking it into consideration.
Because the game is dynamic the reality on the field of play does not have to mirror the statistical probabilities; tomorrow isn’t bound to be the same as yesterday the odds will change according to the gameplay…unlike a card game where the probabilities are set in stone.
What's considered the best medical treatment today may not be the best tomorrow, as more research is done and advances are discovered. Maybe someday all cancer will be curable. If you are saying that as different strategies are tried and new data are compiled, perhaps new strategies will prove best. Sure, of course. It's not a card game. Probabilities aren't fixed. Fences are moved in and out. Balls are juiced, then not juiced. Rules are changed.
If a team wants to deviate from metrics, attempting a new approach, perhaps something different will be discovered best. Existing data show otherwise, but as more data come in, who knows. But by not following the herd and existing data, you're likely hurting yourself.
generally I would say no, that last part is not correct. again, that's all factored into the metrics if they are advanced enough. metrics are more than everybody's collective average....they are the past outcome probabilities of the specific player in the specific scenario as close as can be approximated.Jumping around your post a little bit:
You are hurting yourself when you are playing the game the way the metrics suggest to play it, but you are worse than your opponents at playing that game. That is the opposite of good strategy. Going back to the beginning, that is my main point here and my biggest gripe with metrics-based approaches to sports today.
When it comes to the forward-looking blind spots in the metrics, I’m not talking about their inability to pick up on new developments or major changes to the sport (like rule changes), or even talking about new “discoveries.” It’s as simple as someone saying (pre-rule change) “hmm…pitchers are throwing a ton of sliders these days, maybe we can pick up extra bags with more speed on the roster — sure the data says SBs don’t add marginal runs, but that’s based on data from a generation of rosters composed of players built for station to station baseball”
At the end of the day you have to be good at something to win. And doing something that is statistically unfavorable, but doing it well, can be better than doing that is statistically favorable but doing it worse than your opponent — who is doing the exact same thing but better.
generally I would say no, that last part is not correct. again, that's all factored into the metrics if they are advanced enough. metrics are more than everybody's collective average....they are the past outcome probabilities of the specific player in the specific scenario as close as can be approximated.
Metrics will not suggest a player with no career home runs but good bat control should swing for the fences with no outs and a runner on second. Metrics will say bunt or hit the other way.
I have a lot of sympathy for your dislike of analytics. I just want to point out one thing. You say (correctly) that these days everyone uses analytics. But even before there were analytics, everyone used the same tools (ERA, batting average, RBIs); it's not as though some organizations used different evaluation methods as others.Perhaps we’re just talking about two different approaches of analytics. Play to play, of course you should align your defense where the guy is most likely to hit the ball. You should pitch where the opponent doesn’t hit well, etc.
I’m talking about the broader use of analytics to define how teams should be constructed and their general philosophy or approach to the game.
I have a lot of sympathy for your dislike of analytics. I just want to point out one thing. You say (correctly) that these days everyone uses analytics. But even before there were analytics, everyone used the same tools (ERA, batting average, RBIs); it's not as though some organizations used different evaluation methods as others.
I'm sure you know the saying that it's not the X's and the O's, but the Jimmies and the Joes. I think baseball is the same. While strategy -- the baseball equivalent of the X's and the O's -- is important, the key is to judge talent correctly and to coach it well. I don't know if you are a Phillies fan, but these traditionally have been Philly weaknesses.
Agree on the walking idea.Soto is an analytics dream. Mostly because he walks all the time. He probably walks too much. He takes borderline pitches that he needs to swing at in clutch situations. I watch at least 155 Padre games a year and you have to see him every day to see what I mean.
Is he a good player? Yes. Is he the generational type player some people have called him? No way.
Still no. Now you’re back to square 1. It’s already established that homers win so there’s no model that wins with small ball.Perhaps we’re just talking about two different approaches of analytics. Play to play, of course you should align your defense where the guy is most likely to hit the ball. You should pitch where the opponent doesn’t hit well, etc.
I’m talking about the broader use of analytics to define how teams should be constructed and their general philosophy or approach to the game.
Still no. Now you’re back to square 1. It’s already established that homers win so there’s no model that wins with small ball.
Assuming modern metrics show that starters should go 5, middle guys 3 and closer 1 (to simplify). No model will show it’s better to have your starters go 8.
Two thousand years of chess models show it’s better to have a queen and rook in the end game. No other model will show its better to have a bishop and two pawns.
Get it ? If home runs are proven more correlated to winning than singles and batting avg. then no, no model will simulate a roster constructed with singles hitters that is even more correlated with winning.
Explained another way. The optimally-designed small ball team would not be likely to finish higher in the standings than the optimally designed home run hitting team, so it’s not a strategy to follow.