When it comes to Joltin’ Joe and Ted Williams, the idea that they might be “greater than we thought” seems downright silly. I mean, they were revered as the greatest players of their generation, deservedly so. But I did some digging with a couple of stats that I’ve worked on over time – something I call the Offense Effectiveness Ratio. This is (I keep mentioning him) my Bill James moment, so bear with me.
Bill loves to talk about two complex stats called Runs Created and Win Shares. He’s also been a cornerstone of the argument for Wins Over Replacement. I’m kind of so-so on these, myself. Even Bill has pulled back at times on the real value of statistics; the whole argument for the creation of his statistical models is to try to portray more of a player’s value to a team, hence the concept of Wins Over Replacement. My difficulty with this is twofold.
First – I point to the Derek Jeter model. Joe Dimaggio, actually, fits into this category too. There is no disputiing the significant value of these players; they’re both undisputed Hall of Famers, and you’d have a difficult time disputing that they would both be considered the 10 greatest Yankees of all time. Stats, too, will support this. But what can’t be measured in any logical way how these two players are considered the cornerstone of teams that are dynastys. Statistically, in actual fact, Dimaggio is not the offensive equal of Ted Williams. Williams trumps him in virtually every category, and not just in terms of their career numbers, but also comparing their best seasons. Most of us can remember that A-Rod was a shortstop until he moved to the Bronx, making him a peer to Jeter. While you’d almost certainly take Rodriguez well ahead of Jeter in a fantasy draft, you’d also almost certainly take Jeter first if you were an actual GM building an actual team. Why? Because Jeter was the undisputed leader of the best team in baseball – the type of guy Reggie Jackson referred to when he said “There are guys better than superstars”. It’s also what Leo Durocher meant when he said “Statistics are for losers”.
My second problem with the concept is that no one player can consistently win games by themselves. There are definitely significant ways that players can influence the outcomes of games, without doubt. To suggest that the Yankees have en equivalent chance to win a game whether they play Derek Jeter at shortstop or Edwin Nunez is a ridiculous argument. But my point is this. While Jeter can have a six-RBI game and make a dozen stellar plays for them in the field, if the pitching staff is putrid in the game, the Yankees are still likely to lose. One player is simply too dependent on the other 8 on the field to produce a winning product, and on that basis, the concept of attaching a player’s statistics to their team’s performance is flawed. The fundamental problem is suggesting that a player might be better, or worse, is connected to their team’s performance. While you might quickly think I’m wrong in calling that a problem, I’m really only suggesting the concept is backwards. A player isn’t better because his team is better; the team is better because the player is better.
So what’s my argument for a single offensive rating?
There are three things, and three things only that matter in a player’s contribution to an offense. (1) Getting on base; (2) Advancing on the basepaths; (3) Scoring runs. Pretty difficult to argue this one. Before you start talking about sacrifice bunts and hit and runs, keep in mind that’s part of #2, and sacrifice flies are part of #3. So here goes…
#1 – Getting on base. This, generally speaking,is a version of OPS, but I’ve always believed OPS is a very flawed statistic, and I’m amazed it’s even used. Why? Because it double counts singles. If a player gets a single, this is a total base, and a time reached base. But if a player walks instead, they only get a time reached base. The ultimate result is the same, but a single is counted twice in OPS while a walk is counted only once. And the base stealer is also penalized by OPS. Consider the OPS for a single at-bat. If a player walks, the OPS is 1.00; If a player gets a single, the OPS is 2.00. If a player doubles, their OPS is 3.00. But if a player walks and steals second, the OPS is still 1.00. Is not a player on second with a double and a player on second with a walk and steal a similar result? Of course it is….and yet the OPS fails to adequately reward the speedy player’s contribution. I also considered the risk of a player stealing a base getting thrown out – so here’s my formula to replace OPS.
Total Bases + Bases on Balls + Stolen Bases – Caught Stealing = Bases Earned.
This is my preliminary formula for calculating #1 and #2. above. So how about scoring runs? Quite simple actually.
Runs Scored + RBI – Home Runs = Run Involvement.
Several players are very successful at getting on base and putting themselves into a position to score runs. A classic example of this is the 1987 St. Louis Cardinals, who played themselves all the way to Game 7 of the World Series with only one player who hit more than 12 home runs (Jack Clark, 35 homers, 106 RBI). But they also had Willie McGee (11-105), Terry Pendleton (12-96), Tom Herr (2-83) and Ozzie Smith (0-75). How did they score so many runs, then? Quite simply, they were a track team at the top with Vince Coleman and Smith stealing 152 bases between them and scoring 225 runs. By the time the other hitters mentioned above came to the plate, the Cards were stitching together long rallies with singles, walks, sacrifices, steals, but rarely homers. Ozzie Smith, for one, was involved in 179 of his teams runs without hitting a single home run. In spite of the fact that Coleman led the team in runs scored and Clark led in RBI (Ozzie was actually 5th on the team in this category), he led the team in run involvement. While he would be considered the team MVP for his defensive showing alone, I’d contend that this stat enhances the reason why Ozzie is the only member of this squad in the Hall of Fame today.
So finally – to create a ratio…
Bases Earned + Run Involvement / Plate Appearances = Offensive Effectiveness Ratio
This quickly determines for you how effective (in general) a player is. This measures how far they get by themselves (bases earned), how they’ve affected others (RBI) and how others affect them (Runs scored).
Part of the reason that Bill constructed Win Shares and Wins Over Replacement was to create a single way to measure every player against every other player to ever play the game. Not to question this too much – but I can’t understand how you can measure Lefty Grove against Willie Mays, or Tim Raines against Babe Ruth. It’s just not realistic. What you can do, however, is measure Willie Mays against Hank Aaron, Roberto Clemente and Frank Robinson. You can measure Tim Raines against Lou Brock and Rickey Henderson. It’s a tool to compare similar players, and determine how they stack up against each other.
I hope you try this stat out. It will help give you a starting point in determining how your favorite player really stacks up in the grand scheme of things. I learned a lot from it, myself. If you want to start somewhere, pick the 15 or so modern age (post 1920) first basemen in the Hall of Fame and see how they all stac
k up. Have fun with it!