S.O.P.S.

Hello Baseball Fans,

Baseball statistics. When you read baseball statistics, whether it is the career total of a famed player or current in-season league stats, or when you look at projections for that Fantasy Baseball league draft (or mid-season free agent lists), have you wondered how to calibrate the players who do things at high levels, but in different fashions? Yes? Great! We do too!

One can look at who has the most HRs, the most RBI, the highest batting average, or the most stolen bases or many other ‘counting stats’ that are there for our entertainment and debate. But how do you calibrate who the best is? Yes, we have WAR (Wins Above Replacement) in its two forms (FanGraphs and Baseball-Reference, the latter being our preferred method), but that’s a super fancy formula and not always the best since it’s not a true ‘counting stat’, which are typically more fun.

So how can we get a ‘counting stat’ that imitates a sabre-like stat? We need something that calibrates the power, average, walk, and speed guys into one convenient offensive category. OPS (On-base Plus Slugging) is a huge saber-metric marker. This takes a player’s On Base Percentage (OBP) and adds that to the Slugging Percentage (S). The MLB average here is typically about 0.725 where someone may have a 0.325 OBP and a 0.400 S (slugging formula is (1B + 2Bx2 + 3Bx3 + HRx4)/At-Bats). An OPS of .850 and above is great, 0.900 is all-star status, and 1.000 is MVP-type material.

But from our View From The Dish, OPS does not analyze the combined picture when it comes to comparing our favorite batting average and stolen bases leader type players with our favorite doubles and home run hitting type players. OPS favors the power hitters here as long as they are getting on base at a relatively decent clip overall. A classic example is four singles only equals to one home run in the slugging calculation while that ‘slugger’ may have K’d a couple times in the same game!

Here is our proposed solution. We will work with OBP straight up as is currently defined:

OBP = (Hits + Walks + Hit by Pitch) ÷ (At Bats + Walks + Hit by Pitch + Sacrifice Flies).

Next, we’re going to get creative (and hopefully ingenious, haha, as well) by adding our new invention called SSLG rather than SLG to OBP. SSLG is defined as Stolen bases factored into SLugging Percentage, which equates to adding a Total Base to the slugging percentage aspect.

To account for this, SSLG must include Plate Appearances as its denominator of the formula as opposed to at-bats as mentioned above. While we will credit for Walk (BB) and Stolen Base (SB), we will also be cognizant of Caught Stealing and deduct for it as a result. This will improve accuracy as the runner has gained or been credited with a base in some fashion via his plate appearance but then ‘gave’ it back by making an out on the basepath whether he was at fault or not. The formula for SSLG is as follows:

SSLG = (BB + SB – CS + 1B + 2Bx2 + 3Bx3 + HRx4)/Plate Appearances

Where are we going you might ask? We’re going to the top of the page. SOPS is the new stat! It is Stolen Bases factored into OPS.

SOPS = OBP + SSLG.

To follow up on why we want this accessory of a comparison for the fantasy league owners and stat analyzers out there, we have some examples of how this looks at current players on a larger scale. All stats below are from www.baseball-reference.com and are 2024 season stats through all games played as of May 24, 2024. To demonstrate, we have three players who all dominate a game in their own fashion. So let’s use SOPS to analyze their ’24 seasons a bit more closely than OPS can.

Shoehei Ohtani OPS = 1.035 Elly de la Cruz OPS = 0.805; Gunnar Henderson OPS = 0.969

In looking at the range of these three players, it appears as Ohtani is much more powerful, and thus often viewed as more valuable, than de la Cruz, while Henderson is somewhat close at second and perhaps a good/great combination of power and skill/speed.

Now, when we take their OBPs straight up as OPS did, we have

Shoehei Ohtani OBP = 0.409; Elly de la Cruz OBP = 0.343; Gunnar Henderson OBP = 0.362

To get our new S-SOP, we just need to calculate our SSLG. Without showing all the dirty math work, here is the SSLG for each player below:

Ohtani: SSLG = 0.710 de la Cruz SSLG = 0.978 Henderson SSLG = 0.679.

You may be able to recognize these SSLG numbers as VERY high compared to typical SLG values. Two reasons for this are these guys are VERY good and FREAKS of baseball right now. Second, they specifically have skills on the base paths in addition to possessing well above average SLG values.

Finally, let’s see the OPS added to the newfound SSLG for all three:

Ohtani: 0.409 OBP + 0.710 SSLG = 1.119 SOPS de la Cruz: 0.343 OBP + 0.635 SSLG = 0.978 SOPS Henderson: 0.362 OBP + 0.679 SSLG = 1.041 SOPS

de la Cruz has stolen 31 bases and only been caught 5 times. He was on pace for 100 stolen bases, which has not been done since Vince Coleman in 1987! This netted him 26 more Total Bases. As a result, we can factor in and appreciate his base path skill as it numerically closed the gap in ‘value’ by trailing Ohtani by only 0.141 percentage points in SOPS compared to trailing Ohtani by a 0.230 mark in OPS. Henderson’s gap actually lengthened a tad bit from 0.066 OPS to 0.078 SOPS in part because of his ‘lower’ amount of 7 stolen bases versus 0 times caught stealing because Ohtani has actually swiped 13 bags himself while getting caught 0 times as well!! We bet that was unexpected! Ohtani is rolling! (and does not play defense this year, but that is not relevant now,ha)!!

This is just an example of three players who basically can do it all as each has a handful of stolen bases and at least a few handfuls of extra base hits two months into the season. There may be a few at-bats or plate appearances to double check on as possible oversights into the makeup of this formula, but the impact is minimal at best where out of 500+ plate appearances in a season, it is possible five or so are miscategorized or duplicated towards these calculations. Aside from that, we will do more comparisons for some players who are not powerful but hit for high average and steal bags as well as for players who are powerful but don’t get on base at a high rate nor steal bases. We think the results will be useful relative to gaining a better view of who is more valuable or playing better offensive baseball. One-stop shop was the goal here and the SOPS tool seems like our possible new favorite going forward.

Later Baseball Fans.