First look at lucky RBIs

While clutch hitting is still a temperamental subject, it is relatively accepted now that it doesn’t really exist… or at least only to a small degree. Tangotiger penned an interesting article on this subject and found that from 1999-2002, the extent of clutch hitting was 2 runs per year by Jason Giambi and Miguel Tejada.

Now that that’s out of the way, let’s see how we can use this. I thought, to start on this subject, we’ll look at batting average with runners in scoring position. Similar to what we did with LIPS ERA and DIPS WHIP, we’ll look at batting average with runners in scoring position compared with regular batting average.

What this should tell us is which batters have been getting more RBIs than they are entitled to. If a hitter is batting higher with runners on second or third than they do normally, that batting average should be expected to regress to his typical batting average. When this happens, less runners will be scoring when said batter comes to the plate and that batter’s RBI rate will decrease accordingly.

This, of course, is by no means a perfect metric. Batting average in itself is flawed, but I still thought it might be interesting to look at the results. In the future, once I can establish a good expected batting average metric (which will be partially dependent on the creation of a good system for home runs, which I will be working on over the next few weeks), this tool will be much more effective.

For now, let’s just see what we come up with.

Lucky RBIs

Qualification: Batters need to have at least 300 at-bats, at least 70 at-bats with runners in scoring position, and a BA w/ RISP – BA greater than 0.40.

LASTFIRSTTEAMHABBAH_RISPAB_RISPBARISPBARISP-BAHRRBI
BardJoshPadres873290.26437900.4110.147343
GarciaparraNomarDodgers1114010.277401000.4000.123657
HernandezRamonOrioles743090.23930830.3610.122855
WillinghamJoshMarlins1314840.271461280.3590.0882187
SosaSammyRangers953820.249401240.3230.0741879
HartCoreyBrewers1234230.29134940.3620.0712068
YoungDelmonDevil Rays1665640.294551510.3640.0701281
FelizPedroGiants1254920.254371160.3190.0651865
JonesJacqueCubs1053950.266371120.3300.064554
IngeBrandonTigers1084460.242331080.3060.0641464
ThomeJimWhite Sox1013740.27028840.3330.0632579
BrownEmilRoyals813280.247341100.3090.062657
EncarnacionEdwinReds1244330.286411180.3470.0611162
OrdonezMagglioTigers1875280.354701690.4140.06026123
HillAaronBlue Jays1435280.271461400.3290.0581470
MolinaBengieGiants1234400.280461360.3380.0581777
BetancourtYunieskyMariners1364820.282421240.3390.057957
NadyXavierPirates1083750.28834990.3430.0551765
FrancoeurJeffBraves1675670.295561600.3500.0551791
TeahenMarkRoyals1364750.286431270.3390.053654
MartinezVictorIndians1545040.306471320.3560.05021101
YoungMichaelRangers1735620.308551540.3570.049773
FieldsJoshWhite Sox743120.23723810.2840.0471856
DeRosaMarkCubs1254310.290401190.3360.046865
MauerJoeTwins1063600.29433970.3400.046553
LugoJulioRed Sox1225100.239401410.2840.045667
LeeDerrekCubs1544930.312471320.3560.0441773
UptonBJDevil Rays1274050.314391090.3580.0442376
JeterDerekYankees1795630.318461270.3620.044962
GermanEstebanRoyals843130.26827870.3100.042334

Unlucky RBIs

Qualification: Batters need to have at least 300 at-bats, at least 70 at-bats with runners in scoring position, and a BA w/ RISP – BA less than -0.40.

LASTFIRSTTEAMHABBAH_RISPAB_RISPBARISPBARISP-BAHRRBI
IwamuraAkinoriDevil Rays1184140.28511700.157-0.128727
AmezagaAlfredoMarlins1003770.26513850.153-0.112228
BlakeCaseyIndians1425300.268271450.186-0.0821566
AusmusBradAstros763290.23114900.156-0.075324
LoftonKennyRangers963170.30313570.228-0.075723
WeeksRickieBrewers773330.23114860.163-0.068723
EcksteinDavidCardinals1113760.29518780.231-0.064226
YoungChrisDiamondbacks1195000.23817950.179-0.0592858
DiazMattBraves1063080.34422770.286-0.0581242
PierreJuanDodgers1725900.292301280.234-0.058036
PosadaJorgeYankees1504490.334401430.280-0.0541982
JacksonConorDiamondbacks1063800.27921930.226-0.0531351
WiggintonTyDevil Rays1043780.275241080.222-0.0531649
UribeJuanWhite Sox1014440.22717970.175-0.0521655
BeltreAdrianMariners1404990.281311350.230-0.0512386
GarkoRyanIndians1234210.292271120.241-0.0511652
GrandersonCurtisTigers1645490.299281130.248-0.0512068
PedroiaDustinRed Sox1444470.322291070.271-0.051645
CastilloLuisTwins1063490.30416630.254-0.050018
HafnerTravisIndians1234790.257281340.209-0.0482187
SchneiderBrianNationals843650.23018990.182-0.048646
EllisMarkAthletics1345070.264311430.217-0.0471760
TorrealbaYorvitRockies863390.254241160.207-0.047639
EstradaJohnnyBrewers1154100.280261100.236-0.044844
UgglaDanMarlins1365590.243311550.200-0.0432879
JohjimaKenjiMariners1254310.290311250.248-0.0421456
JonesChipperBraves 1494520.330371280.289-0.0412485
MatsuiHidekiYankees1424870.292361430.252-0.0402391

Concluding thoughts

And that’s that. Again, once we can come up with an awesome system for home runs, we should be able to calculate this with much more certainty. For now, I just thought this would be a fun exercise. If you’re going to try and use them immediately, make sure to carefully check the numbers.

There is no way Akinori Iwamura should only be batting .157 with batters in scoring position, and there is no way Delmon Young should be up at .364. The .286 batting average with runners in scoring position for a guy like Matt Diaz, though, is much closer to what is should be. He is only on the list because his actual batting average is .344 — completely unsustainable.

So be careful and these numbers can be pretty helpful. If nothing else, they are interesting and should lead to some interesting analysis down the line.

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