# Year: 2022

• ## The Ultimate PER Guide | Untangling John Hollinger’s Analytics Lovechild

(Image via Bleacher Report)

Player Efficiency Rating (PER) was the turning point for basketball analytics in the public domain; but with time comes controversy. Lots will claim that PER is an outdated metric, that recent efforts of all-in-one metrics have left PER useless. Let’s say this is true, and for good reason. PER has a limited scope compared to lots of modern metrics, which incorporated Plus/Minus and tracking data that seems to map a player’s value to an objectively greater degree than the box score. Let us be reminded that this is a good thing! More advancements means more descriptive power among these all-in-one metrics, so the science of player analysis has undergone significant evolution since Hollinger’s initial effort. So, as a brief summation, PER is NOT one of the absolute best measures of player impact for the modern era. But like any other subject with a rich history, there is value in going back to appreciate tradition. Let us explore the inner workings of PER. What makes it good or bad, and why should or shouldn’t you use it?

How PER Works

PER puts the “E” in “Efficiency” because it was designed as a fairer comparison between high-volume superstars and role players. Like lots of modern impact metrics, PER is a per-possession metric that estimates a player’s effect on his team’s point differential [1]. But instead of using advanced, complex mathematical modeling to accomplish its results, PER is grounded in concept and critical thinking. It works so that each box score statistic (points, assists, etc.) is assigned a weighting, which is personalized to its box score stat such that each weighting reflects the statistic’s point-value. If that sounds a bit confusing, hopefully this example makes things clearer:

LeBron James committed 196 turnovers [2] during the 2022 regular season. Most basketball fans will agree that turnovers are bad! A turnover means the offensive team lost possession of the ball without having scored. Thus, they lost out on the opportunity to score points in that possession; and basketball is often a game that is won in a matter of possessions. Plus, there’s also the drawback from permitting the opposition a transition possession, which tends to yield more points than typical half-court offense. So we can all agree turnovers are bad, right? But how do we know how bad one is? Well, we have to consider what a turnover is taking away from, and the big thing is those aforementioned points the team could have scored if the ball weren’t turned over.

Since a variety of outcomes could’ve followed barring one of James’s turnovers, Hollinger decided to use a single placeholder number to sum up all possible outcomes of a possession. This estimates just how many points the Lakers were missing out on because of the turnover. Let’s think about it this way: on average, NBA offenses scored 1.12 points per possession in the 2022 regular season [3]. Hollinger concludes this was the best estimate of how much an offense is missing out on from turning the ball over, not accounting for how the opponent can gain a transition possession, as stated earlier. But since the turnover is deducting that amount of value, a turnover in 2022 is worth approximately -1.12 points! If we apply that weighting to all of LeBron James’s 196 turnovers this year, we can estimate that he cost the Lakers almost 220 points from his turnovers.

This process is done for all box score statistics (most of which have far more complicated weightings), and the results are summed up to estimate how many points a player is adding (or subtracting) to his team. However, as stated earlier, there is one last adjustment that converts the results to a per-possession basis. Namely, superstars don’t receive any benefits for playing more of the game. This “adjusted” form of PER is what you’ll see on Basketball-Reference or ESPN leaderboards. With that out of the way, let’s discuss the good and the bad of PER, and what its process means for the metric’s ability to evaluate players.

Believe it or not, there is some good stuff about PER. Take this as more of an opinion than a fact, but PER has solid (and interesting) critique behind it. The idea that each statistics has a hypothetical point-value behind it is logic that is used to this day, even with the most revered metrics like Estimated Plus/Minus and BBall-Index’s LEBRON; and PER was the first to do it. Let’s also consider the benefit to translating the results to per-possession rather than per-game or across an entire season. PER can be a reasonable tool for identifying hidden gems slotted at the end of the bench, and can act as an indicator of whether a role player is outperforming one of the better players on the team. Back when PER was the gold standard, there was some value it could provide to teams looking to manage their roster and shuffle their lineups. Not at all a bad result!

However, there are a considerable number of drawbacks to discuss with PER; and unfortunately, these dominate the conversation and are often valid concerns of the metric. Let’s return to the per-possession basis of PER. While there may be benefits, there are also flaws with this approach. There is the matter of fatigue in which players with a heavier load tend to tire out near the end of games, whereas role players can spend more of their time on the court with a fresh set of legs. Superstars also tend to player with better teammates, meaning they have fewer chances to exert their skill; and they often play tougher opponents, whereas role players tend to match up with the opponent’s bench units as well. That is, not all statistics are created equally, and a player’s impact can be reframed and reimaged depending on who else is on the court, which is something PER struggles to account for.

The other glaring issue with PER is that it lacks a benchmark, or some type of measurement to fall back on to confirm the metric is grounded in reliability. If you’re familiar with other popular impact metrics, you may remember that they are often backed by RAPM, which is arguably the strongest all-in-one metric basketball has to offer. If not, I have written in-depth about RAPM before [4] if you’re interested in learning more about it. (TW: Math.) PER has been around for nearly twenty years, so it’s no surprise that it has been one-upped by more recent metrics, but the larger issue is that John Hollinger has refused to update the metric. PER has been more or less the same since 2005, which excludes the metric from the comprehensive analytical techniques of today. This, paired with the inconclusive nature of the metric’s logic, makes PER one of the less viable options to analyze players.

Should You Use It?

The biggest argument against using PER is that there are many better alternatives, which is true. Estimated Plus/Minus, LEBRON, RAPTOR, and BPM, among others, all have more solid bases in accomplishing their goals. We’ve discussed the positives and the negatives of the metric, and are hopefully all able to recognize that both exist. But, again, PER is simply outdated. Hollinger’s refusal to refine his metric has left it in the dust. You’re much better off using the Backpicks (proprietary) or Basketball-Reference models of BPM if you’re looking to view a player’s impact from the perspective of the box score. But does this mean PER is bad?

I wouldn’t say so. PER has a very intriguing basis, and the logic Hollinger incorporated into the metric shows a considerable understanding of how basketball is played and won. Therefore, PER is still going to be quite a hit-or-miss metric, as lots of them are. But it’s not “bad” to the point that it measures every player off the mark. Heck, there’s the off-chance that PER pins a player down just right! However, it’s not great either, especially considering its peers. So the next time someone tells you PER is the worst thing to grace the Earth, tell them it could be worse. If it helps, tell them to look into Wins Produced from the Wages of Wins Journal. But that’s all from me, folks. I hope this was a somewhat insightful look into PER, and that you’re next perusing of a leaderboard is that much more confident.

[4] http://www.cryptbeam.com/2021/03/08/how-do-nba-impact-metrics-work/

• ## My Top-10 NBA MVP Candidates (2/27/22)

(📸 The Ringer)

The conflict between performing and storytelling on the basketball court has clouded the MVP race for decades; and like other highly-divisive topics in sports, both sides are represented by two camps:

### Criteria

Traditionally, the MVP has a very loose criterion that hinges on the voter’s ability to tell a story with their vote. For example, take 2011 Derrick Rose’s MVP. He was clearly not the best regular-season player that year, but the Chicago Bulls sneaked up behind the newly-formed Heatles and snagged the first seed in the East. Sure, the Bulls were successful because of their defense and not their offense, but Rose’s floor-raising efforts and acrobatic, engaging playstyle drew fans to the screens and promoted the league’s popularity. Was Derrick Rose the “Most Valuable Player” in 2011? No; but nominating him as the MVP was good for the NBA.

Perhaps more recently, there are those who strictly adhere to how “good” a player is when selecting their MVP ballot. This is a basketball-only approach that looks to recognize players based on their ability to affect a team’s chances of winnings: win-loss record, seeding, home-court advantage, all of that. There’s an obvious appeal here: it’s less biased than narrative-based voting when done right; it provides a sturdier baseline to evaluate candidates (not everyone cares who the best player on the best team is when using storylines); and it forces us to look closer at what’s happening on the court and overcome the deficiencies in our thought-processes.

I flesh out these two approaches to not advocate for one or the other, but to establish my priorities as I assemble this list. Typically, my content has been based around the second approach: trying to use observations and material evidence to support arguments for one player or another. While such an approach is fully appropriate for, say, a player rankings list, I’m not sure the same applies to the MVP Award. Perhaps the “Most Valuable Player” isn’t necessarily providing the most value toward winning, but toward the welfare of the Association. With this in mind, I’ll still reference a player’s actual skill and heavily weigh it in my final ranking, but another priority is how a player has been drawing fan interest and promoting league viewership to provide a more holistic view of who has been the NBA’s Most Valuable Player in 2022.

—-

10. Kevin Durant

The Slim Reaper has missed some time with injury troubles, but has still been playing around MVP levels when he’s on the court. Durant has assembled a masterful offensive skill set throughout his career, pairing his length in driving lanes with all-time shooting ability, which are exactly the types of characteristics you’d wish to see in a player who moves the needle for championship offenses.

9. Luka Doncic

The greatest basketball prodigy since LeBron James started off the season in a bit of a slump, but picked himself up in recent weeks, re-evolving into the dangerous offensive centerpiece we’ve seen him be for the third consecutive season. Doncic can hit defenses quickly with unexpected attacks and passes out of traps extremely well. He’s a similar build to James in that he can quarterback an elite offense surrounded by shooters who leverages his drive-and-kick game to their advantage. Dallas has also made a surprise entrance as a top-five team in the West by SRS. [1]

8. Chris Paul

The Phoenix Suns have been the best team in basketball so far, and it would be narratively unjust to go without recognizing one of their players. Among the league leaders in my hand-tracking of shot creation, Paul is a masterful pick-and-roll ball-handler, splitting defenses at will and punishing drop with his lethal mid-range shooting. He drives Phoenix’s offense and manages to play at All-NBA levels while fighting against Father Time’s inescapable aging curve. CP3 is a talent for the ages.

7. Ja Morant

My favorite player to watch in 2022 and the sport’s next great athletic freak. Morant has been the figurehead of an exciting Memphis Grizzlies squad while being one of the more improved players in the league, playing around All-NBA basketball this year. At his best, Morant creates easy offense like the game’s very best. His incredibly dynamic scoring and uncanny passing vision formulates one of the most unique offense skill sets in the sport. Morant will do all this and also steal defensive rebounds from your favorite big man.

6. DeMar DeRozan

DeRozan is one of very few players who have proved they can still be one of the game’s very best scorers without three-point shooting. He’s been breaking basketball with his mid-range shooting, making 51% of a mind-shattering 14.5 attempts per 75 possessions! [2] DeRozan’s storyline would arguably make him a finalist if I were more partial to narratives, but there’s too weak of a stance based on performance alone. Playoff concerns aside, this player has been a unit on the basketball court, revitalizing a stunted career and shedding loads of doubt from critics.

5. LeBron James

The King is still really good at basketball. He’s been having one of his best regular season in years, punishing defenses with the scoring that vaulted his name into the GOAT conversation many years ago. Also one of the best passers in the sport and an adequate floor-spacer whose timeless athletic prowess makes him a strong defensive player even in his nineteenth season. The regular season could be hinting toward the reemergence of Playoff LeBron in a few month’s time.

4. Giannis Antetokounmpo

Ah, the wonders of voter fatigue. The Greek Freak was the third finalist on my ballot from last year, and while he’s done an outstanding job of raising the ceiling for a smaller-market team, the league might do better spicing things up a bit. Regardless, Antetokounmpo is arguably the first or second-best player in basketball right now, making the fourth spot my absolute floor for him.

3. Stephen Curry

Probably the face of the NBA. Curry is among the league-leaders in merchandise sales [3] and promotes the best TV ratings [4] in the league. His scoring has taken a massive hit from its glorious past, but his ability to bend and break defenses remains. Curry is loved by impact metrics and is having one of the best defensive and passing seasons of his career. Given he had maintained his early-season hot streak, he would be the top player on this list. But for now, he slides back to third.

2. Joel Embiid

Embiid is a masterful scorer who pairs punishing brute force in the paint with grateful skill on the block that garnered (self-anointed) comparisons to the likes of Kobe Bryant and Hakeem Olajuwon. He’s still one of the strongest defenders in the league and an improving playmaker. The fans seem to want to see Embiid as a finalist for a second straight season, and such recognition is warranted.

1. Nikola Jokic

The claim for the best player in the league in 2022 seems particularly exclusive this season because of the Joker. We’re talking about a player who has legitimate arguments as both the best scorer and playmaker in the sport right now, blending three-level scoring with an unheralded array of passes that stretch defenses to their absolute limits. Jokic has also been a clear positive on defense this season. By the way, Denver outscoring teams by +9.7 points per 100 with him on the floor and have been 19.2 points worse with him off. [5]

[2] https://backpicks.com/2022-players/

[3] https://www.nba.com/news/nba-top-selling-jerseys

[4] https://sbi.co.in/web/sbi-in-the-news/research-desk

• ## Park-Adjusted Statistics for the MLB

(📸 MLB.com)

The development of sabermetrics in Major League Baseball has coincided with an increased awareness of confounders, one of which is the effect of ballparks and their playing environments. The ubiquitous example is Coors Field in Denver, whose abnormal elevation is known to cause baseballs to travel 5 to 10% farther than at typical sea level. [1] While comprehensive statistics like On-Base Plus Slugging (OPS) and weighted Runs Created (wRC) have spawned improvements that account for such prior knowledge, these principles have yet to be widely applied to traditional box scores. Thus, I set out to develop a subset of “park factors” that can be used to manipulate statistics like batting average and home runs to provide a more level playing field when comparing these measurements between players of varying ballpark conditions.

## The Example

Colorado Rockies players often have more scrutinized slash lines and power statistics because of the aforementioned data on the elevation effect. Let’s use home runs in the 2021 regular season as the example of park-adjusted statistics to observe the supposed bottom-line effect in home-run frequency between stadiums. To estimate a ballpark’s effect on home runs among all thirty teams, their home-run frequency (measured as home runs per plate appearance) is compared between home and away games. To include a larger breadth of information, a five-year data set was used. (For 2021, seasons 2017 through 2021 were used to calculate park factors.)

Because the entire league is usually more prone to hit home runs at home than on the road (likely stemming from the home-field advantage), a small adjustment is made to reflect this. Additionally, only half of the measured effect is added to the rating because teams split roughly half of their schedule between home and away games. Therefore, the final measurement we’re left with is the percent increment of a team’s home-run frequency on the road versus at home relative to the league. This park factor can be used on the player level, too. Let’s see how the power-hitting landscape changes when these listed adjustments are applied to MLB batters.

## The Results

NB: Traded players occupy multiple rows for each team played for.

Marcus SemienTOR43452
Fernando Tatis Jr.SDP4342-1
Shohei OhtaniLAA43463
Brandon LoweTBR4339-4
Matt OlsonOAK4139-2
Mitch HanigerSEA4139-2
Rafael DeversBOS4038-2
Tyler O’NeillSTL3934-5
Pete AlonsoNYM3837-1
Jose RamirezCLE3736-1
Kyle SeagerSEA3735-2
Aaron JudgeNYY36393
Mike ZuninoTBR3633-3
Paul GoldschmidtSTL3631-5
Brandon BeltSFG3429-5
Jorge PolancoMIN3433-1
Austin RileyATL3433-1
Yordan AlvarezHOU3433-1
Hunter RenfroeBOS3331-2
Giancarlo StantonNYY33352
Joey VottoCIN32364
Bryce HarperPHI32353
Freddie FreemanATL3231-1
Jose AltuveHOU31310
Franmil ReyesCLE3130-1
Miguel SanoMIN3130-1
Nick CastellanosCIN31343
Teoscar HernandezTOR31321
Ozzie AlbiesATL3130-1
Kyle TuckerHOU30300
J.D. MartinezBOS2928-1
Ryan MountcastleBAL29334
Mike YastrzemskiSFG2925-4
Matt ChapmanOAK2927-2
Jose AbreuCHW29301
Patrick WisdomCHC28280
Juan SotoWSN28291
Avisail GarciaMIL28291
Brandon CrawfordSFG2824-4
Eugenio SuarezCIN28313
Bo BichetteTOR28291
Dansby SwansonATL27270
Jared WalshLAA27292
Bryan ReynoldsPIT2724-3
Cedric Mullins IIBAL27303
Josh DonaldsonMIN2726-1
Carlos CorreaHOU26260
Bobby DalbecBOS2625-1
Josh BellWSN26271
Ian HappCHC25250
C.J. CronCOL25283
Rhys HoskinsPHI24273
Andrew McCutchenPHI24273
Ronald Acuna Jr.ATL24240
Kyle SchwarberWSN24251
Xander BogaertsBOS2423-1
Jesus AguilarMIA2422-2
Joey GalloTEX24251
Robbie GrossmanDET2423-1
Eduardo EscobarARI2322-1
Jonathan SchoopDET2322-1
Eric HaaseDET2322-1
Luis UriasMIL22231
Javier BaezCHC22220
Yasmani GrandalCHW22231
Randy ArozarenaTBR2220-2
Paul DeJongSTL2219-3
Carlos SantanaKCR2219-3
Jesse WinkerCIN22242
Jake CronenworthSDP21210
Gary SanchezNYY21232
Trevor StoryCOL21243
Seth BrownOAK2120-1
Willson ContrerasCHC21210
Enrique HernandezBOS2120-1
Randal GrichukTOR21221
George SpringerTOR21221
Buster PoseySFG2118-3
Wilmer FloresSFG2118-3
Francisco LindorNYM2120-1
Dylan CarlsonSTL2118-3
Ryan McMahonCOL20233
Lourdes Gurriel Jr.TOR20211
Jazz Chisholm Jr.MIA2018-2
Austin HaysBAL20222
Byron BuxtonMIN19190
Nelson CruzMIN19190
Max KeplerMIN19190
Andrew BenintendiKCR1917-2
Jonathan IndiaCIN19212
Ty FranceSEA1918-1
Jonathan VillarNYM1918-1
Trey ManciniBAL19212
Darin RufSFG1916-3
Cesar HernandezCLE1918-1
Hunter DozierKCR1816-2
Kris BryantCHC18180
Mark CanhaOAK1817-1
Sean MurphyOAK1817-1
Trea TurnerWSN17181
Nathaniel LoweTEX17181
Tyler NaquinCIN17192
Jeimer CandelarioDET1716-1
Tim AndersonCHW16171
Anthony SantanderBAL16182
Elias DiazCOL16182
Justin UptonLAA16171
Luis TorrensSEA1615-1
Kevin PillarNYM1615-1
J.T. RealmutoPHI15172
Jesus SanchezMIA1514-1
Trent GrishamSDP15150
Tommy PhamSDP15150
Yuli GurrielHOU15150
Evan LongoriaSFG1513-2
Alex DickersonSFG1513-2
Jed LowrieOAK1514-1
Ramon LaureanoOAK1514-1
Jorge SolerKCR1513-2
Jarred KelenicSEA1514-1
Michael ConfortoNYM1514-1
Ketel MarteARI1514-1
Kyle FarmerCIN14162
Ryan JeffersMIN14140
Andrew VaughnCHW14151
Jorge SolerATL14140
Chas McCormickHOU14140
Nelson CruzTBR1413-1
Yandy DiazTBR1413-1
Brett PhillipsTBR1413-1
Anthony RizzoCHC14140
Austin SlaterSFG1412-2
Rougned OdorNYY14151
Alex VerdugoBOS1413-1
Michael A. TaylorKCR1412-2
Ryan ZimmermanWSN14140
Kolten WongMIL14140
Carson KellyARI13130
Mitch GarverMIN13130
Brendan RodgersCOL13152
Frank SchwindelCHC13130
Gio UrshelaNYY13141
Jean SeguraPHI13141
Tommy EdmanSTL1311-2
Manny PinaMIL13130
Dylan MooreSEA1312-1
Luis RobertCHW12131
Sam HilliardCOL12142
Gregory PolancoPIT1211-1
Eric HosmerSDP12120
Alex BregmanHOU12120
Joey GalloNYY12131
Max StassiLAA12131
Joey WendleTBR1211-1
Ji-Man ChoiTBR1211-1
Odubel HerreraPHI12131
Didi GregoriusPHI12131
Tyrone TaylorMIL12120
DJ PetersTEX12120
Tom MurphySEA1211-1
Charlie BlackmonCOL11132
Dominic SmithNYM11110
Josh RojasARI11110
Daulton VarshoARI11110
Pavin SmithARI11110
Whit MerrifieldKCR1110-1
Amed RosarioCLE11110
Colin MoranPIT1110-1
Rafael OrtegaCHC11110
Joc PedersonCHC11110
Manuel MargotTBR1110-1
D.J. StewartBAL11121
Omar NarvaezMIL11110
Mitch MorelandOAK1110-1
Nick SolakTEX11110
Danny JansenTOR11110
Gavin SheetsCHW10111
James McCannNYM10100
Christian WalkerARI10100
Austin HedgesCLE10100
Ryan O’HearnKCR109-1
Luke VoitNYY10111
Lewis BrinsonMIA109-1
Garrett CooperMIA109-1
Miguel RojasMIA109-1
Pedro SeverinoBAL10111
Maikel FrancoBAL10111
Garrett HampsonCOL10111
Jonah HeimTEX10100
Eloy JimenezCHW10100
Jake FraleySEA990
J.P. CrawfordSEA990
Javier BaezNYM990
Steven DuggarSFG98-1
Willi CastroDET990
Niko GoodrumDET990
DJ LeMahieuNYY9101
Brett GardnerNYY9101
Kyle HigashiokaNYY9101
Yu ChangCLE990
Jack MayfieldLAA9101
Brent RookerMIN990
Tyler StephensonCIN9101
Aristides AquinoCIN9101
Yoshi TsutsugoPIT98-1
Ben GamelPIT98-1
Jacob StallingsPIT98-1
Dom NunezCOL9101
Lewin DiazMIA98-1
Yan GomesWSN990
Christian YelichMIL990
Daniel VogelbachMIL990
Tony KempOAK880
Taylor TrammellSEA880
Gleyber TorresNYY891
Brandon NimmoNYM880
David PeraltaARI880
Alex KirilloffMIN880
Ha-seong KimSDP880
Tommy La StellaSFG87-1
Donovan SolanoSFG87-1
Kris BryantSFG87-1
William ContrerasATL880
Michael BrantleyHOU880
Aledmys DiazHOU880
Jason CastroHOU880
Jason HeywardCHC880
David BoteCHC880
Freddy GalvisBAL891
Michael PerezPIT87-1
Lorenzo CainMIL880
Isiah Kiner-FalefaTEX880
Starling MarteMIA87-1
Brian AndersonMIA87-1
Wander FrancoTBR87-1
Alejandro KirkTOR880
Brian GoodwinCHW880
Anthony RizzoNYY781
Jose IglesiasLAA781
Mike TroutLAA781
Taylor WardLAA781
Kyle SchwarberBOS770
Jeff McNeilNYM770
Asdrubal CabreraARI770
Eddie RosarioCLE770
Josh NaylorCLE770
Jordan LuplowCLE770
Roberto PerezCLE770
Harold RamirezCLE770
Willians AstudilloMIN770
Trevor LarnachMIN770
Victor CaratiniSDP770
Marcell OzunaATL770
Eddie RosarioATL770
Travis d’ArnaudATL770
Joc PedersonATL770
Connor JoeCOL781
Edmundo SosaSTL76-1
Lane ThomasWSN770
Rowdy TellezMIL770
Andy IbanezTEX770
Cavan BiggioTOR770
Ke’Bryan HayesPIT76-1
Yermin MercedesCHW770
Francisco MejiaTBR76-1
Phil GosselinLAA671
Ronald TorreyesPHI671
Alec BohmPHI671
Christian VazquezBOS660
Christian ArroyoBOS660
Tucker BarnhartCIN671
Jose PerazaNYM660
Ramon UriasBAL671
Josh VanMeterARI660
Andy YoungARI660
Dustin GarneauDET660
Jake RogersDET660
Wilson RamosDET660
Zack ShortDET660
Joshua FuentesCOL671
Jake MeyersHOU660
Abraham ToroHOU660
Mauricio DubonSFG65-1
Curt CasaliSFG65-1
Josh HarrisonWSN660
Luis GarciaWSN660
Carter KieboomWSN660
Jace PetersonMIL660
Eduardo EscobarMIL660
Travis ShawMIL660
Willie CalhounTEX660
Jason MartinTEX660
Eli WhiteTEX660
Lars NootbaarSTL65-1
Jake LambCHW660
Edward OlivaresKCR65-1
Anthony AlfordPIT65-1
Phillip EvansPIT65-1
Kevin NewmanPIT65-1
Rodolfo CastroPIT65-1
Miguel AndujarNYY660
Anthony RendonLAA660
Juan LagaresLAA660
Kurt SuzukiLAA660
Jose RojasLAA660
Luis RengifoLAA660
Bryan De La CruzMIA550
Mike BrosseauTBR550
Mike MoustakasCIN561
Raimel TapiaCOL561
Stephen PiscottyOAK550
Starling MarteOAK550
Yan GomesOAK550
Danny SantanaBOS550
Abraham ToroSEA550
Kyle LewisSEA550
J.D. DavisNYM550
Billy McKinneyNYM550
Stephen VogtARI550
Kole CalhounARI550
Nick AhmedARI550
Victor ReyesDET550
Andres GimenezCLE550
Kyle GarlickMIN550
Abraham AlmonteATL550
Guillermo HerediaATL550
Robinson ChirinosCHC550
Jake MarisnickCHC550
Sergio AlcantaraCHC550
Matt DuffyCHC550
Andrew StevensonWSN550
Charlie CulbersonTEX550
Jose TrevinoTEX550
Seby ZavalaCHW550
Leury GarciaCHW550
Mike TauchmanSFG54-1
Clint FrazierNYY550
Albert PujolsLAA550
Justin WilliamsSTL54-1
Freddy GalvisPHI550
Wilmer DifoPIT440
Pat ValaikaBAL451
Nick FortesMIA440
Jorge AlfaroMIA440
Jon BertiMIA440
Isan DiazMIA440
Sandy LeonMIA440
Kevin KiermaierTBR440
Jordan LuplowTBR440
Shed Long Jr.SEA440
Jose MarmolejosSEA440
Brandon DruryNYM440
Daz CameronDET440
Renato NunezDET440
Daniel JohnsonCLE440
Owen MillerCLE440
Nick GordonMIN440
Jurickson ProfarSDP440
Pablo SandovalATL440
Jose SiriHOU440
Trayce ThompsonCHC440
Alcides EscobarWSN440
Keston HiuraMIL440
John HicksTEX440
David DahlTEX440
Corey DickersonTOR440
Rowdy TellezTOR440
Zack CollinsCHW440
Aaron HicksNYY440
Austin WynnsBAL440
Jason VoslerSFG330
Jose RondonSTL330
Matt CarpenterSTL330
Hoy ParkPIT330
Alex JacksonMIA330
Elvis AndrusOAK330
Aramis GarciaOAK330
Kevin PlaweckiBOS330
Travis ShawBOS330
Jonathan ArauzBOS330
Tomas NidoNYM330
Harold CastroDET330
Derek HillDET330
Ernie ClementCLE330
Andrelton SimmonsMIN330
Jake CaveMIN330
Ben RortvedtMIN330
Marwin GonzalezHOU330
Michael HermosilloCHC330
Starlin CastroWSN330
Billy McKinneyMIL330
Leody TaverasTEX330
Cesar HernandezCHW330
Mike FordNYY330
Max SchrockCIN330
Rio RuizBAL330
Nicky LopezKCR220
Hanser AlbertoKCR220
Ka’ai TomPIT220
Cole TuckerPIT220
Erik GonzalezPIT220
Corey DickersonMIA220
Josh HarrisonOAK220
Jarren DuranBOS220
Marwin GonzalezBOS220
Michael ChavisBOS220
Donovan WaltonSEA220
Sam HaggertySEA220
Cal RaleighSEA220
Evan WhiteSEA220
Josh ReddickARI220
Jake McCarthyARI220
JaCoby JonesDET220
Myles StrawCLE220
Rene RiveraCLE220
Wilson RamosCLE220
Jake BauersCLE220
Rob RefsnyderMIN220
Gilberto CelestinoMIN220
Luis ArraezMIN220
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Riley SmithARI000
Alexander WellsBAL000
Darwinzon HernandezBOS000
Michael KingNYY000
Charlie BarnesMIN000
Brandon BielakHOU000
Griffin CanningLAA000
Drew CarltonDET000
Tucker DavidsonATL000
Kevin GinkelARI000
Tanner HouckBOS000
Gabe KlobositsWSN000
Alex LangeDET000
Clarke SchmidtNYY000
Jose SuarezLAA000
Trevor StephanCLE000
Jhon RomeroWSN000
Ljay NewsomeSEA000
Jesus LuzardoOAK000
Jesus LuzardoMIA000
Zach PlesacCLE000
Bryse WilsonPIT000
Dylan LeeATL000
Tyler WellsBAL000
Wyatt MillsSEA000
John SchreiberBOS000
Hunter OwenPIT000
Darren McCaughanSEA000
Ronald BolanosKCR000
Sean GuentherMIA000
Kaleb OrtBOS000
Bailey FalterPHI000
Miguel SanchezMIL000
Mauricio LloveraPHI000
James KarinchakCLE000
Nick NelsonNYY000
Nate PearsonTOR000
Ty TiceTOR000
Ty TiceATL000
Zach PopMIA000
Ben BowdenCOL000
Eli MorganCLE000
Jeremy BeasleyTOR000
Mike BaumannBAL000
Yennsy DiazNYM000
Tyler IveyHOU000
Zac LowtherBAL000
Griffin JaxMIN000
Mario FelicianoMIL000
Deivi GarciaNYY000
Jhonathan DiazLAA000
Alec BettingerMIL000
Andre ScrubbHOU000
Kyle DohyPHI000
Riley O’BrienCIN000
Ramon RossoPHI000
Matt ManningDET000
Bruce ZimmermannBAL000
Andres MunozSEA000
Tyler ZuberKCR000
Antonio SantosCOL000
Isaac MattsonBAL000
Anthony KayTOR000
Nick MargeviciusSEA000
Josh FlemingTBR000
Jovani MoranMIN000
Enoli ParedesHOU000
Peter SolomonHOU000
J.B. BukauskasARI000
Casey MizeDET000
Scott HurstSTL000
Kyle NelsonCLE000
Nick SandlinCLE000
Kutter CrawfordBOS000
JC MejiaCLE000
Yusei KikuchiSEA000
Cristopher SanchezPHI000
Manuel RodriguezCHC000
Eduard BazardoBOS000
Francisco PerezCLE000
Oliver OrtegaLAA000
Emmanuel ClaseCLE000
Seth MartinezHOU000
Luis GilNYY000
Thomas SzapuckiNYM000
Demarcus EvansTEX000
Dauri MoretaCIN000
Miguel YajurePIT000
Tyler PayneCHC000
Brooks KriskeBAL000
Brooks KriskeNYY000
Connor BrogdonPHI000
Lucas GilbreathCOL000
Jake LatzTEX000
Glenn OttoTEX000
Joe RyanMIN000
Ryan FeltnerCOL000
Kris BubicKCR000
Shane McClanahanTBR000
Daniel LynchKCR000
Reiss KnehrSDP000
Jackson KowarKCR000
Jake CousinsMIL000
Elvis PegueroLAA000
Kervin CastroSFG000
Luis OviedoPIT000
Jose MarteLAA000
Mason ThompsonWSN000
Mason ThompsonSDP000
Gregory SantosSFG000
Camilo DovalSFG000
Luis FriasARI000
Angel RondonSTL000
John KingTEX000
Aaron FletcherSEA000
Kyle TylerLAA000
Max KranickPIT000
Hans CrousePHI000
Mac ScerolerBAL000
Jon HeasleyKCR000
Paul CampbellMIA000
Logan GilbertSEA000
Shane BazTBR000
Tarik SkubalDET000
Dylan ColemanKCR000
Joe BarlowTEX000
Chris RodriguezLAA000
A.J. AlexyTEX000
Stephen RidingsNYY000
Nivaldo RodriguezHOU000
Carlos HernandezKCR000
Angel ZerpaKCR000
Roansy ContrerasPIT000
Luis PatinoTBR000
Spencer HowardTEX000
Packy NaughtonLAA000
Codi HeuerCHW000
Codi HeuerCHC000
Janson JunkLAA000
Damon JonesPHI000
Nick SnyderTEX000
Aaron AshbyMIL000
Ryan DorowTEX000
Brett de GeusTEX000
Brett de GeusARI000
Luis GarciaHOU000
Randy DobnakMIN000
Nick AllgeyerTOR000
Jonathan StieverCHW000
Cody WilsonWSN000
Andrew WantzLAA000
Austin WarrenLAA000
Cooper CriswellLAA000
Nick MearsPIT000
Drew RasmussenMIL000
Alek ManoahTOR000
Garrett CrochetCHW000
Reid DetmersLAA000
Spencer StriderATL000
Kohei AriharaTEX000
Hyeon-jong YangTEX000
Hirokazu SawamuraBOS000

The above table represents five properties: 1) the player’s name; 2) the team for which the player accrued his statistics; 3) his “adjusted” home run total, which uses his team’s park factor; 4) his raw home run total, which does not use his team’s park factor; and 5) “luck,” which measures the difference between his actual home run total and his adjusted home run total. If we sort the table to reflect the luckiest and unluckiest batters, their listed teams will start to reflect which ballparks have the greatest promotion for home runs and which ones do not. It’s no surprise that there are numerous Rockies players near the top of this list:

• C.J. Cron +3 (7th)
• Trevor Story +3 (10th)
• Ryan McMahon +3 (12th)
• Elias Diaz +2 (23rd)
• Brendan Rodgers +2 (30th)
• Sam Hilliard +2 (34th)
• Charlie Blackmon +2 (37th)

Interestingly enough, Colorado has the lowest home-run park factor in 2021, which means the Coors Field environment has the most positive effect on homers compared to other ballparks! Conversely, we can sort to find the “unluckiest” batsmen in the league. Here, we (expectantly) see a whole new crop of players and teams:

2. Tyler O’Neill -5 (STL)
4. Brandon Belt -5 (SFG)
5. Paul Goldschmidt -5 (STL)
6. Mike Yastrzemski -4 (SFG)
7. Brandon Crawford -4 (SFG)
8. Brandon Lowe -4 (TBR)
9. Mike Zunino -3 (TBR)
10. Buster Posey -3 (SFG)

The analytical approach does seem to corroborate the traditional ideas about Coors Field while also revealing insights into which ballparks don’t induce more home runs than usual. Here are the top-5 and bottom-5 teams in this 2021 version of the home-run park factor (higher meaning worse home-run environment, lower meaning better):

• San Francisco Giants (1st)
• St. Louis Cardinals (2nd)
• Kansas City Royals (3rd)
• Pittsburgh Pirates (4th)
• Miami Marlins (5th)
• Los Angeles Dodgers (26th)
• Cincinnati Reds (28th)
• Baltimore Orioles (29th)

• ## NBA All-Star Power Rankings (1/2/22)

(📸 ClevelandSports.org)

Ladies and gentlemen, welcome back to another edition of my NBA All-Star Power Rankings series! Here, I’ll detail the current landscape of the league’s best players and condense my thoughts into one All-Star ballot. Players will be arranged into tiers based on their level of play, which is entirely based on the degree of impact the player provides by helping teams gain higher seeding and home-court advantage for the Playoffs. To add a final disclaimer:

This list is not my “prediction” of the league’s actual All-Star teams lineups. This is a reflection of my evaluations of players, and where that would place them in the NBA’s award hierarchy.

Absolutely

Within the league’s top-25 or so players is a group that has fully established itself as All-Star-caliber (or better). There’s little to no doubt in my mind that these players should be headed to Cleveland in February.

• Giannis Antetokounmpo (East)
• Jimmy Butler (East)
• DeMar DeRozan (East)
• Kevin Durant (East)
• Joel Embiid (East)
• James Harden (East)
• Zach LaVine (East)
• Trae Young (East)
• Mike Conley (West)
• Stephen Curry (West)
• Anthony Davis* (West)
• Luka Doncic (West)
• Paul George* (West)
• Rudy Gobert (West)
• Draymond Green (West)
• LeBron James (West)
• Nikola Jokic (West)
• Donovan Mitchell (West)
• Ja Morant (West)
• Chris Paul (West)
• Karl-Anthony Towns (West)

Because these are players whom I firmly believe are All-Stars, I won’t belabor any points. I will address the two asterisks next to Anthony Davis’s and Paul George’s names, which were added due to uncertainty surrounding their injury status come February. Davis and George are both currently out with a sprained MCL and a torn elbow ligament, respectively. Both will be re-evaluated in a few weeks’ time.

Probably

The “Probably” group includes players I currently believe are All-Star-level, but I may not be entirely sold on their status. A lot of these players will make my final ballot, but whether it be injuries, a lack of signals, or general uncertainty about their playstyle, I distinguish them from those I wholeheartedly believe are All-Stars.

A unique mold of player for the modern game, Adebayo is on track to replicate his All-Star success from the last two seasons. He provides a level of spacing as a threat from the mid-range (39% on 8.6 attempts per 75) to tie into a strong overall scoring package, which he pairs with elite defense that has remained on the perennial DPOY watch.

Beal’s outside shooting slumped out of the gate, which was an attribute of his that was crucially valuable to an elite off-ball package. Resultantly, I can’t view him as an All-Star lock, but his passing and shot creation have been trending upward, which boosts his value in a floor-raising role, also helping to mask his questionable defensive play.

• Jrue Holiday (East)

Holiday is a player that provides a ton of value that the box score doesn’t capture. Adjusted Plus/Minus models have always looked fondly upon his shooting, passing, and tough brand of point-of-attack defense. After a while, it becomes hard to ignore what the analytics are communicating.

• Khris Middleton (East)

Minutes played alongside the Greek Freak have depleted Middleton’s scoring punch so far, (Middleton averages 28.5 points per 75 on 59% True Shooting as the lone star.) but his skills have still carried over: spacing, passing, and shot creation. My only setback is how those skills map to his overall impact; the metrics are concerningly low on Middleton thus far.

• Jayson Tatum (East)

After a rapid ascension in 2020, Tatum seems to have stagnated slightly. His shooting and scoring have been in decline, and he doesn’t have the playmaking chops like Lillard to make up for some of that value. He’s otherwise adding some on defense. This is one of many “Playoffs will tell” cases.

• Damian Lillard (West)

Lillard feels like an obvious choice most other seasons. The only reason I put him here is his early-season shooting slump. He’s quickly picked up where he left off previously, but his struggles have dented his scoring effectiveness and have slightly offset the continued value he brings as an elite playmaker.

Maybe

The league’s talent pool is stacked, and as a result I nearly overwhelmed the nominal threshold of an All-Star player being within the sport’s top-25. Since there’s a numerous amount of other players that provide impact in similar vain to these “probable” stars, the “maybe” talents serve as high sub-All-Stars and potential injury replacements.

• Jarrett Allen (East)
• LaMelo Ball (East)
• Darius Garland (East)
• Fred VanVleet (East)
• Devin Booker (West)

Again, perhaps these players could be viewed as legitimate All-Stars. The 2022 season hasn’t fully taken shape yet, which could mean rearrangement among the previous two tiers. I’m on the absolute fence with some of these players (e.g. Booker and Conley), whether it be more lack of indicators or too little room in the actual ballot.

Note: I’m omitting the “Not Quite There” tier from previous editions of this series due to the influx of information that comes as the season progresses.

Final Ballot

Once again, we reach the trickiest part of this exercise. It was difficult enough to sort the closest calls, but the task extends when putting these players into their All-Star slots. Similar to the previous editions, the ballots are structured to include two teams for either conference: five starters with two backcourt and three frontcourt players, five reserves (same restrictions), and two “wild cards” (no positional restrictions).

Eastern Conference

Starters:

• G: James Harden
• G: Trae Young
• F: Giannis Antetokounmpo
• F: Kevin Durant
• C: Joel Embiid

Reserves:

• G: DeMar DeRozan
• G: Zach LaVine
• F: Jimmy Butler
• F: Jayson Tatum

Wild Cards:

• W: Jrue Holiday
• W: Khris Middleton

The two closest calls here were 1) whether to give the last frontcourt reserves slot to Adebayo or Middleton and 2) whether to give the second wild-card slot to Middleton or Bradley Beal.

Western Conference

Starters:

• G: Stephen Curry
• G: Luka Doncic
• F: LeBron James
• C: Rudy Gobert
• C: Nikola Jokic

Reserves:

• G: Damian Lillard
• G: Donovan Mitchell
• F: Anthony Davis*
• F: Paul George*
• C: Karl-Anthony Towns

Wild Cards:

• W: Chris Paul
• W: Draymond Green

Given the injuries to Davis and George persist, the roster would be rearranged to bump Draymond Green up to a frontcourt reserve slot, give Mike Conley the vacant wild card slot, and move Kristaps Porzingis into the second frontcourt reserve slot.

Data from:

• Backpicks.com
• PBPStats.com