Radar Chart Baseball Cards


Inspired by the radar charts I would spend way too long studying in my childhood video games, I wanted to create something similar for baseball players.

I chose a baseball card format for the execution because baseball cards have always been a great way to see what a player looks like and also see his stats(traditionally by flipping the card over). I wanted to provide something besides just a picture, name, team and position to the front of the card.

The radar chart is the perfect addition to the front of a card as it provides a quickly digestible array of information to give you a sense of a player’s skills.

A radar chart found in my Pokemon video game guide from 1999


Stats Explanation

Just keep scrolling if you are only here to see what the cards look like. But if you want to know more about the actual stats used then this is the section for you!

Finding the 5 Tools

Most baseball fans are familiar with the fabled “5 tools” used by scouts to evaluate players: hit for average, hit for power, speed, glove and arm. These 5 tools are a useful starting place in finding 5 tools to round out my radar chart but I want to tweak the 5 a bit to better suit what I think makes a player valuable.

“Hit for Average” can stay and I’ll call it CONTACT. Same goes for “Hit for Power." POWER and CONTACT are great components for evaluating a hitter but I want to add something that shows more of an all-around offensive ability. We’ll call it HITTING and it will include all aspects of a players hitting ability, including drawing walks.

Offense has been shown to be valuable enough in Wins Above Replacement formulas that I have no problem with it taking up 3 of my 5 tools. As a matter of fact, I’m going to combine the two defensive tools in the original 5, glove and arm, and turn it into DEFENSE.

The 5th and final tool will remain with the players feet. I’m calling it BASE RUNNING instead of speed because I don’t want to completely ignore a players instincts and acceleration as those are both huge components in a player turning his feet into value for his team.

Representing the 5 Tools

In order for these radar charts to work I need to come up with actual values to represent the tools I’m looking to showcase. Choosing one stat to represent each tool will allow me to find out exactly how good a player is in that stat. Finally, I’ll compare that result to the rest of the league to find out how much of that portion of the radar should be filled in.

contact: Batting Average

An obvious choice to represent the Contact tool. Batting average, while not without it’s flaws, is a good component to a bigger picture as it shows a player’s ability to make quality and consistent contact. Calculated by taking total hits divided by at bats.

Power: Isolated Slugging

A simple stat that does a great job of showing the amount of power a player has. Isolated Slugging focuses only on hits that go for extra bases(doubles, triples, homers) by subtracting a players batting average from their slugging percentage.

HITTING: Weighted Runs Created Plus

The most complicated stat so far but it’s a brilliant way to assess how good a hitter is. wRC+ factors in every single type of batting outcome, including walks, and even takes into account the park and league a player plays in. This stat can even be compared across generations because it takes into account the overall run environment of the season. If I could only take one stat onto a desert island…

fangraphs’ explanation

Base Running: Base Running Runs Above Average

No it’s not BRRAA, its shorthand is actually BsR. This is another advanced metric as it calculates a whole lot of things that players do on the bases and jams it all together into one number. Top-end speed is crucial for a good BsR but there are obviously other skills like reads, instincts and acceleration that this stat tries to value.

fangraphs’ explanation

Defense: Defensive runs above average

Finally, we have another all-encompassing metric. This is the best way to judge a player’s defensive skills if you want to look at just one number. The beauty of this metric is that it includes a positional adjustment making it possible to compare a Shortstop with a First Basemen, which is exactly what I need for this exercise.

fangraphs’ explanation

sample size

In order to have radar charts that more accurately reflect how good a player truly is I want a sample size that is bigger than just one season. 3 seasons of stats (2016-2018) feels right as it’s typically the time-frame used in most projections. I even dropped the plate appearance minimum down to 1000 to help capture some of the exciting young players that aren’t exactly veterans, but still have a sizable track record.

This sample size and plate appearance minimum churns out 237 players.


THe finishing touches

Using a proprietary metric called “Players whose charts I think will be interesting” I’ve chosen 15 players that I want to make charts for, but I still need the entire pool of players for the stats rankings to work. Off to excel we go.

percent rank.JPG

237 qualified players and their downloaded stats from 2016-2018 go into a spreadsheet. A Percentile Rank function on each stat churns out the necessary ranking for how each player compares to the other players in the player pool. This gives me the number used to fill in each player’s radar chart for the respective tool.


With all the stat stuff out of the way I had to work on the actual design of the cards. I wanted a consistent design across all of the cards and the distressed tan backdrop provides a good contrast with the important info on the card. Each card also has an edited photo with certain elements leaking out over the frame.

15 cards of 15 players from 15 different teams. A wide variety of players: some are the best in baseball, some are just elite in one skill.






Lucas Hooper