![]() ![]() For this analysis I combined the outside wing positions (LW + RW = OW), the outside fullback positions (LWB + RWB + LB + RB = OB), outside midfielders (LM + RM = OM), and strikers with center forwards (CF + ST = ST). At the bottom of the table I provide an Average Error row, which represents the absolute average error between the model’s prediction for a given player rating and the actual EA player rating (all error values are well below 1.0, meaning that predictions using these coefficients are very close to the actual rating on each card).Īs a fun follow-up analysis, I ran the data through a t-SNE dimensionality reduction method, using the 29 performance categories as features. Finally I reran the GLM to get the coefficients shown in each table below. For each position, I performed a GLM with no intercept term, then I removed any variable with an insignificant p-value (PVAL>.01) or a negligible coefficient (COEF <. I web-scraped all the player data from for all 20,760 players, and used a general linear model to determine the coefficients for each position. ![]() So, naturally, I’ve decided to determine these coefficients myself. ![]() ![]() I have scoured the internet for these positional coefficients, and have not found an updated source for all positions, for FIFA 21. What gives? According to this article, EA uses positional coefficients to determine a player’s overall rating. The same is true if you took the average of all 29 substats. However if you were to take the average of these values for Acuna, and compare them to Pogba, you will find that Acuna has a higher average, even though Pogba has an overall rating 3-points higher: Acuna: (76 + 74 + 82 + 86 + 78 + 82)/6 = 79.6 This rating must somehow be based on an aggregate of a player’s rating in each of 29 different categories (shown below for Marcos Acuna).Īt first it may be tempting to assume that a player’s overall rating is based on a simple average of the 6 main category values (PAC, SHO, PAS, DRI, DEF, PHY). To clarify, each player is given an overall rating, shown on the top-left of each card. I’m specifically referring to how an overall rating is determined for each player, based on each player’s individual sub-stats. I’m not referring to how EA collects data from the real world and assigns attribute values to each player. How EA determines FIFA player ratings has been a source of mystery to me since I started playing FIFA around three years ago. “We need more games on TV, bigger budgets, and fairer coverage by the media.” Tweet from is the only Australian in the top 15, with Rapinoe one of four Americans alongside Tobin Heath, Alex Morgan and Julie Ertz.How are the card ratings calculated in FIFA Ultimate Team? “This is another example of the underinvestment, resourcing, and attention paid to women’s football. “I am not the best,” she tweeted, adding that she was definitely among the top players. When her place at the top of the pile was criticised on social media, she admitted she may not be the best player, but being the most prominent helped her top the ratings. She has also regularly spoken out about social issues – particularly LGBT+ rights, equal pay for women and systemic racism, putting her front and centre. Rapinoe has become the most famous face in women’s football thanks largely to her star turn as the United States won their fourth Women’s World Cup in 2019. Kerr and France’s Wendie Renard are one point lower at 92, with Netherlands and Arsenal star Vivanne Miedema and another Frenchwoman, Amandine Henry, rounding out the top five at 91 each. ![]()
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